Echocardiography Calcium Score And Aortic Stiffness As Predictive Tools Of Severity Of Coronary Artery Disease. A Single Center Egyptian Experience

Echocardiography Calcium Score And Aortic Stiffness As Predictive Tools Of Severity Of Coronary Artery Disease. 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A Single Center Egyptian Experience Asmaa Ahmed, Alaa Roshdy, Adham Abdeltawab This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3912043/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Coronary artery disease (CAD) represents a leading cause of death worldwide. Coronary angiography represents the gold standard for diagnosis and selection of the best treatment for patients with CAD. However some efforts have been made to predict CAD severity and complexity using non-invasive methods to identify the patients at high risk for cardiovascular events with less risk to the patients and before doing coronary angiography. Characterization of coronary-artery calcification by computed tomography known as Coronary artery calcium score (CACS) is proven to be equivalent to the total coronary atherosclerosis load and the angiographically significant lesions. Echocardiographic calcium score is now validated against non-coronary calcium by computed tomography with lower cost and no irradiation safety issues for reclassification of cardiac risk. Aim and Objectives: to determine the correlation of echocardiography calcium score and Aortic stiffness to severity of coronary artery disease. Patients and Methods: Patients coming to Ain Shams University Hospitals for elective coronary angiography were subjected to history taking, examination, blood samples and echocardiographic examination. The calculated echocardiographic calcium score and calculated Aortic stiffness were correlated with their coronary angiography films. Results: The study included 45 patients. The mean final calcium score of the whole study group was 4.95±1.29. The mean Aortic distensibility was 0.0044±0.0029. The mean syntax score of the whole study group was 22.88±12.3. There was highly significant difference between the numerical values of syntax score and final calcium score. There was weak negative but significant correlation between the syntax score numerical value and aortic distensibility. Conclusion: Echocardiographic calcium score is associated with the severity of CAD. The relationship between Aortic stiffness by echocardiography and severity of CAD still needs further evaluation. The low cost, availability and the radiation free nature of echocardiography make it an attractive candidate regarding the non-invasive tools for prediction of CAD. Echocardiography calcium score coronary calcium score Aortic stiffness Atherosclerotic coronary artery disease Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 Figure 18 Figure 19 Figure 20 Figure 21 Figure 22 Figure 23 Figure 24 Figure 25 Figure 26 Figure 27 Figure 28 Figure 29 Figure 30 Figure 31 Introduction Cardiovascular diseases are the leading cause of death worldwide causing about 45.0 million adult deaths worldwide in 2002.Half of such deaths are caused by coronary artery disease (CAD). 1, 2 According to the World Health Organization (WHO), CAD cause 16.7 million deaths in the world each year. 3 Invasive conventional coronary angiography (CCA) is the gold standard technique for diagnosis and selection of best treatment for CAD. 4, 5 SYNTAX score (SS) is one of the scoring systems used for assessment of CAD severity and complexity. SS incorporates morphological features of lesions such as total occlusion, bifurcation, length and localizations of lesions based on the myocardial area at risk. 5 Characterization of coronary-artery calcification by computed tomography known as Coronary artery calcium score (CACS) is proven to be related to angiographically significant lesions. It's used as simple and readily available test for identifying coronary artery disease (CAD) in asymptomatic patients to predict the risk of CAD incidence apart from routine total risk scores. 6,7 The detection of cardiac calcification by echocardiography (non- coronary artery calcification ) has also been shown to be associated with atherosclerosis, severe coronary artery calcification. It may be of value in the evaluation of patients suspected of having CAD. 8–11 Using a large echocardiographic database, Mitral annular calcification (MAC) was found to be independently associated with incident CVD, cardiovascular death, and all-cause death. It can be considered as an overall marker of atherosclerotic burden. This finding confirms the importance of an abnormal mitral annulus as an important prognostic marker. 12, 13 In this study we detected the role of echocardiography calcium score as predictive tool of severity of coronary artery disease in correlation with the patients' coronary angiography and lipid profile. PATIENTS AND METHODS This study included 45 patients coming Ain Shams University Hospitals to do elective coronary angiography in the period between November 2018 and August 2019. Patients were subjected to history taking, examination, blood samples and echocardiographic examination. The echocardiographic calcium score was correlated with syntax score of their coronary angiography films. Also syntax score was divided into three groups; low risk ≤ 18, intermediate risk 18–27 and high risk groups > 27. The study protocol was approved by Ain Shams university faculty of medicine ethical committee. Exclusion criteria Patients not meeting the above inclusion criteria, Age less than 18 and more than 65, Poor patient echogenicity, patients with renal failure or on hemodialysis, patients presenting with ACS or cardiogenic shock, significant valvular heart disease, Aortic aneurysm, patients with AF or frequent premature beats. Methods: All patients were subjected to the following: 1. History taking with particular stress on: A- Renal impairment. B- Any valvular heart disease. C- Previous ischemic events and evidence of revascularization either by stenting or by surgery. D- Any aortic disease or aortic aneurysm. E- Family history of CAD 2. Clinical examination with particular stress on: Blood pressure as well as heart rate and rhythm. General signs of severe valvular lesions. Local cardiac examination for additional sounds or murmurs indicating severe valvular affection. Signs of dyslipidemia. 3. Blood samples were taken for lipid profile. 4. Standard trans-thoracic two-dimensional echocardiographic examinations: All patients were studied in the left lateral decubitus position by an expert cardiologist using an ultrasound system (General Electric Vivid Seven) using an S3 transducer. Standard 2D and M-mode echocardiograms were obtained in the apical four-chamber, apical two-chamber, apical long axis and left parasternal views according to the American society of echocardiography and the European Association of Echocardiography guidelines. 65 in order to calculate : A-Echo calcium score: Table 1, Figure 1-3 1-AVC was defined as focal areas of increased echogenicity and thickening of the aortic valve leaflets in the absence of aortic stenosis (velocity across the valve <2.5 m/sec). Each aortic valve leaflet was graded on a scale of 0 (normal) to 3 (severe) according to leaflet thickening and calcific deposits; the highest score for a given cusp will be assigned as the overall degree of aortic valve sclerosis. 10 2- MAC was defined as an intense and bright echo-producing structure located at the junction of the atrio-ventricular groove and posterior mitral valve leaflet and will be measured from the leading anterior to the trailing posterior edge and judged on a scale of 0 (normal) to 3 (severe). 10 3- Papillary muscle calcium was defined as a bright echo involving the head of 1 or both papillary muscles. 10 4- Aortic root calcium was defined as a focal or diffuse area of increased echo reflectance and thickening in the aortic root on the parasternal long-axis view. 10 5- A final score was derived as the sum of all identified cardiac calcific deposits and was in the range of 0 (no calcium visible) to 8 (extensive cardiac and aortic root calcific deposits). 10 B- Aortic stiffness: figure 4 To evaluate aortic stiffness, aortic diameters was measured by M-mode tracing of the ascending aorta at the level of 3-4 cms above the aortic valve from the parasternal long axis view in systole and diastole. After the acquisition of the 2 prerequisite parameters, several useful indices of local arterial stiffness were calculated after systolic and diastolic blood pressure that was measured manullay and the following formula; 1) Arterial diameter change (mm) = SD-DD 2) Arterial strain = (SD-DD)/DD 3) Elastic modulus E (p) = (SBP-DBP)/strain 4) Arterial stiffness index β=Ln (SBP/DBP)/strain 5) Arterial distensibility = (2×strain) /(SBP-DBP). SD: systolic diameter, DD: diastolic diameter, SBP: systolic blood pressure, DBP: diastolic blood pressure, Ln: natural logarithm.14 5. Cardiac catheterization: -Coronary angiography was performed by a team of expert interventional cardiologists. A detailed analysis of angiographic images was done by the operators. -Significant lesion was defined as a 70% or greater stenosis in the luminal diameter of any major epicardial coronary artery and 50% or greater in left main coronary artery. -The presence of significant lesions is determined based on visual estimation. Basal angiographic characteristics of patients such as diseased vessel, left main coronary artery (LM), left anterior descending (LAD) coronary artery; right coronary artery (RCA), circumflex coronary artery (LCX), and diseased vessel number are recorded. -Syntax Score was calculated using dedicated software (version 2.11, www.syntaxscore.com), the acceptable core-lab reproducibility of SYNTAX score that has been reported which integrates two components:15 (a) morphological features of each lesion such as dominance, chronic total occlusion (CTO), bifurcation, trifurcation, tortuosity, heavy calcification, lesion length, presence of thrombus, aorto-ostial and diffuse lesions. (b) weighting factors of lesions based on myocardial area distal to lesion. Lesions with ≥ 50% luminal obstruction in vessels with a diameter ≥1.5 mm are added to provide SS. - All morphological features of each lesion included in SS were recorded. -The SS was divided into three tertiles as follows: low≤ 18, intermediate risk 18-27 and high risk groups >27. 16 -All angiograms were scored by experienced interventional cardiologist who was blinded to echocardiography calcium score and aortic stiffness measurement data. Statistical analysis: Analysis of data was done using statistical program for social science (SPSS) version 16 as follows: Quantitative variables were described as mean, standard deviation (SD) and range. Qualitative variables were described as number and percentage. Unpaired t-test was used to compare quantitative variables, in parametric data (SD < 50% mean).Comparison between groups as regards qualitative variables was done by using chi-square test. Fisher exact test was used instead of chi-square when one expected cell is less than 5.One way ANOVA (analysis of variance) test was used to compare more than two groups as regard quantitative variable. Spearman correlation co-efficient test was used to rank variables versus each other positively or inversely. Receiver operator characteristic (ROC) curve was used to find out the best cut-off value, and validity of certain variable. P value > 0.05 was non-significant (NS), P < 0.05 was significant (S), and P < 0.001 was highly significant (HS). RESULTS Our study included 45 patients who did elective coronary angiography in Ain Shams university hospitals. All patients were assessed clinically followed by 2D echocardiographic assessment to calculate non-coronary calcium score. Coronary angiography films were used to calculate syntax score that was divided into three groups; low risk ≤ 18, intermediate risk 18-27 and high risk groups >27. Also number of vessels affected was recorded. 1-Demographic and clinical data of the study population: The study included 45 patients; 21 of which were males representing 46.6% of the participants. The mean age of the whole group was 52.7 ± 8.18. 48.8% (22/45) of the participants were diabetic while 64.4% (29/45) were hypertensive. 42.2% (19/45) had previous ischemic history and 4.4% (2/45) had positive family history of CAD. As regards smoking; 9 (20%) patients were smokers, 10 (22.2%) patients were ex-smokers and 26 (57.7%) patients were non- smokers. 2- Lab, echo and angio data: Lipid profile of the study population The mean total cholesterol level among the whole study group was 170.24±27.26, the mean LDL level was 107.33±23.95 , the mean HDL level was 41.15±6.87 and finally the mean TGA level was 154.91±62.2. Echocardiographic data of the study group: Calcium score: The mean final calcium score of the whole study group was 4.95±1.29, the breakdown of this calcium score was as follows: mean Aortic calcium score was 1.22±0.559, mean mitral annular calcium score was 2.33± 0.674 , mean papillary muscles calcium score was 0.644±0.48,and finally mean aortic root calcium score was 0.755±0.43 Aortic stiffness: Mean arterial diameter change was 2.48 ± 1.3, mean strain was 0.092 ± 0.051, mean elastic modulus was 633 ± 351.3, mean stiffness index was 7.57 ± 4.74 and mean Aortic distensibility was 0.0044±0.0029. LV systolic & diastolic function and SWMA: 33 persons had normal LV systolic function representing 73.3% of the whole group while 17 persons had normal diastolic function representing 37.7% of the whole group.27 persons had no SWMA representing 60% of the whole group. Data obtained from coronary angiography: The mean syntax score of the whole study group was 22.88±12.3. 8 (17.7%) patients had no vessels affected. 10 (22.2%) patients had one vessel affected, 6 (13.3%) patients had two vessels affected and 21 (46.6%) patients had more than two vessels affected. 3- Data related to presence and absence of affected coronaries: The study group was subdivided into two subgroups according to presence (n=27) or absence (n=8) of significant CAD. All demographic data matched among the two subgroups except for sex, DM and smoking that showed significant difference. There was more females in sub-group with non-affected coronaries (p value 0.033). The subgroup with affected coronaries had more diabetic patients (p value 0.023). All the subgroup with non-affected coronaries were non-smokers (p value 0.029) (Tables 2,3) (Figures 5-7). There was no significant difference between both sub-groups as regards any of the lipid profile parameters measured (Table 4). Comparing different items of calcium score between the two sub-groups yielded highly significant difference in Aortic root calcification (p value 0.00) and significant difference in Aortic valve calcification & final calcium score (p value 0.047, 0.011 respectively). Patients with significant CAD had higher aortic root calcification, aortic valve calcification and total calcium score (Table 5) (Figures 8-10). Comparing Aortic stiffness data among both subgroups yielded no significant difference regarding aortic distensibility, on the other hand there was highly significant difference between the two subgroups regarding arterial diameter change & strain (p value 0.007 , 0.004 respectively) and significant difference in the stiffness index (p value 0.021). (Table 6) (Figures 11-13). There was no significant difference between both subgroups regarding LV systolic & diastolic function and SWMA (Table 7). Multivariate regression analysis for the individually significant variables shown in the univariate analysis was done(Table 8). Only Aortic root calcification was shown to be significant independent predictor of CAD by multivariate analysis (Table 9). 4- Data related to number of affected coronaries: The study group was subdivided into 4 subgroups as regard number of vessels affected. All demographic data matched among the four subgroups except for DM which was predominantly present in the subgroup with multi-vessel disease (p value 0.004) (Table 10-12) (Figure 14). Comparing different items of calcium score between the four sub-groups showed highly significant difference regarding Aortic root calcification (p value 0.004) and significant difference regarding final calcium score (p value 0.027).(Table 13)(Figures 15,16). Comparing Aortic stiffness data among the four subgroups yielded no significant difference regarding aortic distensibility, meanwhile it showed highly significant difference regarding arterial diameter change & strain (p value 0.008 , 0.007 respectively) and significant difference regarding stiffness index (p value 0.028).(Table 14) (Figures 17-19). There was no significant difference between the four subgroups regarding LV systolic & diastolic function and SWMA (Table 15). 5- Data related to syntax score: The study group was subdivided according to disease severity as estimated by syntax score into three subgroups. There was no significant difference between the subgroups as regard age but there was significant difference in gender distribution (Table 16). Patients with higher syntax scores were predominantly diabetics (Table 17) (Figures 20-22). All the lipid profile matched among the three sub-groups except TGS level which was highly significant (p value 0.003).(Table 18) (Figure 23) There was significant difference between the three subgroups of the syntax score regarding total calcium score (p value 0.013) (Table 19) (Figure 24). However the three subgroups showed no significant difference as regard any of the aortic stiffness parameters measured (Table 20) There was significant difference between the three subgroups of the syntax score concerning SWMA (p value 0.02) (Table 21) (Figure 25). 6-Correlation between final calcium score and Aortic stiffness & angiographic data( syntax score and number of vessels affected): There was weak negative but significant correlation between the total calcium score and arterial diameter change, strain and distensibility. There was a weak positive but significant correlation between the total calcium score and elastic modulus, stiffness index and syntax score subgroups. There was modest positive but significant correlation between the total calcium score and both syntax score and number of vessels affected. (Table 22) (Figures 26-28) There was weak negative but significant correlation between the syntax score numerical value and distensibility. There was modest negative but significant correlation between the syntax score numerical value and arterial diameter change and strain. There was a weak positive but significant correlation between the syntax score numerical value and stiffness index. There was modest positive but significant correlation between the syntax score numerical value and final calcium score. (Table 23) 7- Receiver operateor characteristic (ROC) anaylsis for prediction of CAD Final calcium score The receiver operator characteristic analysis of final calcium score ≥ 5 served as the best cut-off for CAD identification with the highest balanced sensitivity and specificity: 78% and 75% respectively (AUC 0.7804, P value 0.0012) (figure 29). Aortic stiffness variables: Stiffness index The receiver operator characteristic analysis of stiffness index score ≥ 5.47 served as the best cut-off for CAD identification with the highest balanced sensitivity and specificity 62% and 100% respectively (AUC 0.7432, P value 0.0006). (figure 30) Elastic modulus: The receiver operator characteristic analysis of elastic modulus ≥ 620 served as the best cut-off for CAD identification with the highest balanced sensitivity and specificity: 55.5% and 100% respectively (AUC 0.72, P value 0.003) (figure 31) Discussion Cardiac calcifications have been historically recognized since the early days of ultrasound imaging but only recently the correlation between coronary calcification and cardiac non-coronary calcium measured either by echocardiography or by computed tomography was investigated. 17 The detection of cardiac and vascular calcification (non- coronary artery calcification) has also been shown to be associated with atherosclerosis, severe coronary artery calcification and with obstructive coronary artery disease. It may be of value in the evaluation in patients suspected of having CAD. 17,18 Echocardiographic calcium score is now validated against non-coronary calcium by computed tomography with lower cost and no irradiation safety issues for reclassification of cardiac risk. It's significantly and independently associated with all-cause mortality and stroke, with higher scores reflecting higher risk. 18 In parallel; many epidemiological studies have demonstrated the predictive value of aortic stiffness as an independent predictor of cardiovascular (CV) morbidity and mortality. 19,20 . In this study we tried to detect the role of echocardiography calcium score and aortic stiffness as predictive tools of severity of CAD by establishing a correlation between these variables and the patients' coronary angiography and lipid profile. We compared each component of the echo calcium score and the final score with the syntax score subgroups. Also we detected the correlation of aortic stiffness with the syntax score subgroups as well as the final calcium score. According to the coronary angiography we divided the study group again into two subgroups; first with no coronaries affected and the other with affected coronaries and we analyzed the data we got to detect the significant parameters we studied in this correlation. Our study detected significant correlation between final calcium score by echocardiography and syntax score sub-groups and highly significant correlation with the numerical syntax score, that was similar to Gaibazzi N et al. that reported comparable strength of correlation in larger group of similar patients who had clinical indication to do CCTA and echocardiography.This study correlated echocardiographic calcium score with CCTA scores of coronary calcium score, non-coronary cardiac calcium and number of coronaries affected. It detected positive correlation of the final echocardiographic calcium score with the coronary calcium score obtained by CT coronaries. 10 Gaibazzi N et al. also showed a correlation between the echocardiographic calcium score and number of coronaries affected but only when the severe definition of CAD was applied (stenosis diameter > 70%) in CCTA, that was partially similar to our results that showed highly significant correlation between Aortic root calcification and number of affected coronaries and significant correlation between final calcium score and number of affected coronaries but we applied it on a stenosis diameter > 50% in CA. 10 Our study used ROC curve to detect the best cut-off point of final calcium score and each of aortic stiffness variable to detect CAD (at least single vessel with >50% stenosis) with balanced sensitivity and specificity of each parameter. The capability of final calcium score to predict CAD was better than both stiffness index and elastic modulus. Among all the demographic criteria and risk factors in our study, only sex, DM and smoking were significantly different between the group with affected coronaries and the group without. That was discordant with Gaibazzi N et al. that showed only age and prevalence of hypertension were significant. The prevalence of diabetics in our study was 48.8% compared to their prevalence that was only 14%. However the prevalence of males, active smokers and hypertensives were comparable with 46.6%, 20%, 64.4% respectively in our study and 52%, 30% and 65% Gaibazzi et al. 10 Regarding the number of vessels affected among the study population; it was 17.7% with no coronaries affected, 22.2% with one vessel affected, 13.3% with 2 vessels affected and 46.6% with more than two vessels affected. On the other hand the majority of patients in Gaibazzi et al. Study (61%) had no significant CAD which may have played a role in the difference of results between the two studies. 9 Pressman GS et al. also detected the correlation between echocardiography calcium score and CAD in similar group of patients who had clinical indication to do CCTA. This study had almost the same number of participants as our study group (41). The echocardiography calcium score had different items and CAD was evaluated as CAC in CCTA. It showed significant correlation between both. 9 It also showed that the total cardiac calcium is better in prediction of CAD than MAC alone without commenting on other components of calcium score.30 In our study only the final calcium score had significant correlation with syntax score sub-groups but when the calcium score was correlated with the presence or absence of affected coronaries it showed highly significant correlation with Aortic root calcification and significant correlation with Aortic valve calcification as well as the final calcium score. The mean echocardiographic cardiac calcium score in this study was 3.4 (±2.5) while in our study the mean score was 4.95±1.29. 9 Corciu AI et al. detected comparable strength of correlation in a larger group of patients (n=167) who where hospitalized. This study compared Echocardiographoc calcium score with Framingham risk score, Duke score and left ventricle mass index. It showed significant correlation between echocardiographic calcium score and the presence of CAD. Echocardiographic calcium score was assessed as calcium score index (CSI) that didn’t include papillary muscle calcification as a part of the score and the presence of CAD was assessed by Duke score that divided their study population into two subgroups. It also showed significant increase in the mean CSI with the presence of affected coronaries. This study also showed significant correlation of each component of the CSI with the presence of CAD . 21 Our study showed no significant correlation of each single component of echocardiography calcium score with the syntax score sub-groups, but when correlated with presence or absence of affected coronaries it showed highly significant difference in Aortic root calcification and significant difference in Aortic valve calcification as well as the final calcium score. Also when correlated with the number of affected coronaries it showed highly significant difference in Aortic root calcification as well as the final calcium score. In comparison to the multivariate regression analysis that was done in our study and showed no individually significant predictors of presence of affected coronaries other than Aortic root calcification, Corciu AI et al. study showed that hypercholesterolemia, diabetes, gender and CSI were individually significant predictors of CAD status. The receiver operator characteristic analysis of CSI=4 served as the best cut-off for CAD identification in Corciu AI et al. study, but in our study the cut-off for CAD identification was ≥ 5 with 78% sensitivity and 75% specificity. 21 Only few studies detected the correlation between Aortic stiffness and CAD; Elbasan Z et al. correlated Aortic distensibility assessed by echocardiography with syntax score in larger group of similar population (n=376) that had clinical indication to do coronary angiography. It showed that SS was significantly higher in the AD low group compared to the AD high group. 22 Ahmadi N et al. showed that impaired Aortic distensibility measured by computed tomography was strongly correlated with the severity of coronary atherosclerosis.71 Yildiz A et al. showed that AD was independently correlated with the severity of CAD assessed by the Gensini score in 56 stable CAD patients. 23 In our study, the Aortic stiffness variables were correlated with syntax score, presence or absence of coronaries and with number of coronaries affected. When correlated with syntax score subgroups there was no significant correlation with each of aortic stiffness variables but when correlated with the numerical values of syntax score there was weak negative but significant correlation with distensibility. There was modest negative but significant correlation with arterial diameter change and strain. There was a weak positive but significant correlation with stiffness index.When correlated with presence or absence of affected coronaries, there was highly significant difference in arterial diameter change & strain and significant difference in stiffness index. When correlated with the number of affected coronaries, there was highly significant difference in arterial diameter change & strain and significant difference in stiffness index. The variability in the results regarding Aortic stiffness between the current study and others may be due to variation in methodology whether by echo or by CT and also due to non-invasive measurement of systolic and diastolic blood pressure that may have been also affected by the patients’ medications or their presence in hospital setting. Our study detected highly significant correlation between final calcium score and aortic stiffness that was not evaluated in any previous study. Conclusion Atherosclerotic CAD stands out as a very important public health problem responsible for most of the cardiovascular mortalities in both developing and developed country. Echocardiographic calcium score is associated with the severity of CAD and number of coronaries affected and thus it can be used as a new tool for cardiovascular risk stratification. The relationship between Aortic stiffness by echocardiography and severity of CAD still needs further evaluation. The low cost, availability and the radiation free nature of echocardiography make it an attractive candidate for the on-going research regarding the non-invasive tools for prediction of CAD. Declarations Disclosure: None Conflict of Interest: None References Nasir K, Clouse M. Role of nonenhanced multidetector CT coronary artery calcium testing in asymptomatic and symptomatic individuals. Radiology. 2012;264:637–649. Sharma M, Ganguly NK. Premature coronary artery disease in Indians and its associated risk factors. 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Impaired aortic distensibility measured by computed tomography is associated with the severity of coronary artery disease. Int J Cardiovasc Imaging 2011; 27: 459–469. Tables Table 1:Grading system of cardiac and aortic root calcium on echocardiographic examination. 14 Grade Papillary muscle calcium Mitral annular calcium Aortic valve sclerosis Aorta root calcium 0 Absent Absent Absent Absent 1 Present Mild 10 mm Severe Aortic valve sclerosis graded as follows: Absent = Normal cusp thickness (2 mm and/or increased reflectivity; Moderate = Thickness >4 mm and/or diffuse or focal cusp hyperreflectivity; Severe = Thickness >6 mm and/or marked echoreflectivity. Final score was graded from 0 to 8. (Cho JY, Kim KH. Evaluation of Arterial Stiffness by Echocardiography: Methodological Aspects. Chonnam Med J. 2016;52(2):101–106. doi:10.4068/cmj.2016.52.2.101.) Table ( 2 ): Comparison between the two subgroups regarding age and sex Affected vessels Test value P-value Sig. No affected vessels Affected vessels No. = 8 No. = 37 Age Mean ± SD 49.00 ± 8.35 53.51 ± 8.03 -1.432• 0.159 NS Range 37 – 60 35 – 65 Sex Female 7 (87.5%) 17 (45.9%) 4.564* 0.033 S Male 1 (12.5%) 20 (54.1%) P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant *: Chi-square test; •: Independent t-test Table ( 3 ): Comparison between the two subgroups regarding clinical risk factors History Affected vessels Test value* P-value Sig. No affected vessels Affected vessels No. = 8 No. = 37 DM No 7 (87.5%) 16 (43.2%) 5.156 0.023 S Yes 1 (12.5%) 21 (56.8%) HTN No 2 (25.0%) 14 (37.8%) 0.473 0.492 NS Yes 6 (75.0%) 23 (62.2%) Smoking No 8 (100.0%) 18 (48.6%) 7.110 0.029 S Smoker 0 (0.0%) 9 (24.3%) Ex smoker 0 (0.0%) 10 (27.0%) Previous ischemic events No 6 (75.0%) 20 (54.1%) 1.183 0.277 NS Yes 2 (25.0%) 17 (45.9%) Family history No 7 (87.5%) 36 (97.3%) 1.487 0.223 NS Yes 1 (12.5%) 1 (2.7%) P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant *: Chi-square test Table ( 4 ): Lipid profile among both sub groups: Lipid profile Affected vessels Test value• P-value Sig. No affected vessels Affected vessels No. = 8 No. = 37 Total cholesterol Mean ± SD 165.50 ± 29.20 171.27 ± 27.14 -0.538 0.593 NS Range 135 – 217 125 – 268 LDL Mean ± SD 100.50 ± 23.38 108.81 ± 24.14 -0.888 0.380 NS Range 76 – 150 71 – 176 HDL Mean ± SD 43.38 ± 4.72 40.68 ± 7.22 1.008 0.319 NS Range 35 – 50 30 – 61 TGS Mean ± SD 124.38 ± 30.62 161.51 ± 65.53 -1.556 0.127 NS Range 98 – 187 60 – 334 P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant •: Independent t-test Table ( 5 ): Calcium score among both subgroups: Calcium score Affected vessels Test value≠ P-value Sig. No affected vessels Affected vessels No. = 8 No. = 37 Aortic valve Median (IQR) 1 (1 – 1) 1 (1 – 2) -1.983 0.047 S Range 0 – 1 0 – 3 Mitral annulus Median (IQR) 2 (2 – 3) 2 (2 – 3) 0.000 1.000 NS Range 2 – 3 1 – 3 Aortic root Median (IQR) 0 (0 – 0.5) 1 (1 – 1) -3.628 0.000 HS Range 0 – 1 0 – 1 Papillary muscle Median (IQR) 0 (0 – 1) 1 (0 – 1) -1.736 0.083 NS Range 0 – 1 0 – 1 Final score Median (IQR) 4 (3 – 4.5) 5 (5 – 6) -2.541 0.011 S Range 2 – 6 2 – 7 P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant ≠: Mann-Whitney test Table ( 6 ): Aortic stiffness among both sub-groups: Aortic stiffness Affected vessels Test value P-value Sig. No affected vessels Affected vessels No. = 8 No. = 37 Arterial diameter change Mean ± SD 3.63 ± 1.06 2.33 ± 1.20 2.815• 0.007 HS Range 3 – 6 1 – 5 Strain Mean ± SD 0.14 ± 0.05 0.08 ± 0.05 3.008• 0.004 HS Range 0.09 – 0.24 0.03 – 0.17 Elastic modulus Median (IQR) 387.5 (276.67 – 473.33) 647.5 (366.67 – 1050) -1.933≠ 0.053 NS Range 166.67 – 550 180 – 1920 Stiffness index Median (IQR) 3.74 (2.88 – 4.14) 7.14 (3.52 – 10.44) -2.313≠ 0.021 S Range 2.39 – 5.34 2.26 – 16.35 Distensbility Median (IQR) 0.005 (0.004 – 0.007) 0.003 (0.002 – 0.005) -1.933≠ 0.053 NS Range 0.004 – 0.012 0.001 – 0.011 P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant •: Independent t-test; ≠: Mann-Whitney test Table ( 7 ): Other echocardiographic data among both subgroups: Affected vessels Test value* P-value Sig. No affected vessels Affected vessels No. = 8 No. = 37 Systolic LV function Normal 6 (75.0%) 27 (73.0%) 0.014 0.906 NS Impaired 2 (25.0%) 10 (27.0%) Diastolic LV function Normal 5 (62.5%) 12 (32.4%) 2.896 0.235 NS DD I 3 (37.5%) 21 (56.8%) DD II 0 (0.0%) 4 (10.8%) SWMA Negative 6 (75.0%) 21 (56.8%) 0.912 0.340 NS Positive 2 (25.0%) 16 (43.2%) P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant *: Chi-square test Table ( 8 ): Univariate analysis B S.E. Wald P-value Odds ratio (OR) 95% C.I. for OR Lower Upper Sex 2.108 1.119 3.552 0.059 8.235 0.919 73.789 DM 2.218 1.119 3.926 0.048 9.187 1.024 82.414 Aortic valve 2.955 0.948 9.724 0.002 19.200 2.997 122.995 Aortic root > 0 2.955 0.948 9.724 0.002 19.2 2.997 122.995 Final calcium score > 4 2.386 0.909 6.894 0.009 10.875 1.831 64.582 Arterial diameter change -0.929 0.403 5.310 0.021 0.395 0.179 0.870 Stiffness index 0.522 0.262 3.964 0.046 1.685 1.008 2.817 Table ( 9 ): Multi-variate analysis B S.E. Wald P-value Odds ratio (OR) 95% C.I. for OR Lower Upper DM 2.218 1.338 2.749 0.097 9.188 0.668 126.404 Aortic valve 1.473 1.21 1.483 0.223 4.361 0.407 46.68 Aortic root > 0 2.398 1.057 5.15 0.023 11.004 1.387 87.312 Final calcium score > 4 1.597 1.08 2.188 0.139 4.94 0.595 41.015 Arterial diameter change 0.152 1.086 0.019 0.889 1.164 0.138 9.779 Stiffness index 0.278 0.364 0.585 0.444 1.321 0.648 2.694 Table ( 10 ): Comparison between the four subgroups regarding age and sex No. of vessels affected groups Test value P-value Sig. No One vessel Two vessels >2 vessels No. = 8 No. = 10 No. = 6 No. = 21 Age Mean ± SD 49.00 ± 8.35 49.8 ± 8.56 52.17 ± 11.11 55.67 ± 6.33 2.025• 0.125 NS Range 37 – 60 35 – 63 41 – 65 39 – 64 Sex Female 7 (87.5%) 6 (60.0%) 2 (33.3%) 9 (42.9%) 5.821* 0.121 NS Male 1 (12.5%) 4 (40.0%) 4 (66.7%) 12 (57.1%) P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant *: Chi-square test; •: One Way ANOVA test Table ( 11 ): Comparison between the four subgroups regarding clinical risk factors History No. of vessels affected groups Test value P-value Sig. No One vessel Two vessels >2 vessels No. = 8 No. = 10 No. = 6 No. = 21 DM No 7 (87.5%) 6 (60.0%) 5 (83.3%) 5 (23.8%) 13.313 0.004 HS Yes 1 (12.5%) 4 (40.0%) 1 (16.7%) 16 (76.2%) HTN No 2 (25.0%) 5 (50.0%) 3 (50.0%) 6 (28.6%) 2.293 0.514 NS Yes 6 (75.0%) 5 (50.0%) 3 (50.0%) 15 (71.4%) Smoking No 8 (100.0%) 5 (50.0%) 2 (33.3%) 11 (52.4%) 9.492 0.148 NS Smoker 0 (0.0%) 3 (30.0%) 1 (16.7%) 5 (23.8%) Ex smoker 0 (0.0%) 2 (20.0%) 3 (50.0%) 5 (23.8%) Previous ischemic events No 6 (75.0%) 6 (60.0%) 5 (83.3%) 9 (42.9%) 4.516 0.211 NS Yes 2 (25.0%) 4 (40.0%) 1 (16.7%) 12 (57.1%) Family history No 7 (87.5%) 10 (100.0%) 5 (83.3%) 21 (100.0%) 4.775 0.189 NS Yes 1 (12.5%) 0 (0.0%) 1 (16.7%) 0 (0.0%) P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant *: Chi-square test Table ( 12 ): Showing the lipid profile among the four subgroups: Lipid profile No. of vessels affected groups Test value• P-value Sig. No One vessel Two vessels >2 vessels No. = 8 No. = 10 No. = 6 No. = 21 Total cholesterol Mean ± SD 165.50 ± 29.20 165.3 ± 21.62 154.33 ± 22.94 178.95 ± 28.61 1.656 0.191 NS Range 135 – 217 134 – 203 125 – 188 140 – 268 LDL Mean ± SD 100.50 ± 23.38 109.1 ± 10.69 98.67 ± 23.1 111.57 ± 28.72 0.701 0.557 NS Range 76 – 150 95 – 133 71 – 124 75 – 176 HDL Mean ± SD 43.38 ± 4.72 40.6 ± 8.33 42 ± 3.58 40.33 ± 7.66 0.413 0.744 NS Range 35 – 50 32 – 61 35 – 45 30 – 61 TGS Mean ± SD 124.38 ± 30.62 152.5 ± 34.28 122.33 ± 45.89 177 ± 76.96 2.257 0.096 NS Range 98 – 187 110 – 230 60 – 175 70 – 334 P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant •: One Way ANOVA test Table ( 13 ): The calcium score among the four subgroups Calcium score No. of vessels affected groups Test value≠ P-value Sig. No One vessel Tow vessels >2 vessels No. = 8 No. = 10 No. = 6 No. = 21 Aortic valve Median (IQR) 1 (1 – 1) 1 (1 – 1) 1 (1 – 1) 1 (1 – 2) 6.839 0.077 NS Range 0 – 1 1 – 2 1 – 2 0 – 3 Mitral annulus Median (IQR) 2 (2 – 3) 2 (2 – 3) 2.5 (2 – 3) 2 (2 – 3) 0.055 0.997 NS Range 2 – 3 1 – 3 1 – 3 1 – 3 Aortic root Median (IQR) 0 (0 – 0.5) 1 (1 – 1) 1 (1 – 1) 1 (1 – 1) 13.597 0.004 HS Range 0 – 1 0 – 1 0 – 1 0 – 1 Papillary muscle Median (IQR) 0 (0 – 1) 1 (1 – 1) 0 (0 – 1) 1 (1 – 1) 7.226 0.065 NS Range 0 – 1 0 – 1 0 – 1 0 – 1 Final score Median (IQR) 4 (3 – 4.5) 5 (5 – 6) 5 (4 – 5) 6 (5 – 6) 9.192 0.027 S Range 2 – 6 3 – 6 3 – 6 2 – 7 P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant ≠: Kruskal-Wallis test Table ( 14 ): Showing the Aortic stiffness among the four-subgroups Aortic stiffness No. of vessels affected groups Test value P-value Sig. No One vessel Tow vessels >2 vessels No. = 8 No. = 10 No. = 6 No. = 21 Arterial diameter change Mean ± SD 3.63 ± 1.06 3 ± 1.49 1.83 ± 0.75 2.15 ± 1.04 4.562• 0.008 HS Range 3 – 6 1 – 5 1 – 3 1 – 4 Strain Mean ± SD 0.14 ± 0.05 0.11 ± 0.05 0.07 ± 0.05 0.08 ± 0.04 4.634• 0.007 HS Range 0.09 – 0.24 0.03 – 0.16 0.03 – 0.16 0.03 – 0.17 Elastic modulus Median (IQR) 387.5 (276.67 – 473.33) 380.83 (270 – 870) 825 (620 – 1080) 787.5 (373.33 – 1200) 6.301≠ 0.098 NS Range 166.67 – 550 202.5 – 1300 190 – 1200 180 – 1920 Stiffness index Median (IQR) 3.74 (2.88 – 4.14) 3.52 (3.19 – 10.14) 7.92 (6.72 – 10.95) 7.57 (5.12 – 11.66) 9.131≠ 0.028 S Range 2.39 – 5.34 2.74 – 11.49 2.26 – 13.56 2.59 – 16.35 Distensbility Median (IQR) 0.005 (0.004 – 0.007) 0.005 (0.002 – 0.007) 0.002 (0.002 – 0.003) 0.003 (0.002 – 0.005) 6.301≠ 0.098 NS Range 0.004 – 0.012 0.002 – 0.01 0.002 – 0.011 0.001 – 0.011 P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant •: One Way ANOVA test; ≠: Kruskal-Wallis test Table ( 15 ): showing the echocardiographic data among the four subgroups No. of vessels affected groups Test value* P-value Sig. No One vessel Tow vessels >2 vessels No. = 8 No. = 10 No. = 6 No. = 21 Systolic LV function Normal 6 (75.0%) 8 (80.0%) 6 (100.0%) 13 (61.9%) 3.823 0.281 NS Impaired 2 (25.0%) 2 (20.0%) 0 (0.0%) 8 (38.1%) Diastolic LV function Normal 5 (62.5%) 5 (50.0%) 2 (33.3%) 5 (23.8%) 8.031 0.236 NS DD I 3 (37.5%) 5 (50.0%) 4 (66.7%) 12 (57.1%) DD II 0 (0.0%) 0 (0.0%) 0 (0.0%) 4 (19.0%) SWMA Negative 6 (75.0%) 6 (60.0%) 5 (83.3%) 10 (47.6%) 3.452 0.327 NS Positive 2 (25.0%) 4 (40.0%) 1 (16.7%) 11 (52.4%) P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant *: Chi-square test Table ( 16 ): Table comparing between the three subgroups regarding age and sex Coronary angiography syntax score groups Test value P-value Sig. Low Intermediate High No. = 23 No. = 9 No. = 13 Age Mean ± SD 52.52 ± 8.36 51.56 ± 8.38 53.85 ± 8.24 0.213• 0.809 NS Range 37 – 65 35 – 61 39 – 63 Sex Female 14 (60.9%) 1 (11.1%) 9 (69.2%) 8.291* 0.016 S Male 9 (39.1%) 8 (88.9%) 4 (30.8%) P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant *: Chi-square test; •: One Way ANOVA test; ≠: Kruskal-Wallis test Table ( 17 ): Table comparing between the three subgroups regarding clinical risk factors History Coronary angiography syntax score groups Test value* P-value Sig. Low Intermediate High No. = 23 No. = 9 No. = 13 DM No 18 (78.3%) 3 (33.3%) 2 (15.4%) 14.564 0.001 HS Yes 5 (21.7%) 6 (66.7%) 11 (84.6%) HTN No 10 (43.5%) 3 (33.3%) 3 (23.1%) 1.533 0.465 NS Yes 13 (56.5%) 6 (66.7%) 10 (76.9%) Smoking No 15 (65.2%) 2 (22.2%) 9 (69.2%) 6.016 0.198 NS Smoker 4 (17.4%) 3 (33.3%) 2 (15.4%) Ex smoker 4 (17.4%) 4 (44.4%) 2 (15.4%) Previous ischemic events No 16 (69.6%) 5 (55.6%) 5 (38.5%) 3.317 0.190 NS Yes 7 (30.4%) 4 (44.4%) 8 (61.5%) Family history No 21 (91.3%) 9 (100.0%) 13 (100.0%) 2.002 0.368 NS Yes 2 (8.7%) 0 (0.0%) 0 (0.0%) P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant *: Chi-square test Table ( 18 ): Lipid profile of the study population compared in the three sub-groups Lipid profile Coronary angiography syntax score groups Test value• P-value Sig. Low Intermediate High No. = 23 No. = 9 No. = 13 Total cholesterol Mean ± SD 164.04 ± 23.49 167.44 ± 21.48 183.15 ± 33.86 2.215 0.122 NS Range 125 – 217 134 – 195 147 – 268 LDL Mean ± SD 102.39 ± 17.12 108.22 ± 18.55 115.46 ± 34.91 1.258 0.295 NS Range 71 – 150 75 – 133 76 – 176 HDL Mean ± SD 42.17 ± 6.23 40.89 ± 5.46 39.54 ± 8.79 0.608 0.549 NS Range 32 – 61 33 – 51 30 – 61 TGS Mean ± SD 128.17 ± 29.12 160 ± 46.23 198.69 ± 87.99 6.789 0.003 HS Range 60 – 187 70 – 230 76 – 334 P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant •: One Way ANOVA test Table ( 19 ): Comparison between echo calcium score and syntax score subgroups: Calcium score Coronary angiography syntax score groups Test value≠ P-value Sig. Low Intermediate High No. = 23 No. = 9 No. = 13 Aortic valve Median (IQR) 1 (1 – 1) 1 (1 – 2) 1 (1 – 2) 5.539 0.063 NS Range 0 – 2 1 – 3 0 – 2 Mitral annulus Median (IQR) 2 (2 – 3) 3 (2 – 3) 2 (2 – 3) 1.105 0.575 NS Range 1 – 3 2 – 3 1 – 3 Aortic root Median (IQR) 1 (0 – 1) 1 (1 – 1) 1 (1 – 1) 5.405 0.067 NS Range 0 – 1 0 – 1 0 – 1 Papillary muscle Median (IQR) 1 (0 – 1) 1 (1 – 1) 1 (1 – 1) 3.024 0.220 NS Range 0 – 1 0 – 1 0 – 1 Final score Median (IQR) 5 (3 – 5) 6 (5 – 6) 6 (5 – 6) 8.676 0.013 S Range 2 – 6 5 – 7 2 – 7 P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant ≠: Kruskal-Wallis test Table ( 20 ): Comparison between Aortic stiffness and syntax score subgroups: Aortic stiffness Coronary angiography syntax score groups Test value P-value Sig. Low Intermediate High No. = 23 No. = 9 No. = 13 Arterial diameter change Mean ± SD 2.91 ± 1.24 2.44 ± 1.42 2 ± 1.04 2.229• 0.121 NS Range 1 – 6 1 – 5 1 – 4 Strain Mean ± SD 0.11 ± 0.05 0.08 ± 0.05 0.07 ± 0.0 2.641• 0.083 NS Range 0.03 – 0.24 0.03 – 0.17 0.03 – 0.14 Elastic modulus Median (IQR) 433.33 (293.33 – 870) 900 (320 – 1080) 697.5 (389.17 – 1200) 2.374≠ 0.305 NS Range 166.67 – 1300 256 – 1350 180 – 1920 Stiffness index Median (IQR) 4.05 (3.19 – 7.92) 7.87 (3.8 – 9.63) 7 (5.12 – 13.54) 3.919≠ 0.141 NS Range 2.26 – 13.56 2.65 – 14.46 2.59 – 16.35 Distensbility Median (IQR) 0.005 (0.002 – 0.007) 0.002 (0.002 – 0.006) 0.003 (0.002 – 0.005) 2.374≠ 0.305 NS Range 0.002 – 0.012 0.002 – 0.008 0.001 – 0.011 P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant •: One Way ANOVA test; ≠: Kruskal-Wallis test Table ( 21 ): Correlation between other echocardiographic data and syntax score subgroups: Coronary angiography syntax score groups Test value* P-value Sig. Low Intermediate High No. = 23 No. = 9 No. = 13 Systolic LV function Normal 19 (82.6%) 5 (55.6%) 9 (69.2%) 2.578 0.276 NS Impaired 4 (17.4%) 4 (44.4%) 4 (30.8%) Diastolic LV function Normal 11 (47.8%) 2 (22.2%) 4 (30.8%) 2.992 0.559 NS DD I 11 (47.8%) 6 (66.7%) 7 (53.8%) DD II 1 (4.3%) 1 (11.1%) 2 (15.4%) SWMA Negative 17 (73.9%) 2 (22.2%) 8 (61.5%) 7.220 0.027 S Positive 6 (26.1%) 7 (77.8%) 5 (38.5%) P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant *: Chi-square test Table ( 22 ): Correlation between final Calcium score and Lipid profile & Aortic distensibility & angiographic data (syntax score and number of vessels affected) Final calcium score r P-value Arterial diameter change -0.377* 0.012 Strain -0.363* 0.015 Elastic modulus 0.417** 0.005 Stiffness index 0.397** 0.008 Distensbility -0.417** 0.005 Coronary angiography syntax score groups 0.338* 0.041 Syntax score numerical value 0.4677** 0.001 No. of vessels affected 0.428** 0.003 P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant Spearman correlation coefficient Table ( 23 ): Correlation between syntax score numerical value and total Calcium score & Aortic stiffness variables: Syntax score Numerical value r P-value Total calcium score **0.4677 0.001 Arterial diameter change **-0.4437 0.002 Strain **-0.4521 0.001 Elastic modulus 0.281 0.061 Stiffness index *0.349 0.018 Distensbility *-0.376 0.0107 P-value > 0.05: Non significant; P-value < 0.05: Significant; P-value < 0.01: Highly significant Spearman correlation coefficient Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3912043","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":270179390,"identity":"d76b25f3-c204-402c-a30b-7c7742856f52","order_by":0,"name":"Asmaa Ahmed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIiWNgGAWjYBACNgglAUYMPBU1ciDugQd4tPCjajlzzBisJQGPFskGGAukhbeNOREsgE+LwfnTiR9+MFgw8M/uTnzwto0tfX7Y4YdAW+zkdBtwaLmRu1myB2iFxJ2zmw3nnJPJ3Xg7zQCoJdnY7AAuLbwbJHhArrqRu02ap4wtd+PsBJCWA4nbcGixP392888/QC3yN3K3/+ZhY043nJ3+Aa8WgwMgw4FagC7cxszTxpwgL52D3xaQSmsZAwkeQ5Cn5pw5ZrhBOqfgQIIBHr8AHXbzTUWdnNyN3I0f3lTUyMvPTt/84UOFnRwuLVCNDDxIToWIkADkG0hRPQpGwSgYBSMBAADdfGLReNqU8AAAAABJRU5ErkJggg==","orcid":"","institution":"Rochester General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Asmaa","middleName":"","lastName":"Ahmed","suffix":""},{"id":270179391,"identity":"c50afbca-ee03-420f-ad7f-1e4f56201027","order_by":1,"name":"Alaa Roshdy","email":"","orcid":"","institution":"Ainshams University","correspondingAuthor":false,"prefix":"","firstName":"Alaa","middleName":"","lastName":"Roshdy","suffix":""},{"id":270179392,"identity":"d9b65e8c-beaf-4602-b65f-6f0211ff81a9","order_by":2,"name":"Adham Abdeltawab","email":"","orcid":"","institution":"Ainshams University","correspondingAuthor":false,"prefix":"","firstName":"Adham","middleName":"","lastName":"Abdeltawab","suffix":""}],"badges":[],"createdAt":"2024-01-31 00:29:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3912043/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3912043/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50512329,"identity":"ad2ae057-dfb1-4b92-ad77-db7a5a8aaf9d","added_by":"auto","created_at":"2024-02-01 16:19:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":268037,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAortic root and papillary muscle calcification\u003cbr\u003e\n \u003c/strong\u003eExample from our study, patient number 41;there was positive calcification in both papillary muscle and aortic root that added +2 inhis calcium score. this patient total calcium score was 5\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/652de6c0ea26a70764134097.png"},{"id":50513489,"identity":"0c3ab0c4-bca8-4514-8980-7a397957cb62","added_by":"auto","created_at":"2024-02-01 16:27:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":200082,"visible":true,"origin":"","legend":"\u003cp\u003eMitral annular calcification\u003c/p\u003e\n\u003cp\u003eExample from our study, patient number 37. Thickness of posterior leaflet of MV was 1.1cmso mitral annular calcification was 3. Total calcium score for this patient was 4\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/7e1ac2a6204cb8c442a1a4ac.png"},{"id":50513487,"identity":"e3777c57-4663-40c9-a57a-43b882c853a5","added_by":"auto","created_at":"2024-02-01 16:27:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":215861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAortic valve calcification\u003c/strong\u003e Example from our study, patient number 41. Thickness of aortic cusp was 3mm so AVC was 1. This [patient final calcium score was 5\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/dbb76537b7840287a5564023.png"},{"id":50512336,"identity":"b6c3e71d-e4cf-4a6f-a56d-93eecbc8a908","added_by":"auto","created_at":"2024-02-01 16:19:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":564740,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eArterial diameter change \u003c/strong\u003eExample from our study: Patient number 40. Arterial diameter change was 1 with final distensibility of 0.0022\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/f609530f3d340aad854b9573.png"},{"id":50512327,"identity":"1cbbd736-11db-474c-ae2a-23f180051c45","added_by":"auto","created_at":"2024-02-01 16:19:40","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":12714,"visible":true,"origin":"","legend":"\u003cp\u003eColumn graph comparing the two subgroups regarding sex\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/5062252e9686dbe622633c06.png"},{"id":50514495,"identity":"b92aeefe-fe03-497a-a2dc-04154a9fe3bc","added_by":"auto","created_at":"2024-02-01 16:35:40","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":12612,"visible":true,"origin":"","legend":"\u003cp\u003eColumn graph comparing the two subgroups regarding DM\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/fb0fae468244757eddf86208.png"},{"id":50513486,"identity":"7856f11f-5187-4e70-ba98-2903475a914d","added_by":"auto","created_at":"2024-02-01 16:27:40","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":13129,"visible":true,"origin":"","legend":"\u003cp\u003eColumn graph comparing the two subgroups regarding smoking\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/8713c6ac09f6be5a93ae9f5d.png"},{"id":50512332,"identity":"71ebe8d2-22b6-4f05-ab48-a69d106df29c","added_by":"auto","created_at":"2024-02-01 16:19:40","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":13802,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot comparing the two subgroups regarding Aortic valve calcification.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/7c092de9bced2bbcb949109d.png"},{"id":50512357,"identity":"5f0ace11-b225-4f4b-b475-240df75ba138","added_by":"auto","created_at":"2024-02-01 16:19:41","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":13240,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot comparing the two subgroups regarding Aortic root calcification\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/6b10f7718ae38d3939e15f8c.png"},{"id":50515305,"identity":"4c3ac360-3044-4d78-a42d-d557e7454d53","added_by":"auto","created_at":"2024-02-01 16:43:40","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":14678,"visible":true,"origin":"","legend":"\u003cp\u003eBox blot comparing the two subgroups regarding final calcium score\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/014199cd30d29fdf0f8588a9.png"},{"id":50512334,"identity":"4edfad20-fe0a-41bb-9142-ff26163fbde6","added_by":"auto","created_at":"2024-02-01 16:19:40","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":12993,"visible":true,"origin":"","legend":"\u003cp\u003eGraph comparing the two subgroups regarding arterial diameter change\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/06ace5f2426dbb4078df6996.png"},{"id":50513490,"identity":"a24c1d5a-57b0-477e-82b7-7fa5a164752a","added_by":"auto","created_at":"2024-02-01 16:27:40","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":12240,"visible":true,"origin":"","legend":"\u003cp\u003eGraph comparing the two subgroups regarding strain\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/287940ba851cbe3153b6df56.png"},{"id":50514498,"identity":"513b6a09-40e4-4537-a26e-92fc467d2d06","added_by":"auto","created_at":"2024-02-01 16:35:40","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":14198,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot comparing between the two subgroups regarding stiffness index\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/5c57eb5f24362146b4f08e68.png"},{"id":50513495,"identity":"d7795903-179b-45fa-8f54-230876249f4f","added_by":"auto","created_at":"2024-02-01 16:27:40","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":16956,"visible":true,"origin":"","legend":"\u003cp\u003eShowing the presence of DM among the four subgroups:\u003c/p\u003e","description":"","filename":"14.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/383febe27e593ae07486f52b.png"},{"id":50512343,"identity":"6b0b89f6-4136-4e76-bc05-f7a05fa475ab","added_by":"auto","created_at":"2024-02-01 16:19:40","extension":"png","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":15158,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot comparing the 4 subgroups regarding aortic root calcification\u003c/p\u003e","description":"","filename":"15.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/c457e2af597b4b8325f58ee5.png"},{"id":50514500,"identity":"7530c0fc-00f9-4a3b-ad11-f3a475722c11","added_by":"auto","created_at":"2024-02-01 16:35:40","extension":"png","order_by":16,"title":"Figure 16","display":"","copyAsset":false,"role":"figure","size":19503,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot comparing the 4 subgroups regarding final calcium score\u003c/p\u003e","description":"","filename":"16.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/e5bec0f46218ca4f39f4fd21.png"},{"id":50514496,"identity":"304a9810-f7c7-4d67-91b3-2e994db5aa0a","added_by":"auto","created_at":"2024-02-01 16:35:40","extension":"png","order_by":17,"title":"Figure 17","display":"","copyAsset":false,"role":"figure","size":13743,"visible":true,"origin":"","legend":"\u003cp\u003eColumn graph comparing between the four subgroups regarding arterial diameter change\u003c/p\u003e","description":"","filename":"17.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/8acf1bd0097ac04c110f6b24.png"},{"id":50513493,"identity":"2051dbd4-3c5e-4a57-a46f-5f830c3088ac","added_by":"auto","created_at":"2024-02-01 16:27:40","extension":"png","order_by":18,"title":"Figure 18","display":"","copyAsset":false,"role":"figure","size":12904,"visible":true,"origin":"","legend":"\u003cp\u003eColumn graph comparing between the four subgroups regarding strain\u003c/p\u003e","description":"","filename":"18.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/40adb0cb7d30f44776f595b5.png"},{"id":50515306,"identity":"89d5b42c-9b1e-4e2a-a7ee-4e912f54d976","added_by":"auto","created_at":"2024-02-01 16:43:40","extension":"png","order_by":19,"title":"Figure 19","display":"","copyAsset":false,"role":"figure","size":18881,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot comparing between the four subgroups regarding stiffness index\u003c/p\u003e","description":"","filename":"19.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/712d953700e47e001885482c.png"},{"id":50512339,"identity":"9e0959e3-93d0-4d13-bf0e-01da6df14a6e","added_by":"auto","created_at":"2024-02-01 16:19:40","extension":"png","order_by":20,"title":"Figure 20","display":"","copyAsset":false,"role":"figure","size":13139,"visible":true,"origin":"","legend":"\u003cp\u003eAge distribution among the three sub-groups.\u003c/p\u003e","description":"","filename":"20.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/7b17871a9a8003fbebe1ef26.png"},{"id":50512340,"identity":"80c49874-8000-4891-9786-55bfb7518abb","added_by":"auto","created_at":"2024-02-01 16:19:40","extension":"png","order_by":21,"title":"Figure 21","display":"","copyAsset":false,"role":"figure","size":15963,"visible":true,"origin":"","legend":"\u003cp\u003eSex distribution among the three sub-groups.\u003c/p\u003e","description":"","filename":"21.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/e6e7476a2d083b8d48bf3d37.png"},{"id":50513498,"identity":"0e00c34f-6813-4954-95f1-2492b45a558d","added_by":"auto","created_at":"2024-02-01 16:27:40","extension":"png","order_by":22,"title":"Figure 22","display":"","copyAsset":false,"role":"figure","size":15824,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of diabetics and non-diabetics among the three sub-groups.\u003c/p\u003e","description":"","filename":"22.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/7907bc8bcfd0786e15815bb7.png"},{"id":50512350,"identity":"91006959-244f-4820-a71c-6a359c52c487","added_by":"auto","created_at":"2024-02-01 16:19:41","extension":"png","order_by":23,"title":"Figure 23","display":"","copyAsset":false,"role":"figure","size":19272,"visible":true,"origin":"","legend":"\u003cp\u003eLipid profile results in the three subgroups\u003c/p\u003e","description":"","filename":"23.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/0879e1049a50948a2ae6951c.png"},{"id":50512347,"identity":"72446878-c5c4-4bfc-ac68-b96287ddf42f","added_by":"auto","created_at":"2024-02-01 16:19:40","extension":"png","order_by":24,"title":"Figure 24","display":"","copyAsset":false,"role":"figure","size":18281,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot comparison between echo calcium score and syntax score\u003c/p\u003e","description":"","filename":"24.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/c9c291d52f2541004055269b.png"},{"id":50512353,"identity":"62870013-bbb2-4f1e-b4e5-3f68236edfaf","added_by":"auto","created_at":"2024-02-01 16:19:41","extension":"png","order_by":25,"title":"Figure 25","display":"","copyAsset":false,"role":"figure","size":16090,"visible":true,"origin":"","legend":"\u003cp\u003eColumn graph comparing the three syntax score subgroups regarding SWMA\u003c/p\u003e","description":"","filename":"25.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/f005881d30861c610b2bffb7.png"},{"id":50513500,"identity":"af5e2723-b8ab-41d8-8b6b-83b36e6c02a6","added_by":"auto","created_at":"2024-02-01 16:27:41","extension":"png","order_by":26,"title":"Figure 26","display":"","copyAsset":false,"role":"figure","size":26235,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between final calcium score and aortic distensibility:\u003c/p\u003e","description":"","filename":"26.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/b6e888fb8305b42423bc319a.png"},{"id":50512351,"identity":"3b73302d-2778-47b2-a641-7520c6fee498","added_by":"auto","created_at":"2024-02-01 16:19:41","extension":"png","order_by":27,"title":"Figure 27","display":"","copyAsset":false,"role":"figure","size":25873,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between final calcium score and syntax score subgroups:\u003c/p\u003e","description":"","filename":"27.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/114e425779dc556a2937bfcd.png"},{"id":50514501,"identity":"8c2d3889-dee2-4ee2-b8d5-7b1098174467","added_by":"auto","created_at":"2024-02-01 16:35:40","extension":"png","order_by":28,"title":"Figure 28","display":"","copyAsset":false,"role":"figure","size":23431,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between final calcium score and number of coronaries affected:\u003c/p\u003e","description":"","filename":"28.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/8cbdeaa0b9782be4fd735640.png"},{"id":50512355,"identity":"c2d07fa8-a63f-43f4-b587-239ba394bec7","added_by":"auto","created_at":"2024-02-01 16:19:41","extension":"png","order_by":29,"title":"Figure 29","display":"","copyAsset":false,"role":"figure","size":29825,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating curves (ROC) of final calcium score in predicting CAD\u003c/p\u003e","description":"","filename":"29.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/e22ec0270f7c92fd3a362520.png"},{"id":50512356,"identity":"14345c6c-76b5-4517-9937-3d388ddc3c37","added_by":"auto","created_at":"2024-02-01 16:19:41","extension":"png","order_by":30,"title":"Figure 30","display":"","copyAsset":false,"role":"figure","size":21384,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating curves (ROC) of stiffness index in predicting CAD\u003c/p\u003e","description":"","filename":"30.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/ff578a1a04e74079fd464bad.png"},{"id":50512354,"identity":"37b371a3-e75a-4777-83c3-41f2c4b5cedb","added_by":"auto","created_at":"2024-02-01 16:19:41","extension":"png","order_by":31,"title":"Figure 31","display":"","copyAsset":false,"role":"figure","size":23904,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating curves (ROC) of elastic modulus in predicting CAD\u003c/p\u003e","description":"","filename":"31.png","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/6cc82d46c6c29f74039231f8.png"},{"id":61795150,"identity":"3e7cead7-1987-443d-910e-64958fdc63ea","added_by":"auto","created_at":"2024-08-05 16:19:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3557240,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3912043/v1/33f4d7ae-f557-4f30-812e-2f590ba788a7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Echocardiography Calcium Score And Aortic Stiffness As Predictive Tools Of Severity Of Coronary Artery Disease. A Single Center Egyptian Experience","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCardiovascular diseases are the leading cause of death worldwide causing about 45.0\u0026nbsp;million adult deaths worldwide in 2002.Half of such deaths are caused by coronary artery disease (CAD). \u003csup\u003e1, 2\u003c/sup\u003e According to the World Health Organization (WHO), CAD cause 16.7\u0026nbsp;million deaths in the world each year. \u003csup\u003e3\u003c/sup\u003e Invasive conventional coronary angiography (CCA) is the gold standard technique for diagnosis and selection of best treatment for CAD. \u003csup\u003e4, 5\u003c/sup\u003e SYNTAX score (SS) is one of the scoring systems used for assessment of CAD severity and complexity. SS incorporates morphological features of lesions such as total occlusion, bifurcation, length and localizations of lesions based on the myocardial area at risk.\u003csup\u003e5\u003c/sup\u003e Characterization of coronary-artery calcification by computed tomography known as Coronary artery calcium score (CACS) is proven to be related to angiographically significant lesions. It's used as simple and readily available test for identifying coronary artery disease (CAD) in asymptomatic patients to predict the risk of CAD incidence apart from routine total risk scores. \u003csup\u003e6,7\u003c/sup\u003e The detection of cardiac calcification by echocardiography (non- coronary artery calcification ) has also been shown to be associated with atherosclerosis, severe coronary artery calcification. It may be of value in the evaluation of patients suspected of having CAD.\u003csup\u003e8\u0026ndash;11\u003c/sup\u003e Using a large echocardiographic database, Mitral annular calcification (MAC) was found to be independently associated with incident CVD, cardiovascular death, and all-cause death. It can be considered as an overall marker of atherosclerotic burden. This finding confirms the importance of an abnormal mitral annulus as an important prognostic marker.\u003csup\u003e12, 13\u003c/sup\u003e In this study we detected the role of echocardiography calcium score as predictive tool of severity of coronary artery disease in correlation with the patients' coronary angiography and lipid profile.\u003c/p\u003e"},{"header":"PATIENTS AND METHODS","content":"\u003cp\u003eThis study included 45 patients coming Ain Shams University Hospitals to do elective coronary angiography in the period between November 2018 and August 2019. Patients were subjected to history taking, examination, blood samples and echocardiographic examination. The echocardiographic calcium score was correlated with syntax score of their coronary angiography films. Also syntax score was divided into three groups; low risk\u0026thinsp;\u0026le;\u0026thinsp;18, intermediate risk 18\u0026ndash;27 and high risk groups\u0026thinsp;\u0026gt;\u0026thinsp;27. The study protocol was approved by Ain Shams university faculty of medicine ethical committee.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExclusion criteria\u003c/h2\u003e \u003cp\u003ePatients not meeting the above inclusion criteria, Age less than 18 and more than 65, Poor patient echogenicity, patients with renal failure or on hemodialysis, patients presenting with ACS or cardiogenic shock, significant valvular heart disease, Aortic aneurysm, patients with AF or frequent premature beats.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMethods:\u003c/h3\u003e\n\u003cp\u003eAll patients were subjected to the following:\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1. History taking with particular stress on:\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eA- Renal impairment.\u003c/p\u003e \u003cp\u003eB- Any valvular heart disease.\u003c/p\u003e \u003cp\u003eC- Previous ischemic events and evidence of revascularization either by stenting or by surgery.\u003c/p\u003e \u003cp\u003eD- Any aortic disease or aortic aneurysm.\u003c/p\u003e \u003cp\u003eE- Family history of CAD\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\u003ch2\u003e2. Clinical examination with particular stress on:\u003c/h2\u003e\u003cp\u003e\u003col style=\"list-style-type:lower-alpha;\"\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eBlood pressure as well as heart rate and rhythm.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eGeneral signs of severe valvular lesions.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eLocal cardiac examination for additional sounds or murmurs indicating severe valvular affection.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eSigns of dyslipidemia.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003ch2\u003e3. Blood samples were taken for lipid profile.\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e4. Standard trans-thoracic two-dimensional echocardiographic examinations:\u003c/h2\u003e \u003cp\u003eAll patients were studied in the left lateral decubitus position by an expert cardiologist using an ultrasound system (General Electric Vivid Seven) using an S3 transducer. Standard 2D and M-mode echocardiograms were obtained in the apical four-chamber, apical two-chamber, apical long axis and left parasternal views according to the American society of echocardiography and the European Association of Echocardiography guidelines. 65 in order to calculate :\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003cp\u003e\u003cu\u003eA-Echo calcium score: Table 1, Figure 1-3\u003cbr\u003e\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e1-AVC was defined as focal areas of increased echogenicity and thickening of the aortic valve leaflets in the absence of aortic stenosis (velocity across the valve \u0026lt;2.5 m/sec). Each aortic valve leaflet was graded on a scale of 0 (normal) to 3 (severe) according to leaflet thickening and calcific deposits; the highest score for a given cusp will be assigned as the overall degree of aortic valve sclerosis. \u003csup\u003e10\u003c/sup\u003e\u003cbr\u003e\u0026nbsp;\u003cbr\u003e2- MAC was defined as an intense and bright echo-producing structure located at the junction of the atrio-ventricular groove and posterior mitral valve leaflet and will be measured from the leading anterior to the trailing posterior edge and judged on a scale of 0 (normal) to 3 (severe). \u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e3- Papillary muscle calcium was defined as a bright echo involving the head of 1 or both papillary muscles. \u003csup\u003e10\u0026nbsp;\u003c/sup\u003e\u003cbr\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cbr\u003e4- Aortic root calcium was defined as a focal or diffuse area of increased echo reflectance and thickening in the aortic root on the parasternal long-axis view. \u003csup\u003e10\u003c/sup\u003e\u003cbr\u003e\u0026nbsp;\u0026nbsp;\u003cbr\u003e5- A final score was derived as the sum of all identified cardiac calcific deposits and was in the range of 0 (no calcium visible) to 8 (extensive cardiac and aortic root calcific deposits). \u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e\u003cbr\u003e\u0026nbsp;\u003c/u\u003e\u003cu\u003eB- Aortic stiffness: figure 4\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate aortic stiffness, aortic diameters was measured by M-mode tracing of the ascending aorta at the level of 3-4 cms above the aortic valve from the parasternal long axis view in systole and diastole. After the acquisition of the 2 prerequisite parameters, several useful indices of local arterial stiffness were calculated after systolic and diastolic blood pressure that was measured manullay and the following formula;\u003c/p\u003e\n\u003cp\u003e1) Arterial diameter change (mm) = SD-DD\u003c/p\u003e\n\u003cp\u003e2) Arterial strain = (SD-DD)/DD\u003c/p\u003e\n\u003cp\u003e3) Elastic modulus E (p) = (SBP-DBP)/strain\u003c/p\u003e\n\u003cp\u003e4) Arterial stiffness index \u0026beta;=Ln (SBP/DBP)/strain\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e5) Arterial distensibility = (2\u0026times;strain) /(SBP-DBP).\u003c/p\u003e\n\u003cp\u003eSD: systolic diameter, DD: diastolic diameter, SBP: systolic blood pressure, DBP: diastolic blood pressure, Ln: natural logarithm.14\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u0026nbsp;5. Cardiac catheterization:\u003c/p\u003e\n\u003cp\u003e-Coronary angiography was performed by a team of expert interventional cardiologists. A detailed analysis of angiographic images was done by the operators.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e-Significant lesion was defined as a 70% or greater stenosis in the luminal diameter of any major epicardial coronary artery and 50% or greater in left main coronary artery.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e-The presence of significant lesions is determined based on visual estimation. Basal angiographic characteristics of patients such as diseased vessel, left main coronary artery (LM), left anterior descending (LAD) coronary artery; right coronary artery (RCA), circumflex coronary artery (LCX), and diseased vessel number are recorded.\u003c/p\u003e\n\u003cp\u003e-Syntax Score was calculated using dedicated software (version 2.11, www.syntaxscore.com), the acceptable core-lab reproducibility of SYNTAX score that has been reported which integrates two components:15\u0026nbsp;\u003cbr\u003e\u0026nbsp;(a) morphological features of each lesion such as dominance, chronic total occlusion (CTO), bifurcation, trifurcation, tortuosity, heavy calcification, lesion length, presence of thrombus, aorto-ostial and diffuse lesions.\u0026nbsp;\u003cbr\u003e\u0026nbsp;(b) weighting factors of lesions based on myocardial area distal to lesion. Lesions with \u0026ge; 50% luminal obstruction in vessels with a diameter \u0026ge;1.5 mm are added to provide SS.\u003c/p\u003e\n\u003cp\u003e- All morphological features of each lesion included in SS were recorded.\u0026nbsp;\u003cbr\u003e\u0026nbsp;-The SS was divided into three tertiles as follows: low\u0026le; 18, intermediate risk 18-27 and high risk groups \u0026gt;27. 16\u003c/p\u003e\n\u003cp\u003e-All angiograms were scored by experienced interventional cardiologist who was blinded to echocardiography calcium score and aortic stiffness measurement data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Analysis of data was done using statistical program for social science (SPSS) version 16 as follows: Quantitative variables were described as mean, standard deviation (SD) and range. Qualitative variables were described as number and percentage. Unpaired t-test was used to compare quantitative variables, in parametric data (SD \u0026lt; 50% mean).Comparison between groups as regards qualitative variables was done by using chi-square test. Fisher exact test was used instead of chi-square when one expected cell is less than 5.One way ANOVA (analysis of variance) test was used to compare more than two groups as regard quantitative variable. Spearman correlation co-efficient test was used to rank variables versus each other positively or inversely. Receiver operator characteristic (ROC) curve was used to find out the best cut-off value, and validity of certain variable. P value \u0026gt; 0.05 was non-significant (NS), P \u0026lt; 0.05 was significant (S), and P \u0026lt; 0.001 was highly significant (HS).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eOur study included 45 patients who did elective coronary angiography in Ain Shams university hospitals. All patients were assessed clinically followed by 2D echocardiographic assessment to calculate non-coronary calcium score. Coronary angiography films were used to calculate syntax score that was divided into three groups; low risk \u0026le; 18, intermediate risk 18-27 and high risk groups \u0026gt;27. Also number of vessels affected was recorded.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e1-Demographic and clinical data of the study population:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe study included 45 patients; 21 of which were males representing 46.6% of the participants. The mean age of the whole group was 52.7 \u0026plusmn; 8.18. 48.8% (22/45) of the participants were diabetic while 64.4% (29/45) were hypertensive. 42.2% (19/45) had previous ischemic history and 4.4% (2/45) had positive family history of CAD. As regards smoking; 9 (20%) patients were smokers, 10 (22.2%) patients were ex-smokers and 26 (57.7%) patients were non- smokers.\u003c/p\u003e\n\u003cp\u003e2- \u003cu\u003eLab, echo and angio data:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eLipid profile of the study population\u003c/p\u003e\n\u003cp\u003eThe mean total cholesterol level among the whole study group was 170.24\u0026plusmn;27.26, the mean LDL level was 107.33\u0026plusmn;23.95 , the mean HDL level was 41.15\u0026plusmn;6.87 and finally the mean TGA level was 154.91\u0026plusmn;62.2.\u003c/p\u003e\n\u003cp\u003eEchocardiographic data of the study group:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eCalcium score:\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe mean final calcium score of the whole study group was 4.95\u0026plusmn;1.29, the breakdown of this calcium score was as follows:\u003cbr\u003emean Aortic calcium score was 1.22\u0026plusmn;0.559, mean mitral annular calcium score was 2.33\u0026plusmn; 0.674 , mean papillary muscles calcium score was 0.644\u0026plusmn;0.48,and finally mean aortic root calcium score was 0.755\u0026plusmn;0.43\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eAortic stiffness:\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eMean arterial diameter change was 2.48 \u0026plusmn; 1.3, mean strain was 0.092 \u0026plusmn; 0.051, mean elastic modulus was 633 \u0026plusmn; 351.3, mean stiffness index was 7.57 \u0026plusmn; 4.74 and mean Aortic distensibility was 0.0044\u0026plusmn;0.0029.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eLV systolic \u0026amp; diastolic function and SWMA:\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e33 persons had normal LV systolic function representing 73.3% of the whole group while 17 persons had normal diastolic function representing 37.7% of the whole group.27 persons had no SWMA representing 60% of the whole group.\u003c/p\u003e\n\u003cp\u003eData obtained from coronary angiography:\u003c/p\u003e\n\u003cp\u003eThe mean syntax score of the whole study group was 22.88\u0026plusmn;12.3. 8 (17.7%) patients had no vessels affected. 10 (22.2%) patients had one vessel affected, 6 (13.3%) patients had two vessels affected and 21 (46.6%) patients had more than two vessels affected.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e3- Data related to presence and absence of affected coronaries:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe study group was subdivided into two subgroups according to presence (n=27) or absence (n=8) of significant CAD. All demographic data matched among the two subgroups except for sex, DM and smoking that showed significant difference. There was more females in sub-group with non-affected coronaries (p value 0.033). The subgroup with affected coronaries had more diabetic patients (p value 0.023). All the subgroup with non-affected coronaries were non-smokers (p value 0.029) (Tables 2,3) (Figures 5-7).\u003c/p\u003e\n\u003cp\u003eThere was no significant difference between both sub-groups as regards any of the lipid profile parameters measured (Table 4).\u003c/p\u003e\n\u003cp\u003eComparing different items of calcium score between the two sub-groups yielded highly significant difference in Aortic root calcification (p value 0.00) and significant difference in Aortic valve calcification \u0026amp; final calcium score (p value 0.047, 0.011 respectively). Patients with significant CAD had higher aortic root calcification, aortic valve calcification and total calcium score (Table 5) (Figures 8-10).\u003c/p\u003e\n\u003cp\u003eComparing Aortic stiffness data among both subgroups yielded no significant difference regarding aortic distensibility, on the other hand there was highly significant difference between the two subgroups regarding arterial diameter change \u0026amp; strain (p value 0.007 , 0.004 respectively) and significant difference in the stiffness index (p value 0.021). (Table 6) (Figures 11-13).\u003cbr\u003eThere was no significant difference between both subgroups regarding LV systolic \u0026amp; diastolic function and SWMA (Table 7).\u003c/p\u003e\n\u003cp\u003eMultivariate regression analysis for the individually significant variables shown in the univariate analysis was done(Table 8). Only Aortic root calcification was shown to be significant independent predictor of CAD by multivariate analysis (Table 9).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e4- Data related to number of affected coronaries:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe study group was subdivided into 4 subgroups as regard number of vessels affected. All demographic data matched among the four subgroups except for DM which was predominantly present in the subgroup with multi-vessel disease (p value 0.004) (Table 10-12) (Figure 14).\u003c/p\u003e\n\u003cp\u003eComparing different items of calcium score between the four sub-groups showed highly significant difference regarding Aortic root calcification (p value 0.004) and significant difference regarding final calcium score (p value 0.027).(Table 13)(Figures 15,16).\u003c/p\u003e\n\u003cp\u003eComparing Aortic stiffness data among the four subgroups yielded no significant difference regarding aortic distensibility, meanwhile it showed highly significant difference regarding arterial diameter change \u0026amp; strain (p value 0.008 , 0.007 respectively) and significant difference regarding stiffness index (p value 0.028).(Table 14) (Figures 17-19).\u003c/p\u003e\n\u003cp\u003eThere was no significant difference between the four subgroups regarding LV systolic \u0026amp; diastolic function and SWMA (Table 15).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e5- Data related to syntax score:\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe study group was subdivided according to disease severity as estimated by syntax score into three subgroups. There was no significant difference between the subgroups as regard age but there was significant difference in gender distribution (Table 16). Patients with higher syntax scores were predominantly diabetics (Table 17) (Figures 20-22).\u003c/p\u003e\n\u003cp\u003eAll the lipid profile matched among the three sub-groups except TGS level which was highly significant (p value 0.003).(Table 18) (Figure 23)\u003cbr\u003eThere was significant difference between the three subgroups of the syntax score regarding total calcium score (p value 0.013) (Table 19) (Figure 24). However the three subgroups showed no significant difference as regard any of the aortic stiffness parameters measured (Table 20)\u003cbr\u003eThere was significant difference between the three subgroups of the syntax score concerning SWMA (p value 0.02) (Table 21) (Figure 25).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e6-Correlation between final calcium score and Aortic stiffness \u0026amp; angiographic data( syntax score and number of vessels affected):\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThere was weak negative but significant correlation between the total calcium score and arterial diameter change, strain and distensibility. There was a weak positive but significant correlation between the total calcium score and elastic modulus, stiffness index and syntax score subgroups.\u003c/p\u003e\n\u003cp\u003eThere was modest positive but significant correlation between the total calcium score and both syntax score and number of vessels affected. (Table 22) (Figures 26-28)\u003c/p\u003e\n\u003cp\u003eThere was weak negative but significant correlation between the syntax score numerical value and distensibility. There was modest negative but significant correlation between the syntax score numerical value and arterial diameter change and strain. There was a weak positive but significant correlation between the syntax score numerical value and stiffness index. There was modest positive but significant correlation between the syntax score numerical value and final calcium score. (Table 23)\u003c/p\u003e\n\u003cp\u003e\u003cu\u003e7- Receiver operateor characteristic (ROC) anaylsis for prediction of CAD\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eFinal calcium score\u003c/p\u003e\n\u003cp\u003eThe receiver operator characteristic analysis of final calcium score \u0026ge; 5 served as the best cut-off for CAD identification with the highest balanced sensitivity and specificity: 78% and 75% respectively (AUC 0.7804, P value 0.0012) (figure 29).\u003c/p\u003e\n\u003cp\u003eAortic stiffness variables:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eStiffness index\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe receiver operator characteristic analysis of stiffness index score \u0026ge; 5.47 served as the best cut-off for CAD identification with the highest balanced sensitivity and specificity 62% and 100% respectively (AUC 0.7432, P value 0.0006). (figure 30)\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eElastic modulus:\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe receiver operator characteristic analysis of elastic modulus \u0026ge; 620 served as the best cut-off for CAD identification with the highest balanced sensitivity and specificity: 55.5% and 100% respectively (AUC 0.72, P value 0.003) (figure 31)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCardiac calcifications have been historically recognized since the early days of ultrasound imaging but only recently the correlation between coronary calcification and cardiac non-coronary calcium measured either by echocardiography or\u0026nbsp;by computed tomography\u0026nbsp;was investigated.\u003csup\u003e17\u003c/sup\u003eThe detection of cardiac and vascular calcification (non- coronary artery calcification) has also been shown to be associated with atherosclerosis, severe coronary artery calcification and with obstructive coronary artery disease. It may be of value in the evaluation in patients suspected of having CAD.\u003csup\u003e17,18\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eEchocardiographic calcium score is now validated against non-coronary calcium by computed tomography with lower cost and no irradiation safety issues for reclassification of cardiac risk.\u0026nbsp;It's significantly and independently associated with all-cause mortality and stroke, with higher scores reflecting higher risk.\u003csup\u003e18\u003c/sup\u003e In parallel; many epidemiological studies have demonstrated the predictive value of aortic stiffness as an independent predictor of cardiovascular (CV) morbidity and mortality. \u003csup\u003e19,20\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn this study we tried to detect the role of echocardiography calcium score and aortic stiffness as predictive tools of severity of CAD by establishing a correlation between these variables and the patients' coronary angiography and lipid profile. We compared each component of the echo calcium score and the final score with the syntax score subgroups. Also we detected the correlation of aortic stiffness with the syntax score subgroups as well as the final calcium score.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;According to the coronary angiography we divided the study group again into two subgroups; first with no coronaries affected and the other with affected coronaries and we analyzed the data we got to detect the significant parameters we studied in this correlation.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Our study detected significant correlation between final calcium score by echocardiography and syntax score sub-groups and highly significant correlation with the numerical syntax score, that was similar to Gaibazzi N et al. that reported comparable strength of correlation in larger group of similar patients who had clinical indication to do CCTA and echocardiography.This study correlated echocardiographic calcium score with CCTA scores of coronary calcium score, non-coronary cardiac calcium and number of coronaries affected. It detected positive correlation of the final echocardiographic calcium score with the coronary calcium score obtained by CT coronaries. \u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eGaibazzi N et al. also showed a correlation between the echocardiographic calcium score and number of coronaries affected but only when the severe definition of CAD was applied (stenosis diameter \u0026gt; 70%) in CCTA, that was partially similar to our results that showed highly significant correlation between Aortic root calcification and number of affected coronaries and significant correlation between final calcium score and number of affected coronaries but we applied it on a stenosis diameter \u0026gt; 50% in CA. \u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eOur study used ROC curve to detect the best cut-off point of final calcium score and each of aortic stiffness variable to detect CAD (at least single vessel with \u0026gt;50% stenosis) with balanced sensitivity and specificity of each parameter. The capability of final calcium score to predict CAD was better than both stiffness index and elastic modulus.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Among all the demographic criteria and risk factors in our study, only sex, DM and smoking were significantly different between the group with affected coronaries and the group without. That was discordant with Gaibazzi N et al. that showed only age and prevalence of hypertension were significant. The prevalence of diabetics in our study was 48.8% compared to their prevalence that was only 14%. However the prevalence of males, active smokers and hypertensives were comparable with 46.6%, 20%, 64.4% respectively in our study and 52%, 30% and 65% Gaibazzi et al.\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Regarding the number of vessels affected among the study population; it was 17.7% with no coronaries affected, 22.2% with one vessel affected, 13.3% with 2 vessels affected and 46.6% with more than two vessels affected. On the other hand the majority of patients in Gaibazzi et al. Study (61%) had no significant CAD which may have played a role in the difference of results between the two studies. \u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Pressman GS et al. also detected the correlation between echocardiography calcium score and CAD in similar group of patients who had clinical indication to do CCTA. This study had almost the same number of participants as our study group (41). The echocardiography calcium score had different items and CAD was evaluated as CAC in CCTA. It showed significant correlation between both. \u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eIt also showed that the total cardiac calcium is better in prediction of CAD than MAC alone without commenting on other components of calcium score.30 In our study only the final calcium score had significant correlation with syntax score sub-groups but when the calcium score was correlated with the presence or absence of affected coronaries it showed highly significant correlation with Aortic root calcification and significant correlation with Aortic valve calcification as well as the final calcium score. The mean echocardiographic cardiac calcium score in this study was 3.4 (±2.5) while in our study the mean score was 4.95±1.29. \u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eCorciu AI et al. detected comparable strength of correlation in a larger group of patients (n=167) who where hospitalized. This study compared Echocardiographoc calcium score with Framingham risk score, Duke score and left ventricle mass index. It showed significant correlation between echocardiographic calcium score and the presence of CAD. Echocardiographic calcium score was assessed as calcium score index (CSI) that didn’t include papillary muscle calcification as a part of the score and the presence of CAD was assessed by Duke score that divided their study population into two subgroups. It also showed significant increase in the mean CSI with the presence of affected coronaries. This study also showed significant correlation of each component of the CSI with the presence of CAD .\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eOur study showed no significant correlation of each single component of echocardiography calcium score with the syntax score sub-groups, but when correlated with presence or absence of affected coronaries it showed highly significant difference in Aortic root calcification and significant difference in Aortic valve calcification as well as the final calcium score. Also when correlated with the number of affected coronaries it showed highly significant difference in Aortic root calcification as well as the final calcium score. \u0026nbsp;In comparison to the multivariate regression analysis that was done in our study and showed no individually significant predictors of presence of affected coronaries other than Aortic root calcification, Corciu AI et al. study showed that hypercholesterolemia, diabetes, gender and CSI were individually significant predictors of CAD status. The receiver operator characteristic analysis of CSI=4 served as the best cut-off for CAD identification in Corciu AI et al. study, but in our study the cut-off for CAD identification was ≥ 5 with 78% sensitivity and 75% specificity. \u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eOnly few studies detected the correlation between Aortic stiffness and CAD; Elbasan Z et al. correlated Aortic distensibility assessed by echocardiography with syntax score in larger group of similar population (n=376) that had clinical indication to do coronary angiography. It showed that SS was significantly higher in the AD\u003csub\u003elow\u003c/sub\u003e group compared to the AD\u003csub\u003ehigh\u003c/sub\u003e group.\u0026nbsp;\u003csup\u003e22\u003c/sup\u003e Ahmadi N et al. showed that impaired Aortic distensibility measured by computed tomography was strongly correlated with the severity of coronary atherosclerosis.71 Yildiz A et al. showed that AD was independently correlated with the severity of CAD assessed by the Gensini score in 56 stable CAD patients. \u003csup\u003e23\u003c/sup\u003e In our study, the Aortic stiffness variables were correlated with syntax score, presence or absence of coronaries and with number of coronaries affected. When correlated with syntax score subgroups there was no significant correlation with each of aortic stiffness variables but when correlated with the numerical values of syntax score there was weak negative but significant correlation with distensibility. There was modest negative but significant correlation with arterial diameter change and strain. There was a weak positive but significant correlation with stiffness index.When correlated with presence or absence of affected coronaries, there was highly significant difference in arterial diameter change \u0026amp; strain and significant difference in stiffness index. When correlated with the number of affected coronaries, there was highly significant difference in arterial diameter change \u0026amp; strain and significant difference in stiffness index. The variability in the results regarding Aortic stiffness between the current study and others may be due to variation in methodology whether by echo or by CT and also due to non-invasive measurement of systolic and diastolic blood pressure that may have been also affected by the patients’ medications or their presence in hospital setting.\u003c/p\u003e\n\u003cp\u003eOur study detected highly significant correlation between final calcium score and aortic stiffness that was not evaluated in any previous study.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAtherosclerotic CAD stands out as a very important public health problem responsible for most of the cardiovascular mortalities in both developing and developed country. Echocardiographic calcium score is associated with the severity of CAD and number of coronaries affected and thus it can be used as a new tool for cardiovascular risk stratification. The relationship between Aortic stiffness by echocardiography and severity of CAD still needs further evaluation. The low cost, availability and the radiation free nature of echocardiography make it an attractive candidate for the on-going research regarding the non-invasive tools for prediction of CAD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosure:\u003c/strong\u003e None\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest:\u003c/strong\u003e None\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNasir K, Clouse M. Role of nonenhanced multidetector CT coronary artery calcium testing in asymptomatic and symptomatic individuals. Radiology. 2012;264:637\u0026ndash;649.\u003c/li\u003e\n\u003cli\u003eSharma M, Ganguly NK. Premature coronary artery disease in Indians and its associated risk factors. Vasc Health Risk Manag. 2005;1(3):217-25.\u003c/li\u003e\n\u003cli\u003eCardiovascular disease: Prevention and Control. World Health Organization. (Accessed on March 2015, 12, at http://www.who.int/dietphysicalactivity/publications/facts/ cvd/en/).\u003c/li\u003e\n\u003cli\u003eHiggins CB. Coronary angiography a decade of advances. Am J Cardiol. 1988;62(18):7K\u0026ndash;10K.\u003c/li\u003e\n\u003cli\u003eG\u0026ouml;kdeniz T, Kalaycıoğlu E,et al Aykan A\u0026Ccedil;, et al. Value of coronary artery calcium score to predict severity or complexity of coronary artery disease. Arq Bras Cardiol. 2014;102(2):120-7.\u003c/li\u003e\n\u003cli\u003eBudoff MJ, Achenbach S, Blumenthal RS, et al. Assessment of coronary artery disease by cardiac computed tomography: a scientific statement from the American Heart Association Committee on Cardiovascular Imaging and Intervention, Council on Cardiovascular Radiology and Intervention, and Committee on Cardiac Imaging, Council on Clinical Cardiology. Circulation. 2006;114:1761\u0026ndash;1791.\u003c/li\u003e\n\u003cli\u003eRidker Pual.M, Libby Peter, editors. Braunwalds Heart Disease A Textbook of Cardiovascular Medicine. 9th ed. U.S.A.: Elsevier Saunders; 2011: p. 365.\u003c/li\u003e\n\u003cli\u003eRaj MV, Bennett DH, Stovin PG, et al. Echocardiographic assessment of mitral valve calcification. Br Heart J. 1976;38:81\u0026ndash;84.\u003c/li\u003e\n\u003cli\u003ePressman GS, Crudu V, Parameswaran-Chandrika A, et al. Can total cardiac calcium predict the coronary calcium score? Int J Cardiol. 2011;146:202\u0026ndash;206. doi: 10.1016/j.ijcard.2009.06.057.\u003c/li\u003e\n\u003cli\u003eGaibazzi N, Baldari C, Faggiano P, et al. Cardiac calcium score on 2D echo: correlations with cardiac and coronary calcium at multi-detector computed tomography. Cardiovasc Ultrasound. 2014;12:43. Published 2014 Oct 28.\u003c/li\u003e\n\u003cli\u003eLu, M. L., Gupta, S., Romero-Corral, A.,et al. Cardiac Calcifications on Echocardiography Are Associated with Mortality and Stroke. Journal of the American Society of Echocardiography,29(12), 1171-1178.\u003c/li\u003e\n\u003cli\u003eRamaraj R, Manrique C, Hashemzadeh M, et al. Mitral annulus calcification is independently associated with all-cause mortality. Exp Clin Cardiol. 2013;18(1):e5-7.\u003c/li\u003e\n\u003cli\u003eFox, C. S., Vasan, R. S., Parise, et al. Mitral Annular Calcification Predicts Cardiovascular Morbidity and Mortality. Circulation,107(11), 1492-1496.\u003c/li\u003e\n\u003cli\u003eCho JY, Kim KH. Evaluation of Arterial Stiffness by Echocardiography: Methodological Aspects. Chonnam Med J. 2016;52(2):101\u0026ndash;106. doi:10.4068/cmj.2016.52.2.101.\u003c/li\u003e\n\u003cli\u003eSerruys PW, Onuma Y, Garg S,et al. Assessment of the SYNTAX score in the Syntax study. EuroIntervention. 2009;5:50-6\u003c/li\u003e\n\u003cli\u003eCapodanno D, Di Salvo ME, Cincotta G,et al. Usefulness of the Syntax score for predicting clinical outcome after percutaneous coronary intervention of unprotected left main coronary artery disease. Circulation Cardiovasc Intv 2009;2:302-8\u003c/li\u003e\n\u003cli\u003eRaggi P, Shaw LJ, Berman DS \u0026amp; Callister TQ. Prognostic value of coronary artery calcium screening in subjects with and without diabetes. Journal of the American College of Cardiology, 2004; 43(9), 1663-1669.\u003c/li\u003e\n\u003cli\u003eMcEniery CM, Yasmin McDonnell B, Munnery M, et al. Central Pressure: Variability and Impact of Cardiovascular Risk Factors. Hypertension, 2008; 51(6): 1476-1482.\u003c/li\u003e\n\u003cli\u003eManisty C, Mayet J, Tapp RJ, et al. Wave Reflection Predicts Cardiovascular Events in Hypertensive Individuals Independent of Blood Pressure and Other Cardiovascular Risk Factors. Journal of the American College of Cardiology, 2010; 56(1), 24-30.\u003c/li\u003e\n\u003cli\u003ePereira T, Maldonado J, Pereira L, et al. Aortic stiffness is an independent predictor of stroke in hypertensive patients. Arq Bras Cardiol. 2013; 100 (5): 437\u0026ndash;443. Portuguese.\u003c/li\u003e\n\u003cli\u003eCorciu, A. I., Siciliano, V., Poggianti, E.,et al Cardiac calcification by transthoracic echocardiography in patients with known or suspected coronary artery disease. International Journal of Cardiology, 142(3), 288-295. doi:10.1016/j.ijcard.2009.01.021.\u003c/li\u003e\n\u003cli\u003eElbasan Z, Sahin D, G\u0026uuml;r M, et al. (2013). Aortic Distensibility and Extent and Complexity of Coronary Artery Disease in Patients with Stable Hypertensive and Nonhypertensive Coronary Artery Disease. Medical Principles and Practice, 2013; 22(3), 260-264.\u003c/li\u003e\n\u003cli\u003eAhmadi N, Nabavi V, Hajsadeghi F, et al. Impaired aortic distensibility measured by computed tomography is associated with the severity of coronary artery disease. Int J Cardiovasc Imaging 2011; 27: 459\u0026ndash;469.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:Grading system of cardiac and aortic root calcium on echocardiographic examination. 14\u003c/strong\u003e\u003c/p\u003e\n\u003ctable\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePapillary muscle calcium\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMitral annular calcium\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAortic valve sclerosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAorta root calcium\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAbsent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMild \u003cstrong\u003e\u0026lt;\u003c/strong\u003e 5 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePresent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eModerate 5\u0026ndash;10\u0026nbsp;mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSevere \u003cstrong\u003e\u0026gt;\u003c/strong\u003e 10 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSevere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAortic valve sclerosis graded as follows: Absent\u0026thinsp;=\u0026thinsp;Normal cusp thickness (\u0026lt;2 mm), and normal reflectivity; Mild\u0026thinsp;=\u0026thinsp;Cusp thickness \u0026gt;2 mm and/or increased reflectivity; Moderate\u0026thinsp;=\u0026thinsp;Thickness \u0026gt;4 mm and/or diffuse or focal cusp hyperreflectivity; Severe\u0026thinsp;=\u0026thinsp;Thickness \u0026gt;6 mm and/or marked echoreflectivity. Final score was graded from 0 to 8.\u0026nbsp;\u003cbr\u003e\u0026nbsp;(Cho JY, Kim KH. Evaluation of Arterial Stiffness by Echocardiography: Methodological Aspects. Chonnam Med J. 2016;52(2):101\u0026ndash;106. doi:10.4068/cmj.2016.52.2.101.)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e2\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eComparison between the two subgroups regarding age and sex\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAffected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo affected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAffected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 37\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e49.00 \u0026plusmn; 8.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e53.51 \u0026plusmn; 8.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e-1.432\u0026bull;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e37 \u0026ndash; 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e35 \u0026ndash; 65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7 (87.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e17 (45.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e4.564*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e20 (54.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e*: Chi-square test; \u0026bull;: Independent t-test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e3\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eComparison between the two subgroups regarding clinical risk factors\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eHistory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAffected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo affected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAffected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 37\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7 (87.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e16 (43.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e5.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e21 (56.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eHTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e14 (37.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e23 (62.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e8 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e18 (48.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e7.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSmoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9 (24.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEx smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e10 (27.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003ePrevious ischemic\u0026nbsp;\u003cbr\u003e\u0026nbsp;events\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e20 (54.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e1.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e17 (45.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eFamily history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7 (87.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e36 (97.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e1.487\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e*: Chi-square test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Table (\u003c/strong\u003e \u003cstrong\u003e4\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eLipid profile among both sub groups:\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eLipid profile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAffected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u0026bull;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo affected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAffected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 37\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eTotal cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e165.50 \u0026plusmn; 29.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e171.27 \u0026plusmn; 27.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e-0.538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e135 \u0026ndash; 217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e125 \u0026ndash; 268\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eLDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e100.50 \u0026plusmn; 23.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e108.81 \u0026plusmn; 24.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e-0.888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e76 \u0026ndash; 150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e71 \u0026ndash; 176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eHDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e43.38 \u0026plusmn; 4.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e40.68 \u0026plusmn; 7.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e1.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e35 \u0026ndash; 50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e30 \u0026ndash; 61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eTGS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e124.38 \u0026plusmn; 30.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e161.51 \u0026plusmn; 65.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e-1.556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e98 \u0026ndash; 187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e60 \u0026ndash; 334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e\u0026bull;: Independent t-test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e5\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eCalcium score among both subgroups:\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eCalcium score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAffected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u0026ne;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo affected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAffected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 37\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAortic valve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e-1.983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eMitral annulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (2 \u0026ndash; 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (2 \u0026ndash; 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAortic root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0 \u0026ndash; 0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e-3.628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003ePapillary muscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (0 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e-1.736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eFinal score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (3 \u0026ndash; 4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (5 \u0026ndash; 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e-2.541\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 \u0026ndash; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 \u0026ndash; 7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e\u0026ne;: Mann-Whitney test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;Table (\u003c/strong\u003e \u003cstrong\u003e6\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eAortic stiffness among both sub-groups:\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAortic stiffness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAffected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo affected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAffected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 37\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eArterial diameter\u0026nbsp;\u003cbr\u003e\u0026nbsp;change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3.63 \u0026plusmn; 1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.33 \u0026plusmn; 1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e2.815\u0026bull;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 \u0026ndash; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eStrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.14 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.08 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e3.008\u0026bull;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.09 \u0026ndash; 0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.03 \u0026ndash; 0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eElastic modulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e387.5 (276.67 \u0026ndash; 473.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e647.5 (366.67 \u0026ndash; 1050)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e-1.933\u0026ne;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e166.67 \u0026ndash; 550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e180 \u0026ndash; 1920\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eStiffness index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3.74 (2.88 \u0026ndash; 4.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7.14 (3.52 \u0026ndash; 10.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e-2.313\u0026ne;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.39 \u0026ndash; 5.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.26 \u0026ndash; 16.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eDistensbility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.005 (0.004 \u0026ndash; 0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.003 (0.002 \u0026ndash; 0.005)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e-1.933\u0026ne;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.004 \u0026ndash; 0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.001 \u0026ndash; 0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant \u0026bull;: Independent t-test; \u0026ne;: Mann-Whitney test \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e7\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eOther echocardiographic data among both subgroups:\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAffected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo affected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAffected vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 37\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eSystolic LV function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e27 (73.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eImpaired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e10 (27.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eDiastolic LV function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e12 (32.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e2.896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDD I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 (37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e21 (56.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDD II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (10.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eSWMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e21 (56.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e16 (43.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e*: Chi-square test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e8\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eUnivariate analysis\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eS.E.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eWald\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eOdds ratio (OR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e95% C.I. for OR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eLower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eUpper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e8.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.919\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e73.789\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3.926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e82.414\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAortic valve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9.724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e19.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e122.995\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAortic root \u0026gt; 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9.724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e19.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e122.995\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFinal calcium score \u0026gt; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6.894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e10.875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e64.582\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eArterial diameter change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e-0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.403\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.870\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eStiffness index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3.964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.817\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e9\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eMulti-variate analysis\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eS.E.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eWald\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eOdds ratio (OR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e95% C.I. for OR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eLower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eUpper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e126.404\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAortic valve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4.361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e46.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAortic root \u0026gt; 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e11.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e87.312\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFinal calcium score \u0026gt; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e41.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eArterial diameter change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.889\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9.779\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eStiffness index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.694\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e10\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eComparison between the four subgroups regarding age and sex \u0026nbsp;\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. of vessels affected groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eOne vessel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTwo vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e\u0026gt;2 vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e49.00 \u0026plusmn; 8.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e49.8 \u0026plusmn; 8.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e52.17 \u0026plusmn; 11.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e55.67 \u0026plusmn; 6.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e2.025\u0026bull;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e37 \u0026ndash; 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e35 \u0026ndash; 63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e41 \u0026ndash; 65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e39 \u0026ndash; 64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7 (87.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e5.821*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e12 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e*: Chi-square test; \u0026bull;: One Way ANOVA test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e11\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eComparison between the four subgroups regarding clinical risk factors \u0026nbsp;\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eHistory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. of vessels affected groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eOne vessel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTwo vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e\u0026gt;2 vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7 (87.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (83.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e13.313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e16 (76.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eHTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e2.293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e15 (71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e8 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e11 (52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e9.492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSmoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 (30.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEx smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003ePrevious ischemic\u0026nbsp;\u003cbr\u003e\u0026nbsp;events\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (83.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e4.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e12 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eFamily history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7 (87.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e10 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (83.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e21 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e4.775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e*: Chi-square test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e12\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eShowing the lipid profile among the four subgroups:\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eLipid profile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. of vessels affected groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u0026bull;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eOne vessel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTwo vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e\u0026gt;2 vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eTotal\u0026nbsp;\u003cbr\u003e\u0026nbsp;cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e165.50 \u0026plusmn; 29.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e165.3 \u0026plusmn; 21.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e154.33 \u0026plusmn; 22.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e178.95 \u0026plusmn; 28.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e1.656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e135 \u0026ndash; 217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e134 \u0026ndash; 203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e125 \u0026ndash; 188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e140 \u0026ndash; 268\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eLDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e100.50 \u0026plusmn; 23.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e109.1 \u0026plusmn; 10.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e98.67 \u0026plusmn; 23.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e111.57 \u0026plusmn; 28.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.701\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.557\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e76 \u0026ndash; 150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e95 \u0026ndash; 133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e71 \u0026ndash; 124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e75 \u0026ndash; 176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eHDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e43.38 \u0026plusmn; 4.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e40.6 \u0026plusmn; 8.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e42 \u0026plusmn; 3.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e40.33 \u0026plusmn; 7.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e35 \u0026ndash; 50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e32 \u0026ndash; 61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e35 \u0026ndash; 45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e30 \u0026ndash; 61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eTGS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e124.38 \u0026plusmn; 30.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e152.5 \u0026plusmn; 34.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e122.33 \u0026plusmn; 45.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e177 \u0026plusmn; 76.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e2.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e98 \u0026ndash; 187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e110 \u0026ndash; 230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e60 \u0026ndash; 175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e70 \u0026ndash; 334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e\u0026bull;: One Way ANOVA test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e13\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eThe calcium score among the four subgroups\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eCalcium score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. of vessels affected groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u0026ne;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eOne vessel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTow vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e\u0026gt;2 vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAortic valve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e6.839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eMitral annulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (2 \u0026ndash; 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (2 \u0026ndash; 3)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.5 (2 \u0026ndash; 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (2 \u0026ndash; 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAortic root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0 \u0026ndash; 0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e13.597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003ePapillary muscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e7.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eFinal score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (3 \u0026ndash; 4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (5 \u0026ndash; 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (4 \u0026ndash; 5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (5 \u0026ndash; 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e9.192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 \u0026ndash; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 \u0026ndash; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 \u0026ndash; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 \u0026ndash; 7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e\u0026ne;: Kruskal-Wallis test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;Table (\u003c/strong\u003e \u003cstrong\u003e14\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eShowing the Aortic stiffness among the four-subgroups\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAortic stiffness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. of vessels affected groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eOne vessel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTow vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e\u0026gt;2 vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eArterial diameter\u0026nbsp;\u003cbr\u003e\u0026nbsp;change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3.63 \u0026plusmn; 1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 \u0026plusmn; 1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1.83 \u0026plusmn; 0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.15 \u0026plusmn; 1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e4.562\u0026bull;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 \u0026ndash; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eStrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.14 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.11 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.07 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.08 \u0026plusmn; 0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e4.634\u0026bull;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.09 \u0026ndash; 0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.03 \u0026ndash; 0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.03 \u0026ndash; 0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.03 \u0026ndash; 0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eElastic modulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e387.5\u0026nbsp;\u003cbr\u003e\u0026nbsp;(276.67 \u0026ndash; 473.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e380.83\u0026nbsp;\u003cbr\u003e\u0026nbsp;(270 \u0026ndash; 870)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e825\u0026nbsp;\u003cbr\u003e\u0026nbsp;(620 \u0026ndash; 1080)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e787.5\u0026nbsp;\u003cbr\u003e\u0026nbsp;(373.33 \u0026ndash; 1200)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e6.301\u0026ne;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e166.67 \u0026ndash; 550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e202.5 \u0026ndash; 1300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e190 \u0026ndash; 1200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e180 \u0026ndash; 1920\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eStiffness index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3.74\u0026nbsp;\u003cbr\u003e\u0026nbsp;(2.88 \u0026ndash; 4.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3.52\u0026nbsp;\u003cbr\u003e\u0026nbsp;(3.19 \u0026ndash; 10.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7.92\u0026nbsp;\u003cbr\u003e\u0026nbsp;(6.72 \u0026ndash; 10.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7.57\u0026nbsp;\u003cbr\u003e\u0026nbsp;(5.12 \u0026ndash; 11.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e9.131\u0026ne;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.39 \u0026ndash; 5.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.74 \u0026ndash; 11.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.26 \u0026ndash; 13.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.59 \u0026ndash; 16.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eDistensbility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.005\u0026nbsp;\u003cbr\u003e\u0026nbsp;(0.004 \u0026ndash; 0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.005\u0026nbsp;\u003cbr\u003e\u0026nbsp;(0.002 \u0026ndash; 0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.002\u0026nbsp;\u003cbr\u003e\u0026nbsp;(0.002 \u0026ndash; 0.003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.003\u0026nbsp;\u003cbr\u003e\u0026nbsp;(0.002 \u0026ndash; 0.005)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e6.301\u0026ne;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.004 \u0026ndash; 0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.002 \u0026ndash; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.002 \u0026ndash; 0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.001 \u0026ndash; 0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e\u0026bull;: One Way ANOVA test; \u0026ne;: Kruskal-Wallis test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;Table (\u003c/strong\u003e \u003cstrong\u003e15\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eshowing the echocardiographic data among the four subgroups\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. of vessels affected groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eOne vessel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTow vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e\u0026gt;2 vessels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eSystolic LV function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e8 (80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e13 (61.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e3.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eImpaired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e8 (38.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eDiastolic LV function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e8.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e0.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDD I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 (37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e12 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDD II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (19.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eSWMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (83.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e10 (47.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e3.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e11 (52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e*: Chi-square test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e16\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eTable comparing between the three subgroups regarding age and sex\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eCoronary angiography syntax score groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eLow\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eIntermediate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eHigh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e52.52 \u0026plusmn; 8.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e51.56 \u0026plusmn; 8.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e53.85 \u0026plusmn; 8.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.213\u0026bull;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e37 \u0026ndash; 65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e35 \u0026ndash; 61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e39 \u0026ndash; 63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e14 (60.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9 (69.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e8.291*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9 (39.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e8 (88.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (30.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e*: Chi-square test; \u0026bull;: One Way ANOVA test; \u0026ne;: Kruskal-Wallis test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e17\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eTable comparing between the three subgroups regarding clinical risk factors\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eHistory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eCoronary angiography syntax score groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eLow\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eIntermediate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eHigh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e18 (78.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e14.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (21.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e11 (84.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eHTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e10 (43.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 (23.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e1.533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e13 (56.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e10 (76.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e15 (65.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9 (69.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e6.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e0.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSmoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (17.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEx smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (17.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003ePrevious ischemic\u0026nbsp;\u003cbr\u003e\u0026nbsp;events\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e16 (69.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (38.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e3.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7 (30.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e8 (61.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eFamily history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e21 (91.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e13 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e2.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e*: Chi-square test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e18\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eLipid profile of the study population compared in the three sub-groups\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eLipid profile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eCoronary angiography syntax score groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u0026bull;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eLow\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eIntermediate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eHigh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eTotal cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e164.04 \u0026plusmn; 23.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e167.44 \u0026plusmn; 21.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e183.15 \u0026plusmn; 33.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e2.215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e125 \u0026ndash; 217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e134 \u0026ndash; 195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e147 \u0026ndash; 268\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eLDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e102.39 \u0026plusmn; 17.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e108.22 \u0026plusmn; 18.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e115.46 \u0026plusmn; 34.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e1.258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e71 \u0026ndash; 150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e75 \u0026ndash; 133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e76 \u0026ndash; 176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eHDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e42.17 \u0026plusmn; 6.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e40.89 \u0026plusmn; 5.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e39.54 \u0026plusmn; 8.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e32 \u0026ndash; 61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e33 \u0026ndash; 51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e30 \u0026ndash; 61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eTGS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e128.17 \u0026plusmn; 29.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e160 \u0026plusmn; 46.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e198.69 \u0026plusmn; 87.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e6.789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e60 \u0026ndash; 187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e70 \u0026ndash; 230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e76 \u0026ndash; 334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e\u0026bull;: One Way ANOVA test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e19\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eComparison between echo calcium score and syntax score subgroups:\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eCalcium score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eCoronary angiography syntax score groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u0026ne;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eLow\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eIntermediate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eHigh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAortic valve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e5.539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eMitral annulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (2 \u0026ndash; 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e3 (2 \u0026ndash; 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (2 \u0026ndash; 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e1.105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAortic root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (0 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e5.405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003ePapillary muscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (0 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (1 \u0026ndash; 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e3.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0 \u0026ndash; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eFinal score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (3 \u0026ndash; 5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (5 \u0026ndash; 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (5 \u0026ndash; 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e8.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 \u0026ndash; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 \u0026ndash; 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 \u0026ndash; 7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e\u0026ne;: Kruskal-Wallis test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e20\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eComparison between Aortic stiffness and syntax score subgroups:\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eAortic stiffness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eCoronary angiography syntax score groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eLow\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eIntermediate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eHigh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eArterial diameter\u0026nbsp;\u003cbr\u003e\u0026nbsp;change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.91 \u0026plusmn; 1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.44 \u0026plusmn; 1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 \u0026plusmn; 1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e2.229\u0026bull;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 \u0026ndash; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eStrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.11 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.08 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.07 \u0026plusmn; 0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e2.641\u0026bull;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.03 \u0026ndash; 0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.03 \u0026ndash; 0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.03 \u0026ndash; 0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eElastic modulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e433.33 (293.33 \u0026ndash; 870)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e900 (320 \u0026ndash; 1080)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e697.5 (389.17 \u0026ndash; 1200)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e2.374\u0026ne;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e166.67 \u0026ndash; 1300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e256 \u0026ndash; 1350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e180 \u0026ndash; 1920\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eStiffness index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4.05 (3.19 \u0026ndash; 7.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7.87 (3.8 \u0026ndash; 9.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7 (5.12 \u0026ndash; 13.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e3.919\u0026ne;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.26 \u0026ndash; 13.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.65 \u0026ndash; 14.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2.59 \u0026ndash; 16.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eDistensbility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.005 (0.002 \u0026ndash; 0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.002 (0.002 \u0026ndash; 0.006)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.003 (0.002 \u0026ndash; 0.005)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e2.374\u0026ne;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.002 \u0026ndash; 0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.002 \u0026ndash; 0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.001 \u0026ndash; 0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e\u0026bull;: One Way ANOVA test; \u0026ne;: Kruskal-Wallis test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e21\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eCorrelation between other echocardiographic data and syntax score subgroups:\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eCoronary angiography syntax score groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eTest value*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eLow\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eIntermediate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eHigh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNo. = 13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eSystolic LV function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e19 (82.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e9 (69.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e2.578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eImpaired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (17.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (30.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eDiastolic LV function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e11 (47.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e4 (30.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e2.992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp align=\"center\"\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDD I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e11 (47.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7 (53.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDD II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e1 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eSWMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e17 (73.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e2 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e8 (61.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e7.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp align=\"center\"\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e6 (26.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e7 (77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e5 (38.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003e*: Chi-square test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e22\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eCorrelation between final Calcium score and Lipid profile \u0026amp; Aortic distensibility \u0026amp; angiographic data (syntax score and number of vessels affected)\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eFinal calcium score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003er\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eArterial diameter change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e-0.377*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eStrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e-0.363*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eElastic modulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.417**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eStiffness index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.397**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDistensbility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e-0.417**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCoronary angiography syntax score groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.338*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.041\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSyntax score numerical value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.4677**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo. of vessels affected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.428**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003eSpearman correlation coefficient\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable (\u003c/strong\u003e \u003cstrong\u003e23\u003c/strong\u003e \u003cstrong\u003e):\u0026nbsp;\u003c/strong\u003eCorrelation between syntax score numerical value and total Calcium score \u0026amp; Aortic stiffness variables:\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eSyntax score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eNumerical value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003er\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTotal calcium score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e**0.4677\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eArterial diameter change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e**-0.4437\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eStrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e**-0.4521\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eElastic modulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eStiffness index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e*0.349\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDistensbility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e*-0.376\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp align=\"center\"\u003e\u003cstrong\u003e0.0107\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eP-value \u0026gt; 0.05: Non significant; P-value \u0026lt; 0.05: Significant; P-value \u0026lt; 0.01: Highly significant\u003c/p\u003e\n\u003cp\u003eSpearman correlation coefficient\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Echocardiography calcium score, coronary calcium score, Aortic stiffness, Atherosclerotic coronary artery disease","lastPublishedDoi":"10.21203/rs.3.rs-3912043/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3912043/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Coronary artery disease (CAD) represents a leading cause of death worldwide. Coronary angiography represents the gold standard for diagnosis and selection of the best treatment for patients with CAD. However some efforts have been made to predict CAD severity and complexity using non-invasive methods to identify the patients at high risk for cardiovascular events with less risk to the patients and before doing coronary angiography. Characterization of coronary-artery calcification by computed tomography known as Coronary artery calcium score (CACS) is proven to be equivalent to the total coronary atherosclerosis load and the angiographically significant lesions. Echocardiographic calcium score is now validated against non-coronary calcium by computed tomography with lower cost and no irradiation safety issues for reclassification of cardiac risk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim and Objectives:\u003c/strong\u003e to determine the correlation of echocardiography calcium score and Aortic stiffness to severity of coronary artery disease.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatients and Methods:\u003c/strong\u003e Patients coming to Ain Shams University Hospitals for elective coronary angiography were subjected to history taking, examination, blood samples and echocardiographic examination. The calculated echocardiographic calcium score and calculated Aortic stiffness were correlated with their coronary angiography films.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The study included 45 patients. The mean final calcium score of the whole study group was 4.95±1.29. The mean Aortic distensibility was 0.0044±0.0029. The mean syntax score of the whole study group was 22.88±12.3. There was highly significant difference between the numerical values of syntax score and final calcium score. There was weak negative but significant correlation between the syntax score numerical value and aortic distensibility.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Echocardiographic calcium score is associated with the severity of CAD. The relationship between Aortic stiffness by echocardiography and severity of CAD still needs further evaluation. The low cost, availability and the radiation free nature of echocardiography make it an attractive candidate regarding the non-invasive tools for prediction of CAD.\u003c/p\u003e","manuscriptTitle":"Echocardiography Calcium Score And Aortic Stiffness As Predictive Tools Of Severity Of Coronary Artery Disease. A Single Center Egyptian Experience","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-01 16:19:35","doi":"10.21203/rs.3.rs-3912043/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c570fa08-8b1f-4536-9fa5-d2adf896df96","owner":[],"postedDate":"February 1st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-23T12:23:21+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-01 16:19:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3912043","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3912043","identity":"rs-3912043","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}