Central Blood Pressure Association with Micro- and Macro-vascular Complications in A sample of type 2 Diabetic Patients: A Case-Control Study

Central Blood Pressure Association with Micro- and Macro-vascular Complications in A sample of type 2 Diabetic Patients: A Case-Control Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Central Blood Pressure Association with Micro- and Macro-vascular Complications in A sample of type 2 Diabetic Patients: A Case-Control Study Salwa Seddik Hosni, Mona Mohamed Abdel Salam, Hoda Adel Afifi, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8811000/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Vascular complications in diabetes and hypertension significantly contribute to cardiovascular morbidity and mortality. Aim This study assessed the association between central blood pressure and vascular complications in patients with type 2 diabetes and hypertension. It also explored its role in predicting microvascular and macrovascular complications. Methods This case-control study included 100 patients aged 40 to 60 years with type 2 diabetes and newly diagnosed hypertension: 50 cases with vascular complications and 50 controls. Patients were further stratified based on the presence of microvascular or macrovascular complications. Central and peripheral blood pressures, carotid intima-media thickness, ankle-brachial index, and augmentation index standardized to 75 beats per minute were measured. Other variables assessed included demographic data, anthropometric measurement, systemic examination, laboratory data, echocardiographic parameters, fundus findings, and glucose parameters. Results Central systolic and diastolic blood pressures were significantly higher in cases than controls (p < 0.05). Subgroup analyses showed that central systolic blood pressure was significantly higher in patients with both microvascular and macrovascular complications (p < 0.05). Logistic regression analyses performed for each subgroup demonstrated that central systolic blood pressure independently predicted microvascular (odds ratio = 1.064, 95 percent confidence interval: 1.030 to 1.099) and macrovascular (odds ratio = 1.183, 95 percent confidence interval: 1.097 to 1.275) complications. Predictive abilities were comparable to those of peripheral systolic blood pressure. Conclusion Central systolic blood pressure is significantly associated with vascular complications and independently predicts both microvascular and macrovascular complications. It demonstrated similar predictive ability for microvascular complications and a marginally stronger predictive ability for macrovascular complications. Type 2 Diabetes hypertension vascular complications central blood pressure Figures Figure 1 Introduction Uncontrolled blood pressure (BP) in diabetic hypertensive patients is associated with an increased risk of morbidity and mortality from cardiovascular illnesses. It is a crucial step for treating diabetic patients since it is one of the best methods to avoid microvascular, macrovascular, and fatal consequences [ 1 ]. According to Hegazi et al., about 15.6% of all adults in Egypt between the ages of 20 and 79 have type 2 diabetes (T2DM) [ 2 ]. Additionally, the 2017 WHO stepwise survey in Egypt reported that the prevalence of hypertension has been increasing, estimated to be 29.5% [ 3 ]. Type 2 diabetes and hypertension are known to be prevalent comorbidities [ 4 ], as numerous previous studies demonstrate that diabetic patients were approximately twice more likely to develop hypertension compared to patients without the disease, which contributes to the high prevalence of cardiovascular disease (CVD) [ 5 , 6 ]. Diabetes and hypertension are intimately related as both share a number of risk factors, such as endothelial cell dysfunction, arterial remodeling, vascular inflammation, dyslipidemia, and obesity [ 1 ]. Additionally, there is a significant overlap between the cardiovascular consequences of both diabetes and hypertension, which are predominantly driven by micro- and macrovascular disorders [ 7 ]. Numerous randomized controlled trials and meta-analyses involving antihypertensive medications demonstrate that reducing peripheral blood pressure improves cardiovascular and renal outcomes [ 8 , 9 ]. Some observational studies have suggested that the peripheral BP measured in the brachial artery may not accurately reflect the central BP, which is measured in the aortic artery [ 10 , 11 ]. Strokes and heart attacks aren't brought on by high BP in the arm (brachial) artery; instead, it's high BP in the central arteries that have direct contact with the brain and the heart [ 12 ]. Many randomized studies and meta-analyses show that even with the same peripheral BP, patients with high central BP had a statistically significant increased risk of cardiovascular disease than those with low central BP [ 10 , 13 ]. It has been determined that central BP could serve as an independent predictor of cardiovascular disease [ 14 ]. The predictive importance of central blood pressure in patients with diabetes mellitus has not been thoroughly examined in many studies. Thus, the goal of the current case-control study was to assess the relationship between central BP and micro- and macrovascular complications in T2DM hypertensive patients. Patients and Methods This case-control study compared patients with type 2 diabetes mellitus (T2DM) and newly diagnosed hypertension who had overt vascular complications (cases) with those without vascular complications (controls). To further explore specific vascular complications, all patients (cases and controls; N = 100) were stratified into subgroups based on the presence or absence of macrovascular and microvascular complications. Participants were recruited from the internal medicine and diabetes wards, as well as the outpatient clinics of Nasser Institute and Ain Shams University Hospitals, between September 2022 and July 2023. The study was approved by the regional ethics committee at Ain Shams University (IRB No: .......) and informed consent was obtained from all participants. Eligibility We included patients with T2DM with newly diagnosed hypertension with age ranging from 40 to 60 years. We excluded patients with cardiac or cerebrovascular events in the last 6 months, patients with chronic kidney disease and endocrine conditions causing secondary hypertension. We also excluded patients currently receiving sex hormones, lithium, digoxin or non-depolarizing skeletal muscle relaxants and pregnant or breast-feeding women. Sample size Sample size calculation was performed using G*Power 3 software [ 15 ]. Setting the power at 80% and the alpha error at 0.05, a total sample size of 100 was determined, with 50 patients in each group. This sample size was sufficient to detect a medium effect size difference (d = 0.5) regarding central blood pressure. Data collection A questionnaire was used to collect information on patients' age, sex, smoking status, and the duration of diabetes mellitus and hypertension (not presented in tables). The questionnaire also included details on the history of micro- or macrovascular complications (cerebrovascular disease, peripheral vascular disease, ischemic heart disease, retinopathy, nephropathy, and neuropathy), past medical history, and current medication use. Anthropometric data, including height, weight, and body mass index (BMI), were also recorded. Each patient underwent a systemic examination, which included assessments of the neurological, chest, abdominal, and cardiovascular systems. Peripheral blood pressure (BP), including brachial BP and ankle-brachial index (ABI), along with heart rate at rest, were measured. Peripheral BP was recorded at the brachial artery and at the posterior tibial and dorsalis pedis arteries for ABI calculation. BP was measured according to the JNC8 guidelines, with patients seated quietly for 10 minutes, and three readings were taken with a one-minute interval. The final two readings were averaged to calculate the mean brachial BP [ 16 ]. Systolic pressure from the posterior tibial or dorsalis pedis arteries was measured using the same technique on the lower limbs [ 17 ]. Central blood pressure was measured using the Mobil-O-Graph device [ 18 ], which uses a brachial-based cuff to obtain central pressure curves processed via a transfer function. Central systolic and diastolic BP, as well as the augmentation index adjusted for a heart rate of 75 beats per minute (AIx@75), were recorded as indicators of arterial stiffness [ 19 ]. Venous blood samples were obtained for a fasting lipid profile, fasting plasma glucose, 2-hour plasma glucose, glycated hemoglobin (HbA1c), and serum creatinine. Estimated glomerular filtration rate (eGFR) was calculated using the National Kidney Foundation equation [ 20 ], and the Albumin/Creatinine Ratio (A/C ratio) was measured. Additional assessments included fundus examination, echocardiography, carotid duplex, and carotid intima-media thickness (cIMT). Data Management and Statistical Analysis: Data was collected, coded, and entered into SPSS (Statistical Package for the Social Sciences, SPSS Inc., Chicago, IL, USA), version 22. Qualitative data were described using frequencies and percentages, and comparisons were made using Fisher's Exact and Chi-square (χ²) tests. Quantitative data were expressed as mean ± standard deviation (SD) or median (range), depending on the distribution of the data. Comparisons between groups were made using the student's t-test and ANOVA for normally distributed data, or the Mann-Whitney U test and Kruskal-Wallis test for non-normally distributed data. Odds ratios (OR) with 95% confidence intervals (CI) were calculated, and logistic regression was performed to predict the development of diabetic micro- and macrovascular complications in each subgroup. A P-value < 0.05 was considered statistically significant. Results Baseline Characteristics Regarding baseline data, there were no significant differences in gender distribution or age between the two groups. However, cases had significantly higher BMI (P = 0.004), smoking rates (P = 0.022), and longer duration of diabetes mellitus (P < 0.001) compared to controls. Additionally, cases had a higher percentage of patients receiving beta blockers (P = 0.029) and insulin (P < 0.001) (Table 1). The distribution of complications among cases was presented in Fig. 1 . Comparison of Cases and Controls Cases also had significantly higher peripheral and central systolic and diastolic BP, average peripheral BP, CIMT, and Aix@75, as well as significantly lower ABI compared to controls (P < 0.001). Moreover, cases showed significantly higher fasting blood glucose, 2-hour blood glucose, HbA1c, triglycerides (P < 0.001), total cholesterol (P = 0.011), and A/C ratio (P < 0.001 for each). Additionally, eGFR was significantly lower in cases compared to controls (P = 0.005) (Table 2). Prevalence of Complications Out of 100 patients with type 2 diabetes mellitus (DM) and early diagnosed hypertension (HTN) studied, 19% (n = 19) had macrovascular complications, and 46% (n = 46) had microvascular complications. Macrovascular Complications On comparing patients with and without macrovascular complications, results showed significantly higher BMI, longer diabetes duration, higher peripheral and central systolic and diastolic BP, mean peripheral BP, CIMT, and Aix@75, as well as significantly lower ABI in those with macrovascular complications (P < 0.05). Moreover, these patients showed significantly higher fasting blood glucose (P = 0.006), 2-hour blood glucose (P = 0.001), HbA1c (P = 0.001), LDL (P = 0.003), and triglyceride levels (P = 0.010), and significantly lower HDL (P = 0.006). Additionally, the use of beta-blockers and insulin therapy was significantly higher, while the use of CCBs was significantly lower among patients with macrovascular complications (Table 3). Multivariable Logistic Regression Analysis identified longer disease duration, higher peripheral and central SBP, Aix@75, fasting blood glucose, HbA1c, and LDL as significant predictors of macrovascular complications (Table 5). Microvascular Complications On comparing patients with and without microvascular complications, results showed significantly higher BMI, longer diabetes duration, higher peripheral and central systolic and diastolic BP, mean peripheral BP, and CIMT in those with microvascular complications (P < 0.05). Additionally, these patients showed significantly higher fasting blood glucose, 2-hour blood glucose, and HbA1c (P < 0.001 for each), as well as significantly higher triglyceride levels (P = 0.002). The A/C ratio was significantly higher, and eGFR was significantly lower in patients with microvascular complications compared to those without complications (P < 0.01). Furthermore, insulin therapy was significantly more common in patients with microvascular complications (Table 4). Multivariable Logistic Regression Analysis identified higher BMI, longer disease duration, higher peripheral and central SBP, Aix@75, CIMT, fasting blood glucose, HbA1c, triglyceride levels, A/C ratio, and lower eGFR as significant predictors of microvascular complications (P < 0.05) (Table 6). Table (1) Comparison between cases and controls as regards baseline data including their descriptive statistics Baseline data Cases (n = 50) controls(n = 50) P-value Age (years) 51.86 ± 5.64 49.96 ± 6.68 0.128 Gender 0.205 • Male 14 (28.0%) 20 (40.0%) • Female 36 (72.0%) 30 (60.0%) Body mass index (kg/m 2 ) 33.6 (20.7–58.6) 30.8 (19.3–46.9) 0.004 Cigarette smoking 14 (28.0%) 5 (10.0%) 0.022 Duration of diabetes mellitus (years) 7.5 (1 month–25 yrs) 1.5 (1 month–10 yrs) < 0.001 Received medications Anti-hypertensive medication • Beta blocker 20 (40.0%) 10 (20.0%) 0.029 • Diuretics 18 (36.0%) 19 (38.0%) 0.836 • ACEI inhibitors 17 (34.0%) 16 (32.0%) 0.832 • CCBs 8 (16.0%) 16 (32.0%) 0.061 • ARBS 15 (30.0%) 11 (22.0%) 0.362 Anti-diabetic medications < 0.001 • Oral hypoglycemic agents 21 (42.0%) 50 (100.0%) • Insulin 29 (58.0%) 0 (0.0%) ACEI : angiotensin-converting enzyme inhibitors; CCBs : Calcium channel blockers; ARBS : Angiotensin receptor blockers. P-values in bold indicate statistical significance (P < 0.05) Table (2) Comparison of Clinical and Laboratory Parameters Between Cases and Controls including their descriptive statistics Variables Cases (n = 50) Controls (n = 50) P-value Peripheral SBP (mmHg) 133.50 ± 17.30 115.72 ± 8.28 < 0.001 Peripheral DBP (mmHg) 84.62 ± 11.78 76.72 ± 8.91 < 0.001 Mean peripheral BP (mmHg) 101.78 ± 12.72 89.72 ± 7.84 < 0.001 Central SBP (mmHg) 123.60 ± 16.31 107.44 ± 8.25 < 0.001 Central DBP (mmHg) 86.40 ± 12.17 78.04 ± 8.88 < 0.001 ABI 1.08 (0.82–1.35) 1.13 (1.05–1.32) < 0.001 CIMT (mm) 0.90 (0.60–0.90) 0.80 (0.60–0.90) < 0.001 Augmentation index at 75 26.0 (2.0–47.0) 21.0 (2.0–37.0) 0.074 FBS (mg/dl) 158 (74–493) 108 (78–190) < 0.001 2 h BG (mg/dl) 216 (101–558) 140 (72–260) < 0.001 HbA1c 9.16 ± 2.20 6.48 ± 0.49 < 0.001 A/C Ratio 13.2 (1.6–867.8) 9.0 (1.7–25.2) 0.001 eGFR (mL/min/1.73 m 2 ) 93.0 (31.0-119.5) 99.0 (90.0-108.0) 0.005 LDL (mg/dl) 104.12 ± 38.53 98.76 ± 38.45 0.488 HDL (mg/dl) 43.86 ± 11.42 43.40 ± 10.84 0.896 Triglyceride (mg/dl) 148 (62.0-759.0) 110 (44.0-421.0) < 0.001 Cholesterol (mg/dl) 179.84 ± 45.72 158.98 ± 42.31 0.011 SBP: systolic blood pressure; DBP: diastolic blood pressure; ABI: ankle-brachial index; CIMT: carotid intima-media thickness; FBS : fasting blood glucose; A/C ratio: Albumin/Creatinine Ratio; eGFR: estimated glomerular filtration rate; LDL: low density lipoprotein; HDL: high density lipoprotein. Values are presented as Mean ± SD or Median (Range) as appropriate P-values in bold indicate statistical significance (P < 0.05) Table (3) Comparison of Clinical and Laboratory Parameters between patients with and without macrovascular complications Variables With macro-vascular complications, n = 19 Without macro-vascular complications, n = 81 P value Age (years) 50.89 ± 5.91 50.91 ± 6.33 0.991 Gender (%) 0.432 • Male 5 (26.3%) 29 (35.8%) • Female 14 (73.7%) 52 (64.2%) Cigarette smoking (%) 5 (26.3%) 14 (17.3%) 0.350 Body mass index (kg/m 2 ) 38.8 (29.3–51.6) 31.2 (19.3–58.6) < 0.001 Diabetes mellitus duration (years) 10.0 (1.0–25.0) 2.5 (0.04-20.0) < 0.001 Peripheral SBP (mmHg) 146.37 ± 15.88 119.51 ± 11.33 < 0.001 Peripheral DBP (mmHg) 91.63 ± 12.23 78.10 ± 9.18 < 0.001 Mean peripheral BP (mmHg) 109.84 ± 12.35 92.44 ± 9.46 < 0.001 Central SBP (mmHg) 136.58 ± 14.67 110.58 ± 10.38 < 0.001 Central DBP (mmHg) 93.84 ± 12.66 79.49 ± 9.23 < 0.001 ABI 1.08 (0.82–1.13) 1.12 (1.01–1.35) 0.002 CIMT (mm) 0.90 (0.70–0.90) 0.80 (0.60–0.90) < 0.001 Augmentation index at 75 32.79 ± 6.86 20.20 ± 9.11 < 0.001 FBS (mg/dl) 148 (74–493) 116 (78–482) 0.006 2 h BG (mg/dl) 213 (12 − 540) 155 (72–558) 0.001 HbA1c 9.31 ± 2.61 7.47 ± 1.78 0.001 A/C Ratio 13.1 (1.6–125.6) 10.0 (1.7–867.8) 0.102 eGFR (mL/min/1.73 m 2 ) 98.0 (31.0-112.0) 98.0 (54.0-119.5) 0.384 LDL (mg/dl) 124.62 ± 33.23 96.00 ± 37.66 0.003 HDL (mg/dl) 37.89 ± 9.72 44.98 ± 11.00 0.006 Triglyceride (mg/dl) 157.0 (80.0-241.0) 119.0 (44.0-759.0) 0.010 Cholesterol (mg/dl) 173.68 ± 45.01 168.41 ± 45.30 0.650 Received anti-hypertensive medication (%) • Beta blocker 10 (52.6%) 20 (24.7%) 0.017 • Diuretics 7 (36.8%) 30 (37.0%) 0.987 • ACE inhibitors 7 (36.8%) 26 (32.1%) 0.692 • CCB 1 (5.3%) 23 (28.4%) 0.038 • ARBS 6 (31.6%) 20 (24.7%) 0.567 Anti-diabetic medications (%) < 0.001 • Oral hypoglycemic agents 5 (26.3%) 66 (81.5%) • Insulin 14 (73.7%) 15 (18.5%) SBP : systolic blood pressure; DBP : diastolic blood pressure; ABI : ankle-brachial index; CIMT : carotid intima-media thickness; FBS : fasting blood glucose; A/C ratio : Albumin/Creatinine Ratio; eGFR : estimated glomerular filtration rate; LDL : low density lipoprotein; HDL : high density lipoprotein. ACEI : angiotensin-converting enzyme inhibitors; CCBs : Calcium channel blockers; ARBS : Angiotensin receptor blockers. Values are presented as Mean ± SD or Median (Range) as appropriate. P-values in bold indicate statistical significance (P < 0.05) Table (4) Comparison of Clinical and Laboratory Parameters between patients with and without microvascular complication Variables With micro-vascular complications, n = 46 Without micro-vascular complications, n = 54 P value Age (years) 52.04 ± 5.58 49.94 ± 6.63 0.093 Gender (%) 0.123 • Male 12 (26.1%) 22 (40.7%) • Female 34 (73.9%) 32 (59.3%) Cigarette smoking (%) 12 (26.1%) 7 (13.0%) 0.095 Body mass index (kg/m 2 ) 33.4 (20.7–58.6) 30.9 (19.3–48.5) 0.011 DM disease duration (years) 7.5 (0.04-25.0) 2.0 (0.04-10.0) < 0.001 Peripheral SBP (mmHg) 132.04 ± 17.19 118.28 ± 12.22 < 0.001 Peripheral DBP (mmHg) 83.46 ± 11.35 78.30 ± 10.46 0.020 Mean peripheral BP (mmHg) 100.59 ± 12.48 91.63 ± 10.25 < 0.001 Central SBP (mmHg) 122.22 ± 16.18 109.81 ± 11.73 < 0.001 Central DBP (mmHg) 85.22 ± 11.76 79.67 ± 10.53 0.014 ABI 1.08 (1.01–1.35) 1.13 (0.82–1.32) < 0.001 CIMT (mm) 0.90 (0.60–0.90) 0.80 (0.60–0.90) 0.003 Augmentation index 75 24.15 ± 11.46 21.26 ± 8.48 0.151 FBS (mg/dl)) 158 (74–493) 109 (78–190) < 0.001 2 h BG (mg/dl) 215 (101–558) 147 (72–260) < 0.001 HbA1c 9.30 ± 2.21 6.56 ± 0.63 < 0.001 A/C Ratio 13.2 (1.6–876.8) 9.6 (1.7–25.2) 0.004 EGFR (mL/min/1.73 m 2 ) 93.0 (31.0-119.0) 99.0 (83.0–108.0) 0.008 LDL (mg/dl) 102.42 ± 39.11 100.60 ± 38.13 0.814 HDL (mg/dl) 44.67 ± 11.46 42.74 ± 10.77 0.359 Triglyceride (mg/dl) 142.0 (62.0-759.0) 112.0 (44.0-421.0) 0.002 Cholesterol (mg/dl) 178.04 ± 46.43 162.06 ± 42.93 0.077 Received anti-hypertensive medication • Beta blocker 17 (37.0%) 13 (24.1%) 0.161 • Diuretics 16 (34.8%) 21 (38.9%) 0.672 • ACEI 15 (32.6%) 18 (33.3%) 0.939 • CCB 8 (17.4%) 16 (29.6%) 0.153 • ARBS 15 (32.6%) 11 (20.4%) 0.164 Anti-diabetic medications < 0.001 • Oral hypoglycemic agents 21 (45.7%) 50 (92.6%) • Insulin 25 (54.3%) 4 (7.4%) SBP : systolic blood pressure; DBP : diastolic blood pressure; ABI : ankle-brachial index; CIMT : carotid intima-media thickness; FBS : fasting blood glucose; A/C ratio : Albumin/Creatinine Ratio; eGFR : estimated glomerular filtration rate; LDL : low density lipoprotein; HDL : high density lipoprotein. ACEI : angiotensin-converting enzyme inhibitors; CCBs : Calcium channel blockers; ARBS : Angiotensin receptor blockers. Values are presented as Mean ± SD or Median (Range) as appropriate P-values in bold indicate statistical significance (P < 0.05) Table (5) Multivariable Logistic Regression Analysis of Independent Predictors for Macrovascular Complications B S.E. Wald df Sig. Exp(B) 95% C.I. for EXP(B) Lower Upper Body mass index 0.001 0.038 0.000 1 0.985 1.001 0.928 1.079 Duration of DM 0.192 0.050 14.671 1 < 0.001 1.212 1.098 1.337 Peripheral SBP 0.143 0.031 20.599 1 < 0.001 1.154 1.085 1.227 Central SBP 0.168 0.038 19.187 1 < 0.001 1.183 1.097 1.275 ABI -17.290 5.944 8.462 1 0.004 0.000 NA NA CIMT 27.894 7.601 13.467 1 < 0.001 0.000 NA NA AIx@75 0.187 0.046 16.771 1 < 0.001 1.205 1.102 1.318 FBG 0.008 0.003 7.658 1 0.006 1.008 1.002 1.014 HBA1c 0.362 0.114 10.102 1 0.001 1.436 1.149 1.796 LDL 0.020 0.007 7.702 1 0.006 1.021 1.006 1.035 DM : diabetes mellitus; SBP : systolic blood pressure; DBP : diastolic blood pressure; ABI : ankle-brachial index; CIMT : carotid intima-media thickness; FBS : fasting blood glucose; LDL : low density lipoprotein. P-values in bold indicate statistical significance (P < 0.05) Table (6) Multivariable Logistic Regression Analysis of Independent Predictors for Microvascular Complications B S.E. Wald Df Sig. Exp (B) 95% C.I. for EXP(B) Lower Upper Age (years) 0.056 0.033 2.801 1 0.094 1.057 0.990 1.129 Smoking 0.863 0.526 2.689 1 0.101 2.370 0.845 6.647 Body mass index 0.083 0.035 5.755 1 0.016 1.087 1.015 1.164 Duration of DM 0.285 0.067 18.301 1 < 0.001 1.330 1.167 1.515 Peripheral SBP 0.063 0.016 15.192 1 < 0.001 1.065 1.032 1.099 Central SBP 0.062 0.017 14.263 1 < 0.001 1.064 1.030 1.099 ABI -12.720 4.053 9.847 1 0.002 0.000 NA NA CIMT 6.541 2.440 7.188 1 0.007 693.295 5.810 82734.158 FBG 0.025 0.007 13.758 1 < 0.001 1.025 1.012 1.038 HBA1c 2.297 0.474 23.437 1 < 0.001 9.944 3.924 25.200 A/CRatio 0.055 0.021 6.934 1 0.008 1.056 1.014 1.100 eGFR -0.061 0.018 11.766 1 0.001 0.941 0.909 0.974 Triglyceride 0.008 0.004 5.114 1 0.024 1.008 1.001 1.015 SBP : systolic blood pressure; DBP : diastolic blood pressure; ABI : ankle-brachial index; CIMT : carotid intima-media thickness; FBS : fasting blood glucose; A/C ratio : Albumin/Creatinine Ratio; eGFR : estimated glomerular filtration rate. P-values in bold indicate statistical significance (P < 0.05) Discussion There is a paucity of data that examined the predictive importance of central BP in diabetic hypertensive Egyptians. The current study revealed that peripheral and central systolic and diastolic BP, average peripheral BP, and CIMT were significantly higher, while ABI was significantly lower in complicated T2DM hypertensive patients (those with either micro- or macrovascular complications) compared to those without complications (P value < 0.05). This is consistent with the cross-sectional study of Yang et al. which aimed to evaluate association of CBP and CVD in diabetic hypertensive patients. The study included 360 patients. Furthermore, author reported that patients with CVD had significantly greater central SBP and AIx@75 than those without CVD. Age, male gender, and the occurrence of coronary heart disease and ischemic stroke were linked with higher AIx@75, whereas renin-angiotensin-axis inhibitors were associated with lower AIx@75 levels. After controlling for established risk factors such as brachial SBP, both central SBP and AIx@75 remained substantially linked with CVD, with odds ratios and 95% confidence intervals of 1.09 (1.08–1.31) and 1.20 (1.15–1.42, respectively) [ 14 ]. While, in the current study; Aix@75 was significantly higher among T2DM hypertensive patients with macrovascular complications (P value < 0.001), not those with microvascular complications. This finding could be contributed to the fact that the elevated arterial stiffness increases the development of CVD in hypertensive patients and normal subjects [ 19 ]. Also, in consistent with the present investigation, 11 longitudinal studies including 5648 participants followed for an average of forty-five months were examined by Vlachopoulos et al. Author reported an absolute rise of 10% in the central augmentation index was associated with a 31.8% and 38.4% relative risk increase for CVD and all-cause mortality, respectively, after controlling for CV risk variables, which included brachial BP and history of hypertension in five trials [ 21 ]. Another interesting finding in the current study is that T2DM hypertensive patients with complications (micro- or macrovascular complications) had significantly higher cIMT compared to those without complications (P value < 0.05). Thus, our findings enforce the growing body of research establishing that cIMT as a noninvasive surrogate marker for vascular disease. This finding was supported by the studies of Miyamoto et al. and Talpur et al. which aimed to evaluate the relationship between diabetic retinopathy (DR) and CIMT, and observed that CIMT was more in patients with DR [ 22 , 23 ]. Additionally, the recent systematic review and meta-analysis of Liao et al. support the current finding as authors observed associations between increased common carotid artery intima-media thickness (CCA-IMT) and the risk of diabetic micro and macro-vascular complications [ 24 ]. However, further larger studies are needed to determine the role of cIMT as a noninvasive surrogate marker for predicting the development of vascular complications among T2DM hypertensive patients. Additionally, in the current study, T2DM hypertensive patients with complications (micro- or macrovascular complications) had significantly lower ABI compared to those without complications (P value < 0.05). In line with the current study, a recent study of Amelia et al. which was aimed to using ABI as a non-invasive marker for predicting macrovascular complications among 89 patients with T2DM. The study discovered a link between LDL-C, triglycerides, and vitamin D (25OH-D) based on the ABI classification (p > 0.05). Based on this finding authors concluded that ABI could be for early detection of macrovascular complications among T2DM patients [ 25 ]. Generally, regarding to the metabolic parameters of the studied cases, it was found that those with either micro- or macrovascular complications had significantly higher fasting blood glucose, 2h blood glucose, HbA1c (p value < 0.05). This finding comes in concordance with previous studies [ 26 , 27 ]. Furthermore, Au Yeung et al. study which aimed to determine the relation between HbA~1c ~ and CVD, revealed that HbA~1c ~ was associated with increased coronary artery disease (CAD) risk (OR:1.50 per %, and 95% CI:1.08–2.11). Thus, HbA1c is likely to be the cause of CAD. However, the underlying mechanisms have yet to be fully understood [ 28 ]. Another study by El Toony et al. reported a link between fasting blood glucose level, HbA1c and developing CAD [ 12 ]. Unique finding for patients with macrovascular complications is that those patients had significantly higher LDL, and triglycerides levels, and significantly lower HDL, and comparable level of total cholesterol levels, A/C ratio, and eGFR compared to those without macrovascular complications (P value < 0.05). While, the unique finding for patients with microvascular complications is that those patients had significantly higher triglycerides levels, and A/C ratio, and significantly lower eGFR, and comparable level of LDL, HDL, and total cholesterol levels compared to those without microvascular complications (P value < 0.05). Thus, the current finding revealed that dyslipidaemia is a common finding in T2DM hypertensive patients with complication; however, it is more prevalent among those with macrovascular complications. The elevated TC, LDL-C, TAG, and low HDL-C levels observed in T2DM hypertensive individuals with complications were comparable to previously documented trends [ 29 , 30 ]. Also, LDL and triglycerides were consistently positively correlated with cardiovascular mortality, according to Silbernagel et al. [ 31 ]. This is not a surprising result since dyslipidemia is recognized to be a substantial risk factor that greatly contributes to the development of micro- and macrovascular complications in patients with T2DM patients. In fact, hyperlipidaemia (high LDL-C, triglycerides) is known to increase the risk for macrovascular diseases. It is thought to accelerate the development of atherosclerosis particularly when diabetes mellitus comorbid by hypertension as T2DM hypertensive patients have a higher risk of developing CAD [ 30 ]. While, renal dysfunction "defined by higher A/C ratio, and lower eGFR" is more prevalent among the studied T2DM hypertensive patients with microvascular complications. This finding contributed to the high prevalence of nephropathy observed in the current study (28.0% of the studied cases suffered from nephropathy). As chronic kidney disease is one of the major complications in T2DM patients. UACR and eGFR were two commonly used indicators to assess renal function, according to previous literature; these two biomarkers (eGFR and albuminuria) are independent predictors for progression to end-stage renal disease [ 32 , 33 , 34 ]. In concordance to the current study, Sabanayagam et al. reported that microvascular complications in T2DM patients was positively associated with both micro and macroalbuminuria and eGFR [ 35 ]. Additionally, studies had shown that eGFR and albuminuria were also predictors of CVD and mortality [ 36 , 37 ]. To assess the independent predictors of the development of macrovascular complications in diabetic hypertensive patients, logistic regression analysis was used and revealed that longer disease duration, higher peripheral & central SBP, Aix@75, higher fasting BG, HBA1c, and higher LDL were significantly associated with the occurrence of macrovascular complications in T2DM hypertensive patients. Also, higher BMI, longer disease duration, higher peripheral & central SBP, Aix@75, CIMT, higher fasting BG, HBA1c, higher A/C ratio, higher triglyceride level, and lower eGFR were significantly associated with the occurrence of microvascular complications in T2DM hypertensive patients. The main finding in the current finding is that peripheral & central SBP have more or less equivalent predictive ability for prediction of either micro- or macrovascular complications in T2DM hypertensive patients, however, central SBP had slightly higher prediction of macrovascular complications as evident by the values of logistic regression analysis (OR = 1.183, 95%CI = 1.097–1.275, P < 0.001) for central SBP compared to (OR = 1.154, 95%CI = 1.085–1.227, P < 0.001) for peripheral SBP, while peripheral SBP had slightly higher prediction of microvascular complications in T2DM hypertensive patients (OR = 1.065, 95%CI = 1.032–1.099, P < 0.001) compared to (OR = 1.064, 95%CI = 1.030–1.099, P < 0.001) for central SBP. Thus, this finding is not clearly evident may be because of small sample size; particularly because of the lower prevalence of macrovascular complications in the current study which was only documented in 19.0%. This finding highlights the need for further larger studies to confirm the role of central BP as a powerful predictor for macrovascular complication in T2DM hypertensive patients. Nowadays, physicians can take the value of central BP using the non-invasive equipment, which may help to prove the role of central BP in minimizing T2DM macrovascular complications. Jung et al. study which aimed to study the association between central and peripheral BP and microvascular complications in 201 T2DM patients. Author revealed consistent finding to the current study as author stated that central and brachial BP were strongly correlated (correlation coefficients between central and brachial SBP and PP are 0.889 and 0.816, respectively). However, the higher brachial BP levels are associated with increased probability for microvascular complications more than central BP in relation to diabetic nephropathy (DN) and diabetic retinopathy (DR). While, central BP level considered as surrogate marker of macrovascular complications more than brachial BP [ 38 ]. Furthermore, many previous clinical trials revealed that patients with high central BP had considerably higher cardiovascular risk than those with low central BP, even when their peripheral BP was equal [ 10 , 13 ], suggesting that central BP could be an independent predictor for CVD [ 39 , 40 ]. On the other hand, Mitchell et al.'s study aimed to investigate how wave velocity, central pulse pressure, and augmentation index might be used to predict cardiovascular risk. The Framingham Heart Study found no correlation between CVD outcomes and the augmentation index, central pulse pressure, or pulse pressure amplification in multivariable models [ 41 ]. Conclusions This work clearly identified that peripheral and central SBP have more or less equivalent predictive ability for prediction of either micro- or macro-vascular complications in T2DM hypertensive patients, however, central SBP had slightly higher prediction of macro-vascular complications, while peripheral SBP had slightly higher prediction of micro-vascular complications in T2DM hypertensive patients, as evident by the values of logistic regression analysis. In addition, augmentation index was significantly associated with the occurrence of macro-vascular complications among T2DM hypertensive patients but not micro-vascular complications. Abbreviations T2DM Type 2 Diabetes Mellitus BP Blood Pressure SBP Systolic Blood Pressure DBP Diastolic Blood Pressure CVD Cardiovascular Disease CIMT Carotid Intima-Media Thickness ABI Ankle-Brachial Index AIx@75 Augmentation Index standardized to a heart rate of 75 bpm HbA1c Glycated Hemoglobin eGFR estimated Glomerular Filtration Rate A/C ratio Albumin/Creatinine Ratio LDL Low-Density Lipoprotein HDL High-Density Lipoprotein ACEI Angiotensin-Converting Enzyme Inhibitors ARBS Angiotensin Receptor Blockers CCBs Calcium Channel Blockers OR Odds Ratio CI Confidence Interval SD Standard Deviation Declarations Ethics approval and consent to participate The study protocol was approved by the Institutional Review Board of the Faculty of Medicine, Ain Shams University (approval number: FAMSU md 193/2022, date of approval: 18 October 2022). The research was conducted in accordance with the principles outlined in the Declaration of Helsinki. Written informed consent was obtained from all individual participants included in the study. Consent for publication Not applicable. This manuscript does not contain any individual person's data in any form (e.g., individual details, images, or videos). Availability of data and materials The datasets generated and/or analyzed during the current study are not publicly available due to privacy and ethical restrictions but are available from the corresponding author on reasonable request. Competing Interests The authors declare that they have no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors' contributions SSH, MMAS, and HAA contributed to the study conception and design. Material preparation, data collection, and analysis were performed by EEG, MNN, and AMMAEHS. The first draft of the manuscript was written by AMMAEHS and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript Clinical Trial Number: Not applicable. HUMAN AND ANIMAL RIGHTS: No animals were used in this study. All the procedures performed in this study involving human participants were in accordance with the ethical standards of the Institutional Research Committee and the 1975 Declaration of Helsinki as revised in 2013. References Sinha S, Haque M. Insulin Resistance Is Cheerfully Hitched with Hypertension. Life. 2022;12(4):564. Hegazi R, El-Gamal M, Abdel-Hady N, Hamdy O. Epidemiology of and risk factors for type 2 diabetes in Egypt. Annals Global Health. 2015;81(6):814–20. El Faramawy A, Youssef G, El Aroussy W, El Remisy D, Deeb E, Aal HA, A., Ibrahim MM. Registry of the Egyptian specialized hypertension clinics: patient risk profiles and geographical differences. J Hum Hypertens. 2020;34(7):520–7. 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Insight into blood pressure targets for universal coverage of hypertension services in Iran: the 2017 ACC/AHA versus JNC 8 hypertension guidelines. BMC Public Health. 2020;20(1):347. Abouhamda A, Alturkstani M, Jan Y. Lower sensitivity of ankle-brachial index measurements among people suffering with diabetes-associated vascular disorders: A systematic review. SAGE Open Med. 2019;7:2050312119835038. Sánchez R, Pessana F, Lev G, Mirada M, Mendiz O, Ramírez A, Fischer EC. Central blood pressure waves assessment: a validation study of non-invasive aortic pressure measurement in human beings. High Blood Press Cardiovasc Prev. 2020;27(2):165–74. Wakabayashi I. Homocysteine levels and arterial stiffness in the general population. J Atheroscler Thromb. 2016;23(6):668–70. Miller WG, Kaufman HW, Levey AS, Straseski JA, Wilhelms KW, Yu HY, Klutts JS, Hilborne LH, Horowitz GL, Lieske J, Ennis JL, Bowling JL, Lewis MJ, Montgomery E, Vassalotti JA, Inker LA. National Kidney Foundation Laboratory Engagement Working Group Recommendations for Implementing the CKD-EPI 2021 Race-Free Equations for Estimated Glomerular Filtration Rate: Practical Guidance for Clinical Laboratories. Clin Chem. 2021;68(4):511–20. Vlachopoulos C, Aznaouridis K, O'Rourke MF, Safar ME, Baou K, Stefanadis C. Prediction of cardiovascular events and all-cause mortality with central haemodynamics: a systematic review and meta-analysis. Eur Heart J. 2010;31(15):1865–71. Miyamoto M, Kotani K, Okada K, Fujii Y, Konno K, Ishibashi S, Taniguchi N. The correlation of common carotid arterial diameter with atherosclerosis and diabetic retinopathy in patients with type 2 diabetes mellitus. Acta Diabetol. 2012;49(1):63–8. Talpur AS, Amar Z, Zafar S, Memon A, Latif AHE, Hafizyar F, Hashim S, Nazary K. (2021). Association between diabetic retinopathy and carotid intima-media thickness. Cureus, 13(6), e15507. Liao M, Chen S, Guo R. (2023). Association between carotid ultrasonographic parameters and microvascular and macrovascular complications in diabetes: A systematic review and meta-analysis. J Diabetes Complicat, 108554. Amelia R, Harahap J, Yunanda Y, Wijaya H, Fujiati II, Yamamoto Z. Early detection of macrovascular complications in type 2 diabetes mellitus in Medan, North Sumatera, Indonesia: A cross-sectional study. F1000Research. 2021;10:742. Sherwani SI, Khan HA, Ekhzaimy A, Masood A, Sakharkar MK. Significance of HbA1c test in diagnosis and prognosis of diabetic patients. Biomark Insights. 2016;11:95–104. Mohammad P, Khan EH. Unnoticed microalbuminuria is substantially prevalent in patients of type-2 diabetes mellitus in Peshawar. J Saidu Med Coll Swat. 2019;9(1):18–22. Au Yeung SL, Luo S, Schooling CM. The impact of glycated hemoglobin (HbA1c) on cardiovascular disease risk: a Mendelian randomization study using UK Biobank. Diabetes Care. 2018;41(9):1991–7. Eghan B, Acheampong JW. Dyslipidemia in outpatients at General Hospital in Kumasi, Ghana: cross-sectional study. Croatian Med J. 2003;44(5):576–8. Adinortey MB, Gyan BE, Adjimani J, Nyarko P, Sarpong C, Tsikata FY, Nyarko AK. Dyslipidaemia associated with type 2 diabetics with micro and macrovascular complications among Ghanaians. Indian J Clin Biochem. 2011;26:261–8. Silbernagel G, Scharnagl H, Kleber ME, Delgado G, Stojakovic T, Laaksonen R, Erdmann J, Rankinen T, Bouchard C, Landmesser U. LDL triglycerides, hepatic lipase activity, and coronary artery disease: An epidemiologic and Mendelian randomization study. Atherosclerosis. 2019;282:37–44. Amin AP, Whaley-Connell AT, Li S, Chen S-C, McCullough PA, Kosiborod MN, Investigators K. The synergistic relationship between estimated GFR and microalbuminuria in predicting long-term progression to ESRD or death in patients with diabetes: results from the Kidney Early Evaluation Program (KEEP). Am J Kidney Dis. 2013;61(4):S12–23. Fung CSC, Wan EYF, Chan AKC, Lam CLK. Association of estimated glomerular filtration rate and urine albumin-to-creatinine ratio with incidence of cardiovascular diseases and mortality in Chinese patients with type 2 diabetes mellitus–a population-based retrospective cohort study. BMC Nephrol. 2017;18(1):188. Asghar S, Asghar S, Mahmood T, Bukhari SMH, Mumtaz MH, Rasheed A. (2023). Microalbuminuria as the Tip of Iceberg in Type 2 Diabetes Mellitus: Prevalence, Risk Factors, and Associated Diabetic Complications. Cureus, 15(8), e43879. Sabanayagam C, Shankar A, Koh D, Chia KS, Saw SM, Lim SC, Tai ES, Wong TY. Retinal microvascular caliber and chronic kidney disease in an Asian population. Am J Epidemiol. 2009;169(5):625–32. Wang Y, Katzmarzyk PT, Horswell R, Zhao W, Johnson J, Hu G. Kidney function and the risk of cardiovascular disease in patients with type 2 diabetes. Kidney Int. 2014;85(5):1192–9. Soriano LC, Johansson S, Stefansson B, Rodríguez LAG. Cardiovascular events and all-cause mortality in a cohort of 57,946 patients with type 2 diabetes: associations with renal function and cardiovascular risk factors. Cardiovasc Diabetol. 2015;14:38. Jung C-H, Jung S-H, Kim K-J, Kim B-Y, Kim C-H, Kang S-K, Mok J-O. Differential associations of central and brachial blood pressure with carotid atherosclerosis and microvascular complications in patients with type 2 diabetes. BMC Cardiovasc Disord. 2014;14(1):23. Lukich E, Matas Z, Boaz M, Shargorodsky M. Increasing derangement of glucose homeostasis is associated with increased arterial stiffness in patients with diabetes, impaired fasting glucose and normal controls. Diab/Metab Res Rev. 2010;26(5):365–70. Ben-Shlomo Y, Spears M, Boustred C, May M, Anderson SG, Benjamin EJ, Boutouyrie P, Cameron J, Chen C-H, Cruickshank JK. Aortic pulse wave velocity improves cardiovascular event prediction: an individual participant meta-analysis of prospective observational data from 17,635 subjects. J Am Coll Cardiol. 2014;63(7):636–46. Mitchell GF, Hwang S-J, Vasan RS, Larson MG, Pencina MJ, Hamburg NM, Vita JA, Levy D, Benjamin EJ. Arterial stiffness and cardiovascular events: the Framingham Heart Study. Circulation. 2010;121(4):505–11. 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-8811000","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":599140635,"identity":"b68064ee-674d-47c5-b3b5-4c808aece2f7","order_by":0,"name":"Salwa Seddik Hosni","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Salwa","middleName":"Seddik","lastName":"Hosni","suffix":""},{"id":599140637,"identity":"7d29f4b8-d056-4aa0-b7bf-f4da7d8f2b8a","order_by":1,"name":"Mona Mohamed Abdel Salam","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Mona","middleName":"Mohamed Abdel","lastName":"Salam","suffix":""},{"id":599140639,"identity":"43348202-7f92-4308-a6de-593de503f884","order_by":2,"name":"Hoda Adel Afifi","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Hoda","middleName":"Adel","lastName":"Afifi","suffix":""},{"id":599140642,"identity":"f836fccf-af87-41a1-bbdd-ae64c6faa58d","order_by":3,"name":"Engy Eshak Gedy","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Engy","middleName":"Eshak","lastName":"Gedy","suffix":""},{"id":599140643,"identity":"d1bf3e1d-b4df-4949-b65c-9f2a7ba89643","order_by":4,"name":"Mina Michaeil Nesim","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Mina","middleName":"Michaeil","lastName":"Nesim","suffix":""},{"id":599140645,"identity":"7d9bb94a-feba-475e-9a40-5ae1c2deec99","order_by":5,"name":"Amr Mahmoud Mohamed Abd El Hady Saleh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYNCCAoYEfiAlAeUaEKHFgCFBsoFkLQYHiNXCP+3s4w8/DGzyjK8dPniDoaYusYG9eZsEQ0UtTi0St9PNJHsM0orNbqclWzAcO5zYwHOsTILhzHHc1txOY2PgMTicuO12jpkEA9uBxAYJIIOx7RhOHfK305g//jH4n7h5dv43CYZ/QIfJvwFq+Ydbi8HtNAZpHoMDiRukc9iAhjMDbeEBammowanFEOgwaRmD5MQZt9OMLRL7Dhu38aQVWyQcO4BTixzIYW8q7BL7Zyc/vPHhW51sP/vhjTc+1NTh9j4KSABiNgjjMJFakACxtoyCUTAKRsEIAABCYVPtZwlfSgAAAABJRU5ErkJggg==","orcid":"","institution":"Ain Shams University","correspondingAuthor":true,"prefix":"","firstName":"Amr","middleName":"Mahmoud Mohamed Abd El Hady","lastName":"Saleh","suffix":""}],"badges":[],"createdAt":"2026-02-06 22:08:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8811000/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8811000/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104175672,"identity":"08cf53c0-1075-41f6-944b-0377148424fd","added_by":"auto","created_at":"2026-03-08 16:31:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":25819,"visible":true,"origin":"","legend":"\u003cp\u003eThe distribution of complications among cases\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8811000/v1/6c39fa7039a279cfe34e10ff.png"},{"id":104404933,"identity":"189b86c4-5efb-4dad-bb28-95f11e3dc8cc","added_by":"auto","created_at":"2026-03-11 12:21:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2152983,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8811000/v1/8b6f1f27-067a-44cf-acf2-3d986f1b44fa.pdf"},{"id":104175671,"identity":"dd0e529c-7b0c-44d1-be5a-91603cdae6fc","added_by":"auto","created_at":"2026-03-08 16:31:32","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":37938,"visible":true,"origin":"","legend":"","description":"","filename":"rawdatacbp.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8811000/v1/e5ed7f0043a4c68d4161d551.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Central Blood Pressure Association with Micro- and Macro-vascular Complications in A sample of type 2 Diabetic Patients: A Case-Control Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eUncontrolled blood pressure (BP) in diabetic hypertensive patients is associated with an increased risk of morbidity and mortality from cardiovascular illnesses. It is a crucial step for treating diabetic patients since it is one of the best methods to avoid microvascular, macrovascular, and fatal consequences [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to Hegazi et al., about 15.6% of all adults in Egypt between the ages of 20 and 79 have type 2 diabetes (T2DM) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Additionally, the 2017 WHO stepwise survey in Egypt reported that the prevalence of hypertension has been increasing, estimated to be 29.5% [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eType 2 diabetes and hypertension are known to be prevalent comorbidities [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], as numerous previous studies demonstrate that diabetic patients were approximately twice more likely to develop hypertension compared to patients without the disease, which contributes to the high prevalence of cardiovascular disease (CVD) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDiabetes and hypertension are intimately related as both share a number of risk factors, such as endothelial cell dysfunction, arterial remodeling, vascular inflammation, dyslipidemia, and obesity [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Additionally, there is a significant overlap between the cardiovascular consequences of both diabetes and hypertension, which are predominantly driven by micro- and macrovascular disorders [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNumerous randomized controlled trials and meta-analyses involving antihypertensive medications demonstrate that reducing peripheral blood pressure improves cardiovascular and renal outcomes [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Some observational studies have suggested that the peripheral BP measured in the brachial artery may not accurately reflect the central BP, which is measured in the aortic artery [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStrokes and heart attacks aren't brought on by high BP in the arm (brachial) artery; instead, it's high BP in the central arteries that have direct contact with the brain and the heart [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Many randomized studies and meta-analyses show that even with the same peripheral BP, patients with high central BP had a statistically significant increased risk of cardiovascular disease than those with low central BP [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. It has been determined that central BP could serve as an independent predictor of cardiovascular disease [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe predictive importance of central blood pressure in patients with diabetes mellitus has not been thoroughly examined in many studies. Thus, the goal of the current case-control study was to assess the relationship between central BP and micro- and macrovascular complications in T2DM hypertensive patients.\u003c/p\u003e"},{"header":"Patients and Methods","content":" \u003cp\u003eThis case-control study compared patients with type 2 diabetes mellitus (T2DM) and newly diagnosed hypertension who had overt vascular complications (cases) with those without vascular complications (controls). To further explore specific vascular complications, all patients (cases and controls; N\u0026thinsp;=\u0026thinsp;100) were stratified into subgroups based on the presence or absence of macrovascular and microvascular complications. Participants were recruited from the internal medicine and diabetes wards, as well as the outpatient clinics of Nasser Institute and Ain Shams University Hospitals, between September 2022 and July 2023. The study was approved by the regional ethics committee at Ain Shams University (IRB No: .......) and informed consent was obtained from all participants.\u003c/p\u003e \u003cp\u003eEligibility We included patients with T2DM with newly diagnosed hypertension with age ranging from 40 to 60 years. We excluded patients with cardiac or cerebrovascular events in the last 6 months, patients with chronic kidney disease and endocrine conditions causing secondary hypertension. We also excluded patients currently receiving sex hormones, lithium, digoxin or non-depolarizing skeletal muscle relaxants and pregnant or breast-feeding women.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample size\u003c/h2\u003e \u003cp\u003eSample size calculation was performed using G*Power 3 software [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Setting the power at 80% and the alpha error at 0.05, a total sample size of 100 was determined, with 50 patients in each group. This sample size was sufficient to detect a medium effect size difference (d\u0026thinsp;=\u0026thinsp;0.5) regarding central blood pressure.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eA questionnaire was used to collect information on patients' age, sex, smoking status, and the duration of diabetes mellitus and hypertension (not presented in tables). The questionnaire also included details on the history of micro- or macrovascular complications (cerebrovascular disease, peripheral vascular disease, ischemic heart disease, retinopathy, nephropathy, and neuropathy), past medical history, and current medication use. Anthropometric data, including height, weight, and body mass index (BMI), were also recorded. Each patient underwent a systemic examination, which included assessments of the neurological, chest, abdominal, and cardiovascular systems.\u003c/p\u003e \u003cp\u003ePeripheral blood pressure (BP), including brachial BP and ankle-brachial index (ABI), along with heart rate at rest, were measured. Peripheral BP was recorded at the brachial artery and at the posterior tibial and dorsalis pedis arteries for ABI calculation. BP was measured according to the JNC8 guidelines, with patients seated quietly for 10 minutes, and three readings were taken with a one-minute interval. The final two readings were averaged to calculate the mean brachial BP [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Systolic pressure from the posterior tibial or dorsalis pedis arteries was measured using the same technique on the lower limbs [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCentral blood pressure was measured using the Mobil-O-Graph device [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], which uses a brachial-based cuff to obtain central pressure curves processed via a transfer function. Central systolic and diastolic BP, as well as the augmentation index adjusted for a heart rate of 75 beats per minute (AIx@75), were recorded as indicators of arterial stiffness [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVenous blood samples were obtained for a fasting lipid profile, fasting plasma glucose, 2-hour plasma glucose, glycated hemoglobin (HbA1c), and serum creatinine. Estimated glomerular filtration rate (eGFR) was calculated using the National Kidney Foundation equation [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and the Albumin/Creatinine Ratio (A/C ratio) was measured. Additional assessments included fundus examination, echocardiography, carotid duplex, and carotid intima-media thickness (cIMT).\u003c/p\u003e\n\u003ch3\u003eData Management and Statistical Analysis:\u003c/h3\u003e\n\u003cp\u003eData was collected, coded, and entered into SPSS (Statistical Package for the Social Sciences, SPSS Inc., Chicago, IL, USA), version 22. Qualitative data were described using frequencies and percentages, and comparisons were made using Fisher's Exact and Chi-square (χ\u0026sup2;) tests. Quantitative data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or median (range), depending on the distribution of the data. Comparisons between groups were made using the student's t-test and ANOVA for normally distributed data, or the Mann-Whitney U test and Kruskal-Wallis test for non-normally distributed data. Odds ratios (OR) with 95% confidence intervals (CI) were calculated, and logistic regression was performed to predict the development of diabetic micro- and macrovascular complications in each subgroup. A P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eBaseline Characteristics\u003c/p\u003e \u003cp\u003eRegarding baseline data, there were no significant differences in gender distribution or age between the two groups. However, cases had significantly higher BMI (P\u0026thinsp;=\u0026thinsp;0.004), smoking rates (P\u0026thinsp;=\u0026thinsp;0.022), and longer duration of diabetes mellitus (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to controls. Additionally, cases had a higher percentage of patients receiving beta blockers (P\u0026thinsp;=\u0026thinsp;0.029) and insulin (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;1). The distribution of complications among cases was presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eComparison of Cases and Controls\u003c/p\u003e \u003cp\u003eCases also had significantly higher peripheral and central systolic and diastolic BP, average peripheral BP, CIMT, and Aix@75, as well as significantly lower ABI compared to controls (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Moreover, cases showed significantly higher fasting blood glucose, 2-hour blood glucose, HbA1c, triglycerides (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), total cholesterol (P\u0026thinsp;=\u0026thinsp;0.011), and A/C ratio (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for each). Additionally, eGFR was significantly lower in cases compared to controls (P\u0026thinsp;=\u0026thinsp;0.005) (Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003ePrevalence of Complications\u003c/p\u003e \u003cp\u003eOut of 100 patients with type 2 diabetes mellitus (DM) and early diagnosed hypertension (HTN) studied, 19% (n\u0026thinsp;=\u0026thinsp;19) had macrovascular complications, and 46% (n\u0026thinsp;=\u0026thinsp;46) had microvascular complications.\u003c/p\u003e \u003cp\u003eMacrovascular Complications\u003c/p\u003e \u003cp\u003eOn comparing patients with and without macrovascular complications, results showed significantly higher BMI, longer diabetes duration, higher peripheral and central systolic and diastolic BP, mean peripheral BP, CIMT, and Aix@75, as well as significantly lower ABI in those with macrovascular complications (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Moreover, these patients showed significantly higher fasting blood glucose (P\u0026thinsp;=\u0026thinsp;0.006), 2-hour blood glucose (P\u0026thinsp;=\u0026thinsp;0.001), HbA1c (P\u0026thinsp;=\u0026thinsp;0.001), LDL (P\u0026thinsp;=\u0026thinsp;0.003), and triglyceride levels (P\u0026thinsp;=\u0026thinsp;0.010), and significantly lower HDL (P\u0026thinsp;=\u0026thinsp;0.006). Additionally, the use of beta-blockers and insulin therapy was significantly higher, while the use of CCBs was significantly lower among patients with macrovascular complications (Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003eMultivariable Logistic Regression Analysis identified longer disease duration, higher peripheral and central SBP, Aix@75, fasting blood glucose, HbA1c, and LDL as significant predictors of macrovascular complications (Table\u0026nbsp;5).\u003c/p\u003e \u003cp\u003eMicrovascular Complications\u003c/p\u003e \u003cp\u003eOn comparing patients with and without microvascular complications, results showed significantly higher BMI, longer diabetes duration, higher peripheral and central systolic and diastolic BP, mean peripheral BP, and CIMT in those with microvascular complications (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, these patients showed significantly higher fasting blood glucose, 2-hour blood glucose, and HbA1c (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for each), as well as significantly higher triglyceride levels (P\u0026thinsp;=\u0026thinsp;0.002). The A/C ratio was significantly higher, and eGFR was significantly lower in patients with microvascular complications compared to those without complications (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Furthermore, insulin therapy was significantly more common in patients with microvascular complications (Table\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eMultivariable Logistic Regression Analysis identified higher BMI, longer disease duration, higher peripheral and central SBP, Aix@75, CIMT, fasting blood glucose, HbA1c, triglyceride levels, A/C ratio, and lower eGFR as significant predictors of microvascular complications (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;6).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTable\u0026nbsp;(1)\u003c/strong\u003e \u003cp\u003eComparison between cases and controls as regards baseline data including their descriptive statistics\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline data\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCases (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003econtrols(n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.86\u0026thinsp;\u0026plusmn;\u0026thinsp;5.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.96\u0026thinsp;\u0026plusmn;\u0026thinsp;6.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (28.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (40.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (72.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (60.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody mass index (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.6 (20.7\u0026ndash;58.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.8 (19.3\u0026ndash;46.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCigarette smoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (28.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of diabetes mellitus (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.5 (1 month\u0026ndash;25 yrs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 (1 month\u0026ndash;10 yrs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReceived medications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnti-hypertensive medication\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Beta blocker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (40.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Diuretics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (36.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (38.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.836\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; ACEI inhibitors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (34.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (32.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.832\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; CCBs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (16.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (32.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; ARBS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnti-diabetic medications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Oral hypoglycemic agents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (42.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Insulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (58.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eACEI\u003c/b\u003e: angiotensin-converting enzyme inhibitors; \u003cb\u003eCCBs\u003c/b\u003e: Calcium channel blockers; \u003cb\u003eARBS\u003c/b\u003e: Angiotensin receptor blockers. P-values in bold indicate statistical significance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTable\u0026nbsp;(2)\u003c/strong\u003e \u003cp\u003eComparison of Clinical and Laboratory Parameters Between Cases and Controls including their descriptive statistics\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCases (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControls (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeripheral SBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133.50\u0026thinsp;\u0026plusmn;\u0026thinsp;17.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115.72\u0026thinsp;\u0026plusmn;\u0026thinsp;8.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeripheral DBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.62\u0026thinsp;\u0026plusmn;\u0026thinsp;11.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.72\u0026thinsp;\u0026plusmn;\u0026thinsp;8.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean peripheral BP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101.78\u0026thinsp;\u0026plusmn;\u0026thinsp;12.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.72\u0026thinsp;\u0026plusmn;\u0026thinsp;7.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCentral SBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123.60\u0026thinsp;\u0026plusmn;\u0026thinsp;16.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107.44\u0026thinsp;\u0026plusmn;\u0026thinsp;8.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCentral DBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.40\u0026thinsp;\u0026plusmn;\u0026thinsp;12.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.04\u0026thinsp;\u0026plusmn;\u0026thinsp;8.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eABI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.08 (0.82\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13 (1.05\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCIMT (mm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90 (0.60\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80 (0.60\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAugmentation index at 75\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.0 (2.0\u0026ndash;47.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.0 (2.0\u0026ndash;37.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFBS (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158 (74\u0026ndash;493)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108 (78\u0026ndash;190)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2 h BG (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e216 (101\u0026ndash;558)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140 (72\u0026ndash;260)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHbA1c\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.16\u0026thinsp;\u0026plusmn;\u0026thinsp;2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eA/C Ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.2 (1.6\u0026ndash;867.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.0 (1.7\u0026ndash;25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeGFR (mL/min/1.73 m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93.0 (31.0-119.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.0 (90.0-108.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLDL (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104.12\u0026thinsp;\u0026plusmn;\u0026thinsp;38.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.76\u0026thinsp;\u0026plusmn;\u0026thinsp;38.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHDL (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.86\u0026thinsp;\u0026plusmn;\u0026thinsp;11.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.40\u0026thinsp;\u0026plusmn;\u0026thinsp;10.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.896\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTriglyceride (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148 (62.0-759.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 (44.0-421.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCholesterol (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e179.84\u0026thinsp;\u0026plusmn;\u0026thinsp;45.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158.98\u0026thinsp;\u0026plusmn;\u0026thinsp;42.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSBP: systolic blood pressure; DBP: diastolic blood pressure; ABI: ankle-brachial index; CIMT: carotid intima-media thickness; \u003cb\u003eFBS\u003c/b\u003e: fasting blood glucose; A/C ratio: Albumin/Creatinine Ratio; eGFR: estimated glomerular filtration rate; LDL: low density lipoprotein; HDL: high density lipoprotein. Values are presented as Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or Median (Range) as appropriate P-values in bold indicate statistical significance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTable\u0026nbsp;(3)\u003c/strong\u003e \u003cp\u003eComparison of Clinical and Laboratory Parameters between patients with and without macrovascular complications\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWith macro-vascular complications, n\u0026thinsp;=\u0026thinsp;19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWithout macro-vascular complications, n\u0026thinsp;=\u0026thinsp;81\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.89\u0026thinsp;\u0026plusmn;\u0026thinsp;5.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.91\u0026thinsp;\u0026plusmn;\u0026thinsp;6.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.991\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (26.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (35.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (73.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (64.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCigarette smoking (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (26.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (17.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.350\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody mass index (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.8 (29.3\u0026ndash;51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.2 (19.3\u0026ndash;58.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes mellitus duration (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.0 (1.0\u0026ndash;25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5 (0.04-20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeripheral SBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146.37\u0026thinsp;\u0026plusmn;\u0026thinsp;15.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119.51\u0026thinsp;\u0026plusmn;\u0026thinsp;11.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeripheral DBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.63\u0026thinsp;\u0026plusmn;\u0026thinsp;12.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.10\u0026thinsp;\u0026plusmn;\u0026thinsp;9.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean peripheral BP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109.84\u0026thinsp;\u0026plusmn;\u0026thinsp;12.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.44\u0026thinsp;\u0026plusmn;\u0026thinsp;9.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCentral SBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136.58\u0026thinsp;\u0026plusmn;\u0026thinsp;14.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110.58\u0026thinsp;\u0026plusmn;\u0026thinsp;10.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCentral DBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93.84\u0026thinsp;\u0026plusmn;\u0026thinsp;12.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.49\u0026thinsp;\u0026plusmn;\u0026thinsp;9.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eABI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.08 (0.82\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12 (1.01\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCIMT (mm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90 (0.70\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80 (0.60\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAugmentation index at 75\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.79\u0026thinsp;\u0026plusmn;\u0026thinsp;6.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.20\u0026thinsp;\u0026plusmn;\u0026thinsp;9.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFBS (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148 (74\u0026ndash;493)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116 (78\u0026ndash;482)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2 h BG (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e213 (12 \u0026minus;\u0026thinsp;540)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155 (72\u0026ndash;558)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHbA1c\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.31\u0026thinsp;\u0026plusmn;\u0026thinsp;2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eA/C Ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.1 (1.6\u0026ndash;125.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.0 (1.7\u0026ndash;867.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeGFR (mL/min/1.73 m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.0 (31.0-112.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.0 (54.0-119.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.384\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLDL (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124.62\u0026thinsp;\u0026plusmn;\u0026thinsp;33.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.00\u0026thinsp;\u0026plusmn;\u0026thinsp;37.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHDL (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.89\u0026thinsp;\u0026plusmn;\u0026thinsp;9.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.98\u0026thinsp;\u0026plusmn;\u0026thinsp;11.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTriglyceride (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157.0 (80.0-241.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119.0 (44.0-759.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCholesterol (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e173.68\u0026thinsp;\u0026plusmn;\u0026thinsp;45.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168.41\u0026thinsp;\u0026plusmn;\u0026thinsp;45.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.650\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReceived anti-hypertensive medication (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Beta blocker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (52.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (24.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Diuretics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (36.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (37.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.987\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; ACE inhibitors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (36.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (32.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.692\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; CCB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (28.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.038\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; ARBS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (31.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (24.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnti-diabetic medications (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Oral hypoglycemic agents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (26.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (81.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Insulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (73.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (18.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eSBP\u003c/b\u003e: systolic blood pressure; \u003cb\u003eDBP\u003c/b\u003e: diastolic blood pressure; \u003cb\u003eABI\u003c/b\u003e: ankle-brachial index; \u003cb\u003eCIMT\u003c/b\u003e: carotid intima-media thickness; \u003cb\u003eFBS\u003c/b\u003e: fasting blood glucose; \u003cb\u003eA/C ratio\u003c/b\u003e: Albumin/Creatinine Ratio; \u003cb\u003eeGFR\u003c/b\u003e: estimated glomerular filtration rate; \u003cb\u003eLDL\u003c/b\u003e: low density lipoprotein; \u003cb\u003eHDL\u003c/b\u003e: high density lipoprotein. \u003cb\u003eACEI\u003c/b\u003e: angiotensin-converting enzyme inhibitors; \u003cb\u003eCCBs\u003c/b\u003e: Calcium channel blockers; \u003cb\u003eARBS\u003c/b\u003e: Angiotensin receptor blockers. Values are presented as Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or Median (Range) as appropriate. P-values in bold indicate statistical significance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;(4)\u003c/b\u003e Comparison of Clinical and Laboratory Parameters between patients with and without microvascular complication\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabd\" border=\"1\"\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eWith micro-vascular complications, n\u0026thinsp;=\u0026thinsp;46\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eWithout micro-vascular complications, n\u0026thinsp;=\u0026thinsp;54\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e52.04\u0026thinsp;\u0026plusmn;\u0026thinsp;5.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e49.94\u0026thinsp;\u0026plusmn;\u0026thinsp;6.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.123\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e(40.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(73.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e(59.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCigarette smoking (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e(13.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody mass index (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e33.4 (20.7\u0026ndash;58.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e30.9 (19.3\u0026ndash;48.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDM disease duration (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e7.5 (0.04-25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e2.0 (0.04-10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeripheral SBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e132.04\u0026thinsp;\u0026plusmn;\u0026thinsp;17.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e118.28\u0026thinsp;\u0026plusmn;\u0026thinsp;12.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeripheral DBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e83.46\u0026thinsp;\u0026plusmn;\u0026thinsp;11.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e78.30\u0026thinsp;\u0026plusmn;\u0026thinsp;10.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean peripheral BP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e100.59\u0026thinsp;\u0026plusmn;\u0026thinsp;12.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e91.63\u0026thinsp;\u0026plusmn;\u0026thinsp;10.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCentral SBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e122.22\u0026thinsp;\u0026plusmn;\u0026thinsp;16.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e109.81\u0026thinsp;\u0026plusmn;\u0026thinsp;11.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCentral DBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e85.22\u0026thinsp;\u0026plusmn;\u0026thinsp;11.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e79.67\u0026thinsp;\u0026plusmn;\u0026thinsp;10.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eABI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1.08 (1.01\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e1.13 (0.82\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCIMT (mm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.90 (0.60\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e0.80 (0.60\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAugmentation index 75\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e24.15\u0026thinsp;\u0026plusmn;\u0026thinsp;11.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e21.26\u0026thinsp;\u0026plusmn;\u0026thinsp;8.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFBS (mg/dl))\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e158 (74\u0026ndash;493)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e109 (78\u0026ndash;190)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2 h BG (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e215 (101\u0026ndash;558)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e147 (72\u0026ndash;260)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHbA1c\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e9.30\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e6.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eA/C Ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e13.2 (1.6\u0026ndash;876.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e9.6 (1.7\u0026ndash;25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEGFR (mL/min/1.73 m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e93.0 (31.0-119.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e99.0 (83.0\u0026ndash;108.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLDL (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e102.42\u0026thinsp;\u0026plusmn;\u0026thinsp;39.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e100.60\u0026thinsp;\u0026plusmn;\u0026thinsp;38.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.814\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHDL (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e44.67\u0026thinsp;\u0026plusmn;\u0026thinsp;11.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e42.74\u0026thinsp;\u0026plusmn;\u0026thinsp;10.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTriglyceride (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e142.0 (62.0-759.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e112.0 (44.0-421.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCholesterol (mg/dl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e178.04\u0026thinsp;\u0026plusmn;\u0026thinsp;46.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e162.06\u0026thinsp;\u0026plusmn;\u0026thinsp;42.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReceived anti-hypertensive medication\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Beta blocker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(37.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(24.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Diuretics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(34.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(38.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; ACEI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(32.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.939\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; CCB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(29.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; ARBS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(32.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(20.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnti-diabetic medications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Oral hypoglycemic agents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(45.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(92.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Insulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(54.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(7.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eSBP\u003c/b\u003e: systolic blood pressure; \u003cb\u003eDBP\u003c/b\u003e: diastolic blood pressure; \u003cb\u003eABI\u003c/b\u003e: ankle-brachial index; \u003cb\u003eCIMT\u003c/b\u003e: carotid intima-media thickness; \u003cb\u003eFBS\u003c/b\u003e: fasting blood glucose; \u003cb\u003eA/C ratio\u003c/b\u003e: Albumin/Creatinine Ratio; \u003cb\u003eeGFR\u003c/b\u003e: estimated glomerular filtration rate; \u003cb\u003eLDL\u003c/b\u003e: low density lipoprotein; \u003cb\u003eHDL\u003c/b\u003e: high density lipoprotein. \u003cb\u003eACEI\u003c/b\u003e: angiotensin-converting enzyme inhibitors; \u003cb\u003eCCBs\u003c/b\u003e: Calcium channel blockers; \u003cb\u003eARBS\u003c/b\u003e: Angiotensin receptor blockers. Values are presented as Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or Median (Range) as appropriate P-values in bold indicate statistical significance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;(5)\u003c/b\u003e Multivariable Logistic Regression Analysis of Independent Predictors for Macrovascular Complications\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabe\" border=\"1\"\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS.E.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExp(B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e95% C.I. for EXP(B)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody mass index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of DM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.337\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeripheral SBP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCentral SBP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.275\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eABI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-17.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCIMT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAIx@75\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.318\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFBG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHBA1c\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.796\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLDL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cb\u003eDM\u003c/b\u003e: diabetes mellitus; \u003cb\u003eSBP\u003c/b\u003e: systolic blood pressure; \u003cb\u003eDBP\u003c/b\u003e: diastolic blood pressure; \u003cb\u003eABI\u003c/b\u003e: ankle-brachial index; \u003cb\u003eCIMT\u003c/b\u003e: carotid intima-media thickness; \u003cb\u003eFBS\u003c/b\u003e: fasting blood glucose; \u003cb\u003eLDL\u003c/b\u003e: low density lipoprotein. P-values in bold indicate statistical significance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;(6)\u003c/b\u003e Multivariable Logistic Regression Analysis of Independent Predictors for Microvascular Complications\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabf\" border=\"1\"\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS.E.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExp (B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e95% C.I. for EXP(B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody mass index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of DM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeripheral SBP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCentral SBP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eABI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-12.720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCIMT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e693.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e82734.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFBG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHBA1c\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eA/CRatio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eeGFR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTriglyceride\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cb\u003eSBP\u003c/b\u003e: systolic blood pressure; \u003cb\u003eDBP\u003c/b\u003e: diastolic blood pressure; \u003cb\u003eABI\u003c/b\u003e: ankle-brachial index; \u003cb\u003eCIMT\u003c/b\u003e: carotid intima-media thickness; \u003cb\u003eFBS\u003c/b\u003e: fasting blood glucose; \u003cb\u003eA/C ratio\u003c/b\u003e: Albumin/Creatinine Ratio; \u003cb\u003eeGFR\u003c/b\u003e: estimated glomerular filtration rate. P-values in bold indicate statistical significance (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThere is a paucity of data that examined the predictive importance of central BP in diabetic hypertensive Egyptians. The current study revealed that peripheral and central systolic and diastolic BP, average peripheral BP, and CIMT were significantly higher, while ABI was significantly lower in complicated T2DM hypertensive patients (those with either micro- or macrovascular complications) compared to those without complications (P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This is consistent with the cross-sectional study of Yang et al. which aimed to evaluate association of CBP and CVD in diabetic hypertensive patients. The study included 360 patients. Furthermore, author reported that patients with CVD had significantly greater central SBP and AIx@75 than those without CVD. Age, male gender, and the occurrence of coronary heart disease and ischemic stroke were linked with higher AIx@75, whereas renin-angiotensin-axis inhibitors were associated with lower AIx@75 levels. After controlling for established risk factors such as brachial SBP, both central SBP and AIx@75 remained substantially linked with CVD, with odds ratios and 95% confidence intervals of 1.09 (1.08\u0026ndash;1.31) and 1.20 (1.15\u0026ndash;1.42, respectively) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile, in the current study; Aix@75 was significantly higher among T2DM hypertensive patients with macrovascular complications (P value\u0026thinsp;\u0026lt;\u0026thinsp;0.001), not those with microvascular complications. This finding could be contributed to the fact that the elevated arterial stiffness increases the development of CVD in hypertensive patients and normal subjects [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlso, in consistent with the present investigation, 11 longitudinal studies including 5648 participants followed for an average of forty-five months were examined by Vlachopoulos et al. Author reported an absolute rise of 10% in the central augmentation index was associated with a 31.8% and 38.4% relative risk increase for CVD and all-cause mortality, respectively, after controlling for CV risk variables, which included brachial BP and history of hypertension in five trials [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnother interesting finding in the current study is that T2DM hypertensive patients with complications (micro- or macrovascular complications) had significantly higher cIMT compared to those without complications (P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Thus, our findings enforce the growing body of research establishing that cIMT as a noninvasive surrogate marker for vascular disease. This finding was supported by the studies of Miyamoto et al. and Talpur et al. which aimed to evaluate the relationship between diabetic retinopathy (DR) and CIMT, and observed that CIMT was more in patients with DR [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Additionally, the recent systematic review and meta-analysis of Liao et al. support the current finding as authors observed associations between increased common carotid artery intima-media thickness (CCA-IMT) and the risk of diabetic micro and macro-vascular complications [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, further larger studies are needed to determine the role of cIMT as a noninvasive surrogate marker for predicting the development of vascular complications among T2DM hypertensive patients.\u003c/p\u003e \u003cp\u003eAdditionally, in the current study, T2DM hypertensive patients with complications (micro- or macrovascular complications) had significantly lower ABI compared to those without complications (P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In line with the current study, a recent study of Amelia et al. which was aimed to using ABI as a non-invasive marker for predicting macrovascular complications among 89 patients with T2DM. The study discovered a link between LDL-C, triglycerides, and vitamin D (25OH-D) based on the ABI classification (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Based on this finding authors concluded that ABI could be for early detection of macrovascular complications among T2DM patients [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGenerally, regarding to the metabolic parameters of the studied cases, it was found that those with either micro- or macrovascular complications had significantly higher fasting blood glucose, 2h blood glucose, HbA1c (p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This finding comes in concordance with previous studies [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, Au Yeung et al. study which aimed to determine the relation between HbA~1c\u0026thinsp;~\u0026thinsp;and CVD, revealed that HbA~1c\u0026thinsp;~\u0026thinsp;was associated with increased coronary artery disease (CAD) risk (OR:1.50 per %, and 95% CI:1.08\u0026ndash;2.11). Thus, HbA1c is likely to be the cause of CAD. However, the underlying mechanisms have yet to be fully understood [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Another study by El Toony et al. reported a link between fasting blood glucose level, HbA1c and developing CAD [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUnique finding for patients with macrovascular complications is that those patients had significantly higher LDL, and triglycerides levels, and significantly lower HDL, and comparable level of total cholesterol levels, A/C ratio, and eGFR compared to those without macrovascular complications (P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). While, the unique finding for patients with microvascular complications is that those patients had significantly higher triglycerides levels, and A/C ratio, and significantly lower eGFR, and comparable level of LDL, HDL, and total cholesterol levels compared to those without microvascular complications (P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Thus, the current finding revealed that dyslipidaemia is a common finding in T2DM hypertensive patients with complication; however, it is more prevalent among those with macrovascular complications. The elevated TC, LDL-C, TAG, and low HDL-C levels observed in T2DM hypertensive individuals with complications were comparable to previously documented trends [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Also, LDL and triglycerides were consistently positively correlated with cardiovascular mortality, according to Silbernagel et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis is not a surprising result since dyslipidemia is recognized to be a substantial risk factor that greatly contributes to the development of micro- and macrovascular complications in patients with T2DM patients. In fact, hyperlipidaemia (high LDL-C, triglycerides) is known to increase the risk for macrovascular diseases. It is thought to accelerate the development of atherosclerosis particularly when diabetes mellitus comorbid by hypertension as T2DM hypertensive patients have a higher risk of developing CAD [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile, renal dysfunction \"defined by higher A/C ratio, and lower eGFR\" is more prevalent among the studied T2DM hypertensive patients with microvascular complications. This finding contributed to the high prevalence of nephropathy observed in the current study (28.0% of the studied cases suffered from nephropathy). As chronic kidney disease is one of the major complications in T2DM patients. UACR and eGFR were two commonly used indicators to assess renal function, according to previous literature; these two biomarkers (eGFR and albuminuria) are independent predictors for progression to end-stage renal disease [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In concordance to the current study, Sabanayagam et al. reported that microvascular complications in T2DM patients was positively associated with both micro and macroalbuminuria and eGFR [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Additionally, studies had shown that eGFR and albuminuria were also predictors of CVD and mortality [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo assess the independent predictors of the development of macrovascular complications in diabetic hypertensive patients, logistic regression analysis was used and revealed that longer disease duration, higher peripheral \u0026amp; central SBP, Aix@75, higher fasting BG, HBA1c, and higher LDL were significantly associated with the occurrence of macrovascular complications in T2DM hypertensive patients. Also, higher BMI, longer disease duration, higher peripheral \u0026amp; central SBP, Aix@75, CIMT, higher fasting BG, HBA1c, higher A/C ratio, higher triglyceride level, and lower eGFR were significantly associated with the occurrence of microvascular complications in T2DM hypertensive patients.\u003c/p\u003e \u003cp\u003eThe main finding in the current finding is that peripheral \u0026amp; central SBP have more or less equivalent predictive ability for prediction of either micro- or macrovascular complications in T2DM hypertensive patients, however, central SBP had slightly higher prediction of macrovascular complications as evident by the values of logistic regression analysis (OR\u0026thinsp;=\u0026thinsp;1.183, 95%CI\u0026thinsp;=\u0026thinsp;1.097\u0026ndash;1.275, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) for central SBP compared to (OR\u0026thinsp;=\u0026thinsp;1.154, 95%CI\u0026thinsp;=\u0026thinsp;1.085\u0026ndash;1.227, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) for peripheral SBP, while peripheral SBP had slightly higher prediction of microvascular complications in T2DM hypertensive patients (OR\u0026thinsp;=\u0026thinsp;1.065, 95%CI\u0026thinsp;=\u0026thinsp;1.032\u0026ndash;1.099, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to (OR\u0026thinsp;=\u0026thinsp;1.064, 95%CI\u0026thinsp;=\u0026thinsp;1.030\u0026ndash;1.099, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) for central SBP.\u003c/p\u003e \u003cp\u003eThus, this finding is not clearly evident may be because of small sample size; particularly because of the lower prevalence of macrovascular complications in the current study which was only documented in 19.0%. This finding highlights the need for further larger studies to confirm the role of central BP as a powerful predictor for macrovascular complication in T2DM hypertensive patients. Nowadays, physicians can take the value of central BP using the non-invasive equipment, which may help to prove the role of central BP in minimizing T2DM macrovascular complications.\u003c/p\u003e \u003cp\u003eJung et al. study which aimed to study the association between central and peripheral BP and microvascular complications in 201 T2DM patients. Author revealed consistent finding to the current study as author stated that central and brachial BP were strongly correlated (correlation coefficients between central and brachial SBP and PP are 0.889 and 0.816, respectively). However, the higher brachial BP levels are associated with increased probability for microvascular complications more than central BP in relation to diabetic nephropathy (DN) and diabetic retinopathy (DR). While, central BP level considered as surrogate marker of macrovascular complications more than brachial BP [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, many previous clinical trials revealed that patients with high central BP had considerably higher cardiovascular risk than those with low central BP, even when their peripheral BP was equal [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], suggesting that central BP could be an independent predictor for CVD [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOn the other hand, Mitchell et al.'s study aimed to investigate how wave velocity, central pulse pressure, and augmentation index might be used to predict cardiovascular risk. The Framingham Heart Study found no correlation between CVD outcomes and the augmentation index, central pulse pressure, or pulse pressure amplification in multivariable models [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis work clearly identified that peripheral and central SBP have more or less equivalent predictive ability for prediction of either micro- or macro-vascular complications in T2DM hypertensive patients, however, central SBP had slightly higher prediction of macro-vascular complications, while peripheral SBP had slightly higher prediction of micro-vascular complications in T2DM hypertensive patients, as evident by the values of logistic regression analysis. In addition, augmentation index was significantly associated with the occurrence of macro-vascular complications among T2DM hypertensive patients but not micro-vascular complications.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eT2DM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eType 2 Diabetes Mellitus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBlood Pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSBP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSystolic Blood Pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDBP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiastolic Blood Pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCVD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCardiovascular Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCIMT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCarotid Intima-Media Thickness\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eABI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnkle-Brachial Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAIx@75\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAugmentation Index standardized to a heart rate of 75 bpm\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHbA1c\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlycated Hemoglobin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eeGFR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eestimated Glomerular Filtration Rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eA/C ratio\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlbumin/Creatinine Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLDL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLow-Density Lipoprotein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHDL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHigh-Density Lipoprotein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACEI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAngiotensin-Converting Enzyme Inhibitors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eARBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAngiotensin Receptor Blockers\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCBs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCalcium Channel Blockers\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Institutional Review Board of the Faculty of Medicine, Ain Shams University (approval number: FAMSU md 193/2022, date of approval: 18 October 2022). The research was conducted in accordance with the principles outlined in the Declaration of Helsinki. Written informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This manuscript does not contain any individual person's data in any form (e.g., individual details, images, or videos).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to privacy and ethical restrictions but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSSH, MMAS, and HAA contributed to the study conception and design. Material preparation, data collection, and analysis were performed by EEG, MNN, and AMMAEHS. The first draft of the manuscript was written by AMMAEHS and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHUMAN AND ANIMAL RIGHTS:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo animals were used in this study. All the procedures performed in this study involving human participants were in accordance with the ethical standards of the Institutional Research Committee and the 1975 Declaration of Helsinki as revised in 2013.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSinha S, Haque M. Insulin Resistance Is Cheerfully Hitched with Hypertension. 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J Atheroscler Thromb. 2016;23(6):668\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller WG, Kaufman HW, Levey AS, Straseski JA, Wilhelms KW, Yu HY, Klutts JS, Hilborne LH, Horowitz GL, Lieske J, Ennis JL, Bowling JL, Lewis MJ, Montgomery E, Vassalotti JA, Inker LA. National Kidney Foundation Laboratory Engagement Working Group Recommendations for Implementing the CKD-EPI 2021 Race-Free Equations for Estimated Glomerular Filtration Rate: Practical Guidance for Clinical Laboratories. Clin Chem. 2021;68(4):511\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVlachopoulos C, Aznaouridis K, O'Rourke MF, Safar ME, Baou K, Stefanadis C. Prediction of cardiovascular events and all-cause mortality with central haemodynamics: a systematic review and meta-analysis. Eur Heart J. 2010;31(15):1865\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiyamoto M, Kotani K, Okada K, Fujii Y, Konno K, Ishibashi S, Taniguchi N. The correlation of common carotid arterial diameter with atherosclerosis and diabetic retinopathy in patients with type 2 diabetes mellitus. Acta Diabetol. 2012;49(1):63\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTalpur AS, Amar Z, Zafar S, Memon A, Latif AHE, Hafizyar F, Hashim S, Nazary K. (2021). Association between diabetic retinopathy and carotid intima-media thickness. Cureus, 13(6), e15507.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiao M, Chen S, Guo R. (2023). Association between carotid ultrasonographic parameters and microvascular and macrovascular complications in diabetes: A systematic review and meta-analysis. 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The impact of glycated hemoglobin (HbA1c) on cardiovascular disease risk: a Mendelian randomization study using UK Biobank. Diabetes Care. 2018;41(9):1991\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEghan B, Acheampong JW. Dyslipidemia in outpatients at General Hospital in Kumasi, Ghana: cross-sectional study. Croatian Med J. 2003;44(5):576\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdinortey MB, Gyan BE, Adjimani J, Nyarko P, Sarpong C, Tsikata FY, Nyarko AK. Dyslipidaemia associated with type 2 diabetics with micro and macrovascular complications among Ghanaians. Indian J Clin Biochem. 2011;26:261\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilbernagel G, Scharnagl H, Kleber ME, Delgado G, Stojakovic T, Laaksonen R, Erdmann J, Rankinen T, Bouchard C, Landmesser U. LDL triglycerides, hepatic lipase activity, and coronary artery disease: An epidemiologic and Mendelian randomization study. 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Cardiovasc Diabetol. 2015;14:38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJung C-H, Jung S-H, Kim K-J, Kim B-Y, Kim C-H, Kang S-K, Mok J-O. Differential associations of central and brachial blood pressure with carotid atherosclerosis and microvascular complications in patients with type 2 diabetes. BMC Cardiovasc Disord. 2014;14(1):23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLukich E, Matas Z, Boaz M, Shargorodsky M. Increasing derangement of glucose homeostasis is associated with increased arterial stiffness in patients with diabetes, impaired fasting glucose and normal controls. Diab/Metab Res Rev. 2010;26(5):365\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBen-Shlomo Y, Spears M, Boustred C, May M, Anderson SG, Benjamin EJ, Boutouyrie P, Cameron J, Chen C-H, Cruickshank JK. Aortic pulse wave velocity improves cardiovascular event prediction: an individual participant meta-analysis of prospective observational data from 17,635 subjects. J Am Coll Cardiol. 2014;63(7):636\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitchell GF, Hwang S-J, Vasan RS, Larson MG, Pencina MJ, Hamburg NM, Vita JA, Levy D, Benjamin EJ. Arterial stiffness and cardiovascular events: the Framingham Heart Study. Circulation. 2010;121(4):505\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Type 2 Diabetes, hypertension, vascular complications, central blood pressure","lastPublishedDoi":"10.21203/rs.3.rs-8811000/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8811000/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eVascular complications in diabetes and hypertension significantly contribute to cardiovascular morbidity and mortality.\u003c/p\u003e\u003ch2\u003eAim\u003c/h2\u003e \u003cp\u003eThis study assessed the association between central blood pressure and vascular complications in patients with type 2 diabetes and hypertension. It also explored its role in predicting microvascular and macrovascular complications.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis case-control study included 100 patients aged 40 to 60 years with type 2 diabetes and newly diagnosed hypertension: 50 cases with vascular complications and 50 controls. Patients were further stratified based on the presence of microvascular or macrovascular complications. Central and peripheral blood pressures, carotid intima-media thickness, ankle-brachial index, and augmentation index standardized to 75 beats per minute were measured. Other variables assessed included demographic data, anthropometric measurement, systemic examination, laboratory data, echocardiographic parameters, fundus findings, and glucose parameters.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCentral systolic and diastolic blood pressures were significantly higher in cases than controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Subgroup analyses showed that central systolic blood pressure was significantly higher in patients with both microvascular and macrovascular complications (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Logistic regression analyses performed for each subgroup demonstrated that central systolic blood pressure independently predicted microvascular (odds ratio\u0026thinsp;=\u0026thinsp;1.064, 95 percent confidence interval: 1.030 to 1.099) and macrovascular (odds ratio\u0026thinsp;=\u0026thinsp;1.183, 95 percent confidence interval: 1.097 to 1.275) complications. Predictive abilities were comparable to those of peripheral systolic blood pressure.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eCentral systolic blood pressure is significantly associated with vascular complications and independently predicts both microvascular and macrovascular complications. It demonstrated similar predictive ability for microvascular complications and a marginally stronger predictive ability for macrovascular complications.\u003c/p\u003e","manuscriptTitle":"Central Blood Pressure Association with Micro- and Macro-vascular Complications in A sample of type 2 Diabetic Patients: A Case-Control Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 16:31:28","doi":"10.21203/rs.3.rs-8811000/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"12712107830665705998901258585752995368","date":"2026-05-14T14:30:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"48381445962247728254094932796485510951","date":"2026-05-13T11:08:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"176461594606607977437469499427902924302","date":"2026-05-08T04:05:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-05T13:22:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"302772026413180135486602954725647741655","date":"2026-03-01T18:16:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-27T09:48:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-25T09:39:59+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-24T07:01:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-23T19:45:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2026-02-23T19:40:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"83c1778a-51a6-45c5-ba80-a88afbdc8f5e","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"12712107830665705998901258585752995368","date":"2026-05-14T14:30:35+00:00","index":90,"fulltext":""},{"type":"reviewerAgreed","content":"48381445962247728254094932796485510951","date":"2026-05-13T11:08:19+00:00","index":86,"fulltext":""},{"type":"reviewerAgreed","content":"176461594606607977437469499427902924302","date":"2026-05-08T04:05:09+00:00","index":70,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-08T16:31:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 16:31:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8811000","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8811000","identity":"rs-8811000","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}