Impact of Coronary Artery Calcium on Progression of Diastolic Dysfunction: A Cohort Study

Impact of Coronary Artery Calcium on Progression of Diastolic Dysfunction: A Cohort 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 Impact of Coronary Artery Calcium on Progression of Diastolic Dysfunction: A Cohort Study Ki Hong Choi, Danbee Kang, Seung Hun Lee, Darae Kim, Sung Won Cho, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4585013/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Feb, 2025 Read the published version in BMC Medicine → Version 1 posted 12 You are reading this latest preprint version Abstract Background The relationship between coronary artery calcium (CAC) and progression of diastolic dysfunction (DD) during longitudinal follow-up is uncertain. This study aimed to investigate the prevalence and progression of DD according to severity of CAC and understand their synergistic effect on mortality. Methods This was a population-based cohort study. All 15,193 adults who underwent a health screening exam with simultaneous echocardiography and CAC scan were enrolled. Definite DD (≥ 3/4 abnormal parameters for DD [e’, E/e’, tricuspid regurgitation-velocity, and left atrial volume index) and definite or probable DD (≥ 2/4) were defined. All-cause mortality was assessed based on the CAC and DD. Results Among the population, 7,995 participants (52.6%) had CAC = 0; 4,661 (30.7%) had 0 < CAC < 100; and 2,537 (16.7%) had CAC ≥ 100. The prevalence ratios for definite (adjusted-ratio:1.72, 95% CI:1.23–2.22) and definite or probable DD (adjusted-ratio:1.83, 95% CI:1.31–2.36) were significantly higher in individuals with CAC ≥ 100 than in those with CAC = 0. There was significant linear association of CAC with E/e’ (adjusted p-for linearity = 0.001). Compared with CAC < 100 without definite DD, the adjusted HRs with 95% CI for mortality of CAC ≥ 100 without definite DD, CAC < 100 with definite DD, and CAC ≥ 100 with definite DD were 2.56 (95% CI:1.67–3.94), 3.08 (95% CI:1.28–7.39), and 3.91 (95% CI:1.68–9.10). Among participants without DD at CAC measurement who had at least two echocardiographic measurements, the presence of significant CAC (≥ 100) was significantly associated with accelerated progression in definite DD over time (adjusted-HR:1.46, 95% CI:1.13–1.88), with more rapid elevation of E/e’ during follow-up (difference:0.06, 95% CI:0.02–0.10, p = 0.003). Conclusions In the general population, there was a significant relationship between CAC and prevalence of DD, and both subclinical parameters were associated with increased mortality. Moreover, CAC ≥ 100 significantly affects the progression of DD independently of other clinical factors. coronary artery calcium diastolic dysfunction mortality echocardiography heart failure Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Left ventricular (LV) diastolic dysfunction (DD) is highly prevalent and represents a pattern of relaxation abnormality, leading to elevated filling pressure in the LV despite a normal ejection fraction (EF).[ 1 , 2 ] Established risk factors for DD include advanced age, obesity, hypertension, diabetes, and atrial fibrillation.[ 3 – 6 ] The manifestation of DD is recognized to independently increase the risk of major cardiovascular events, encompassing cardiac mortality, heart failure (HF), and atherosclerotic events, even in the general population.[ 7 – 9 ] These results emphasize the importance of early recognition and initiation of appropriate preventative treatments for DD in the subclinical stage. The coronary artery calcium (CAC) scan measured by computed tomography (CT) has become popular for individuals at risk for atherosclerotic cardiovascular disease. The CAC is strongly associated with atherosclerotic burden and predicts coronary artery disease events and mortality, regardless of age, sex, race, or atherosclerotic cardiovascular disease risk.[ 10 – 13 ] Recently, there has been great interest in better understanding the relationship between DD and CAC. It has been shown in several studies that CAC burden or CAC progression is associated with a risk of HF with preserved ejection fraction (HFpEF), suggesting a potential connection between CAC and DD.[ 14 – 16 ] However, there are limited data regarding the synergistic effects on mortality of DD and CAC, both of which are subclinical disease subsets in the general population. More importantly, the relationship between CAC and progression of DD over time with longitudinal follow-up is poorly understood. Therefore, our study aimed to evaluate the association of CAC score with prevalence of DD assessed by resting echocardiography at baseline and to explore the combined effect of CAC and DD on mortality in the general population using a large cohort from a health screening examination program in Korea. We also sought to evaluate the incidence rates of progression of DD during follow-up according to the baseline CAC score in a longitudinal dataset. Methods Study Population We conducted a retrospective cohort analysis of men and women ≥ 18 years of age who underwent a comprehensive health screening exam with simultaneous echocardiography and CAC scan at the Samsung Medical Center Health Promotion Center, Republic of Korea, from January 2010 and December 2019 (N = 15,830). We excluded 1,978 participants who had history of cardiovascular disease (N = 571) or LVEF < 50% at baseline (N = 31). Among the eligible participants (N = 15,228), we further excluded 35 who had missing data for lipid profile, blood pressure, and body mass index (BMI) at baseline. The final sample size was 15,193. The Institutional Review Board of Samsung Medical Center approved this study and waived the requirement for informed consent as we used only de-identified data routinely collected during health screening visits. Measurement Echocardiography All echocardiography measurements were performed in health screening practice in accordance with guidelines using a commercially available systems (Vivid7, GE Medical Systems, Horten, Norway; Vivid9, GE Medical Systems, Horten, Norway; SC2000, Siemens Medical Solution, Mountain View, CA, USA).[ 17 ] The inter-ventricular septum thickness, posterior wall thickness, and LV dimensions in diastole and systole were measured from M-mode images, and the LV mass (g) was calculated using the American Society of Echocardiography (ASE) and the European Association of Cardiovascular Imaging (EACVI) equation.[ 18 ] LVEF was assessed using the biplane Simpson technique, M-mode, or visual estimation. Left atrial volume was measured by the biplane method using dedicated apical 4- and 2-chamber views at the end-systolic frame to avoid foreshortening. The left atrial volume index (LAVI) was calculated as left atrial volume / body surface area (mL/m 2 ). Trans-mitral inflow velocities (E and A) were obtained by pulsed-wave Doppler analysis performed in the apical-4 chamber plane. Tissue Doppler imaging was used to obtain early (e’) and late (a’) atrial diastolic annular velocities in the apical 4-chamber view. Peak tricuspid regurgitation (TR) velocity was recorded using continuous Doppler. Definitions of DD DD was defined according to the 2016 ASE/EACVI recommendations.[ 19 ] Four main echocardiographic parameters were considered, and abnormal cutoffs were as follows: septal e’ 15, LAVI > 34 mL/m 2 , and TR velocity > 2.8 m/s. The presence of at least 3 of 4 abnormal DD parameters were mandatory to classify definite DD, even if some of the four diastolic parameters were missing. Similarly, the presence of at least 2 of 4 abnormal DD parameters was evaluated as a separate binary variable and defined as ‘definite or probable DD.’[ 6 ] Each DD index was also evaluated as a continuous variable to complement the binary assessment of DD using previously determined cutoffs. Coronary CT scans Imaging data for the evaluation of CAC were acquired using Brilliance 40 (Philips Medical Systems), VCT LightSpeed 64 (GE Healthcare), or Discovery 750HD (GE Healthcare) multidetector CT scanners. The analysis of the scans was performed on Extended Brilliance Workspace (Philips Medical Systems) or Advantage (GE Healthcare) workstations. CAC scores were calculated as described by Agatston et al.[ 20 ] Covariates At each visit, demographic characteristics, smoking status, alcohol consumption, medical history, and medication use were collected through standardized, self-administered questionnaires. Smoking status was categorized into never, former, or current smoker. Alcohol consumption was categorized into none, light (< 10 g/day in women and < 20 g/day in men), moderate (10–<40 g/day in women and 20–<60 g/day in men), and heavy (≥ 40 g/day in women and ≥ 60 g/day in men).[ 21 ] Height, weight, waist circumference, and sitting blood pressure were measured by trained nurses. BMI was calculated as weight in kilograms divided by height in meters squared. Hypertension was defined as a systolic blood pressure ≥ 140 mmHg, a diastolic blood pressure ≥ 90mmHg, a self-reported history of hypertension, or current use of anti-hypertensive medications. Diabetes mellitus was defined as a fasting serum glucose ≥ 126mg/dL, a self-reported history of diabetes, or self-reported use of insulin or oral hypoglycemic medications. Mortality Mortality data were obtained from a health screening center registry through December 31, 2019, ascertained by the Korean Ministry of the Interior and Safety. Statistical Analysis Descriptive statistics were used to summarize the characteristics of participants by CAC category. To test for linear trends, we included the median value of each CAC category as a continuous variable in the regression models. To compare the parameters of echocardiography by CAC, we conducted multivariable linear regression models to control age, sex, BMI, smoking status, drinking status, diabetes, hypertension, hyperlipemia, statin use, and aspirin use. To evaluate the association between CAC category and the prevalence of definite or probable DD, we calculated its prevalence and 95% confidence interval (CI) for definite or probable DD by CAC category. We also used log-binomial regression to estimate adjusted prevalence ratios and 95% CIs after adjusting for age, sex, BMI, smoking status, alcohol consumption, diabetes, hypertension, hyperlipidemia, statin use, and aspirin use. To estimate the synergistic effects of CAC and DD on mortality, we generated 4 groups of CAC < 100 without definite DD, CAC < 100 with definite DD, CAC ≥ 100 without definite DD, and CAC ≥ 100 with definite DD. Participants were followed from the time of their first health screening exam until death or December 31, 2019, whichever came first. We used a proportional hazards model to assess the associations between the 4 groups at baseline and all-cause mortality. Participants without definite or probable DD at baseline were followed for development of definite or probable DD using all available echocardiography until the last available echocardiography follow-up at the time of data extraction (31 December 2019). Since the development of DD occurred at an unknown time point between the visit of detection and the previous visit (interval censoring), we used a flexible parametric proportional hazards model to assess the association between the CAC status at baseline and the development of DD.[ 22 ] Since participants in our analyses had to have undergone at least 2 screening visits (N = 5,706), we used inverse probability weights (IPWs) to correct for potential selection bias. The IPWs of study participants were reweighted so that participants who were similar to those lost to follow-up after the first echocardiography were assigned a higher weight. IPWs were obtained from a logistic regression model including all those screened with at least one echocardiography and with similar selection criteria to those used in this analysis (N = 9,487). We also compared the quantitative trajectories of e’ and E/e’ by CAC status at baseline using linear mixed models for longitudinal data with random intercepts and random slopes. We estimated the changes of e’ and E/e’ (with 95% CIs) relative to those of participants with CAC = 0. All reported P values were two-sided, and the significance level was set to 0.05. All analyses were performed using STATA version 16 (StataCorp LP, College Station, TX, USA). Results Baseline Characteristics The mean (standard deviation) age of study participants was 55.8 (8.6) years. The median CAC score at baseline was 0 (52.6% participants had a CAC score of 0). The prevalence of CAC by category was categorized as follows: 52.6% had a score of 0, 30.7% had a 0 < CAC < 100, and 16.7% had a CAC ≥ 100. Age, male, current smoker, and metabolically unhealthy were positively associated with CAC (Table 1 ). Table 1 Baseline characteristics of study participants by CAC group Characteristic CAC = 0 0 < CAC < 100 CAC ≥ 100 (N = 7,995) (N = 4,661) (N = 2,537) Age, years 52.9 (7.3) 57.2 (8.2) 62.1 (9.0) Sex, male 6041 (75.6) 3902 (83.7) 2227 (87.8) BMI, kg/m 2 24.0 (2.8) 24.7 (2.8) 25.0 (2.8) Smoking Never 3067 (38.4) 1456 (31.2) 674 (26.6) Ever 4572 (57.2) 2994 (64.2) 1727 (68.1) Missing 356 (4.5) 211 (4.5) 136 (5.4) Drinking status None 1759 (22) 998 (21.4) 562 (22.2) Little 4380 (54.8) 2441 (52.4) 1257 (49.5) Moderate 1007 (12.6) 685 (14.7) 358 (14.1) Heavy 506 (6.3) 310 (6.7) 223 (8.8) Missing 343 (4.3) 227 (4.9) 137 (5.4) Comorbidities Diabetes 727 (9.1) 819 (17.6) 719 (28.3) Hypertension 2392 (29.9) 2222 (47.7) 1580 (62.3) Hyperlipemia 4198 (52.5) 3101 (66.5) 1845 (72.7) Atrial fibrillation 25 (0.3) 21 (0.5) 26 (1.0) Cancer 463 (5.8) 373 (8.0) 252 (9.9) Laboratory findings LVEF, % 64.6 (5.5) 64.9 (5.6) 65.2 (5.6) NT-proBNP, pg/mL (N = 8,308) 30.6 (45.2) 33.9 (58.5) 55.8 (135.9) Total cholesterol, mg/dL 193.8 (34.3) 192.5 (36.9) 179.8 (37.4) LDL-C, mg/dL 125.6 (31.6) 125.2 (33.6) 112.8 (33.7) HDL-C, mg/dL 56.6 (15.0) 54.2 (14.0) 53.9 (14.1) hsCRP, mg/dL 0.1 (0.3) 0.1 (0.3) 0.1 (0.3) Lipoprotein (a), mg/dL 18.6 (17.7) 19.3 (19.4) 21.1 (22.6) Creatinine, mg/dL 0.9 (0.2) 0.9 (0.2) 0.9 (0.3) Medication Statin 891 (11.1) 1078 (23.1) 880 (34.7) Aspirin 442 (5.5) 712 (15.3) 80 (3.2) Values are mean (SD), median (IQR), or number (%). All P for trends comparing baseline characteristics of the three groups were < 0.05. Abbreviations: BMI, body mass index; CAC: coronary artery calcium; HDL-C, high-density lipoprotein cholesterol, hsCRP, high-sensitivity C-reactive protein; IQR, interquartile range; LDL-C, low-density lipoprotein cholesterol; LVEF, left ventricular ejection fraction; NT-proBNP, N-Terminal pro-B-type natriuretic peptide; SD, standard deviation. Associations Between CAC and Baseline Echocardiographic Parameters In terms of the parameters of echocardiography, the CAC was linearly associated with lower septal e′, higher E/e’, LV mass, and TR velocity among the groups ( Supplementary Table 1 ). On the other hand, CAC showed no linear association with E velocity. When performing association analysis between CAC as a continuous variable and LVEF or E/e’, the linear adjusted p-value for LVEF was 0.47, but the linear p-value was 0.001 for E/e' (Fig. 1 ). At baseline, the prevalence of definite and probable DD was 2.6%, and 12.2%, respectively. The prevalence ratio for definite DD was 1.34 (95% CI: 0.98–1.69) and 1.72 (95% CI: 1.23–2.22) in the groups of 0 < CAC < 100 and CAC ≥ 100 compared to the CAC = 0 group, respectively (Table 2 ). The prevalence ratio for definite or probable DD when comparing the groups of 0 < CAC < 100 and CAC ≥ 100 with the CAC = 0 group was 1.34 (95% CI: 0.98–1.70) and 1.83 (95% CI: 1.31–2.36), respectively (Table 2 ). Higher CAC score was positively associated with the prevalence of definite and probable DD regardless of age ( Supplementary Fig. 1 ). Table 2 Prevalence ratio for incidence of diastolic dysfunction by CAC score CAC score Number of DD cases (%) Adjusted prevalence ratio (95% CI) * Definite DD CAC = 0 108 (1.4) Reference 0 < CAC < 100 145 (3.1) 1.34 (0.98, 1.69) CAC ≥ 100 154 (6.1) 1.72 (1.23, 2.22) Definite or probable DD CAC = 0 555 (6.9) Reference 0 < CAC < 100 654 (14.0) 1.34 (0.98, 1.70) CAC ≥ 100 648 (25.5) 1.83 (1.31, 2.36) * Adjusted for age, sex, BMI category, smoking status (never, ever, or missing), drinking status, diabetes, hypertension, hyperlipemia, atrial fibrillation, history of cancer, aspirin use, and statin use at baseline. Abbreviations: BMI, body mass index; CAC: coronary artery calcium; CI, confidence interval; DD, diastolic dysfunction. Effects of CAC and DD on Mortality From baseline to date at vital status confirmation (median follow-up was 5.1 years, maximum 9.5 years), 117 individuals died. The CAC ≥ 100 with definite DD group at baseline showed the highest cumulative mortality rate among 4 groups (Fig. 2 ). Compared with CAC < 100 without definite DD, the adjusted HRs (95% CIs) for all-cause mortality of CAC ≥ 100 without definite DD and CAC < 100 with definite DD were 2.56 (95% CI: 1.67–3.94) and 3.08 (95% CI: 1.28–7.39), respectively. The risk of mortality was highest in patients with CAC ≥ 100 and definite DD (adjusted HR:3.91, 95% CI: 1.68–9.10, Table 3 ). Table 3 Hazard ratio for mortality by CAC score and diastolic dysfunction 8-year cumulative mortality,% (95% CI) Adjusted hazard ratio (95% CI) * CAC < 100 without definite DD 0.96 (0.68, 1.35) Reference CAC ≥ 100 without definite DD 3.62 (2.56, 5.10) 2.56 (1.67, 3.94) CAC < 100 with definite DD 3.27 (1.47, 7.20) 3.08 (1.28, 7.39) CAC ≥ 100 with definite DD 9.94 (4.51, 21.14) 3.91 (1.68, 9.10) * Adjusted for age, sex, BMI, smoking status (never, ever, or missing), drinking status, diabetes, hypertension, hyperlipemia, atrial fibrillation, history of cancer, aspirin use, and statin use at baseline. Abbreviations: BMI, body mass index; CAC: coronary artery calcium; CI, confidence interval; DD, diastolic dysfunction. Association Between CAC and Progression of DD Among the participants, those without definite or probable DD at the time of CAC measurement who had at least two available echocardiographic measurements were 4,938 and 5,221, respectively. The average duration of follow-up was 4.1 years (maximum 9.9 years; average number of visits per participant was 4.5). During the follow-up period, the annual average incidence rates of definite DD in participants with CAC = 0, 0 < CAC < 100, and CAC ≥ 100 at baseline were 0.46, 0.91 and 1.91, respectively (Fig. 3 A). The multivariable adjusted hazard ratios (HRs) of definite DD (95% CI) for comparing participants with CAC = 0 to those with 0 < CAC < 100 and CAC ≥ 100 were 1.32 (95% CI: 0.90–1.95) and 1.95 (95% CI: 1.16–3.26), respectively (Table 4 ). The annual average incidence rates of definite or probable DD in participants with CAC = 0, 0 < CAC < 100, and CAC ≥ 100 were 1.82, 3.08 and 5.23, respectively (Fig. 3 B). The multivariable adjusted HRs of definite or probable DD (95% CI) comparing participants with CAC = 0 to those with 0 < CAC < 100 and CAC ≥ 100 were 1.17 (95% CI: 0.96–1.44) and 1.46 (95% CI: 1.13–1.88), respectively (Table 4 ). Table 4 Hazard ratios for incidence of diastolic dysfunction by CAC score among participants without dysfunction at baseline Number of events (Incidents% per a year) Adjusted hazard ratio (95% CI) * Definite DD (N = 5,221) CAC = 0 56 (0.46) Reference 0 < CAC < 100 69 (0.91) 1.32 (0.90, 1.95) CAC ≥ 100 23 (1.91) 1.95 (1.16, 3.26) Definite or probable DD (N = 4,938) CAC = 0 217 (1.82) Reference 0 < CAC < 100 218 (3.08) 1.17 (0.96, 1.44) CAC ≥ 100 171 (5.23) 1.46 (1.13, 1.88) * Adjusted for age, sex, BMI, smoking status (never, ever, or missing), drinking status, diabetes, hypertension, hyperlipemia, atrial fibrillation, history of cancer, aspirin use, and statin use at baseline. The hazard ratio was estimated using inverse probability weighting (see text for details) for generalizability. Abbreviations: BMI, body mass index; CAC, coronary artery calcium; CI, confidence interval; DD, diastolic dysfunction. Among participants without definite or probable DD, the 0 < CAC < 100 (difference: 0.03, 95% CI: 0.00-0.06, P = 0.042) and CAC ≥ 100 (difference: 0.06; 95% CI: 0.02–0.10, P = 0.003) groups showed faster increasing trends of E/e’ compared to the CAC = 0 group (Fig. 4 ). DISCUSSION The current study investigated the relationship between CAC score and prevalence of DD, their effects on mortality, and the progression of DD over time according to CAC score in a general population using a large longitudinal cohort from a health screening examination program ( Central Illustration ). The principal findings of this study were as follows. First, the prevalence ratio of definite or probable DD was significantly higher in participants with CAC ≥ 100 compared to those without CAC, even after adjustment for confounding factors including age. In particular, CAC was significantly correlated with baseline E/e’ but not with LVEF. Second, after stratification according to CAC score and definite DD, individuals with CAC ≥ 100 and definite DD showed the highest risk of mortality. Third, in longitudinal analysis, significant CAC (≥ 100) was associated with accelerated progression in DD over time, with more rapid elevation of LV filling pressure as measured by E/e’. The historical inconsistency in defining and grading diastolic dysfunction has presented a formidable challenge for clinicians. As a result, the 2016 ASE/EACVI was newly recommended for diagnosis of DD to provide a streamlined stepwise hierological assessment using four key variables in the absence of myocardial disease (e’ velocity, E/e’ ratio, TR velocity, and LAVI).[ 19 ] The application of this guideline resulted in a much lower prevalence of DD compared to previous recommendations.[ 23 ] Furthermore, a substantial portion of individuals have ‘indeterminate’ diastolic function, indicating reduced sensitivity of the diagnostic criteria. Given a previous report that indeterminate DD was not a benign disease and showed a significantly increased risk of cardiovascular death or HF readmission compared to no evidence of DD,[ 24 ] we defined participants categorized as indeterminate (2 of 4 abnormal DD parameters) as ‘probable DD’ and used this as one of the outcomes. Associations between CAC and DD and their Effects on Mortality Both CAC and DD were associated with advanced age, hypertension, diabetes mellitus, and obesity.[ 3 – 5 , 25 – 27 ] These comorbidities are believed to trigger a systemic proinflammatory state, leading to coronary microvascular dysfunction, followed by structural and functional alterations such as myocardial inflammation and interstitial fibrosis,[ 28 , 29 ] and these changes may affect both LV diastolic stiffness and formation of calcified coronary plaques. In this regard, several previous studies have been conducted to evaluate the association between CAC and DD.[ 30 – 34 ] However, none of these studies had a large sample size. Therefore, the association between CAC and DD is currently inconclusive, with conflicting results after adjusting for common shared comorbidities. The current study found an independent association between CAC score and DD, even after adjustment for various comorbidities in a large cohort of a general population without previous history of cardiovascular disease. Interestingly, CAC score was continuously correlated with baseline E/e’. In addition, higher CAC score was associated with the prevalence of DD irrespective of age category. These results imply that CAC score offers incremental information beyond traditional risk factors for predicting DD or high filling pressure. The presence of both CAC and DD is an independent predictor of cardiovascular outcomes in numerous cohorts.[ 10 – 13 , 35 , 36 ] However, there is a scarcity of data regarding the effects on mortality when patients have both subclinical CAC and DD. In the current study, participants with either DD or a significant CAC score (≥ 100) had an increased risk of all-cause mortality during follow-up compared to those without DD and significant CAC. More important, the integration of subclinical parameters including CAC and DD further increased the risk of all-cause mortality in the general population. These results indicate that subclinical CAC and DD, even without definitive symptoms or signs of ischemia or HF, are independent risk factors of all-cause mortality. Furthermore, rapid detection of and response to pathophysiological changes, such as a chronic inflammatory process that affects both CAC and DD, is thought to be necessary to reduce the long-term mortality rate in the general population. Progression of DD According to Presence of CAC Although CAC and DD share some pathophysiology and risk factors, their independent effects on each other are not well characterized. Therefore, we hypothesized that participants with a significant CAC score at baseline have more highly accelerated progression of DD over time than those without CAC, independent of other clinical characteristics. If substantiated, this would establish CAC as a crucial biomarker for preclinical HFpEF, enhancing its utility in guiding more effective preventive interventions. In our longitudinal dataset of participants with a significant CAC score and no DD at baseline, 1.9% developed definite and 5.2% developed definite or probable DD each year. This was 2.0 and 1.5 times more frequent compared to participants without DD, respectively, independent of age, sex, BMI, or other potential confounders including comorbidities. Furthermore, a significant CAC score was associated with more rapid increase of E/e’ during follow-up than in patients without CAC. To our knowledge, this is the first study to confirm that significant CAC affects the progression of DD independently of other clinical factors. These findings suggest that individuals with higher CAC scores are at an increased risk of developing subclinical or overt HFpEF, emphasizing the need for early recognition by active surveillance and timely intervention. Limitations Several limitations should be considered in the interpretation of our findings. First, this study was derived from retrospective observational data; therefore, unmeasured confounding factors could have influenced the study results. Second, the severity of symptoms related to DD or CAC was not quantified in this study. Third, additional echocardiographic parameters from the 2016 ASE/EACVI recommendations, such as pulmonary venous flow or deceleration time or LV strain, were not included in the current study and could provide helpful guidance in the accurate assessment of diastolic function. Fourth, in the longitudinal dataset, there was a loss of sample size in the analysis of DD progression according to CAC by requiring participants to have undergone at least two echocardiograms. However, there were near 5000 participants in whom progression of DD was confirmed; therefore, the number of samples was sizable. Fifth, the follow-up duration was not standardized, potentially leading to variations in the timing of subsequent evaluations. Consequently, patients with more severe conditions might have undergone more frequent assessments, influencing the diagnosis of DD during follow-up. Sixth, our study was conducted in Korean men and women attending regular health screening examinations, and our findings may not be generalizable to other populations, particularly other ages, or race/ethnicity. CONCLUSIONS In a general population that underwent a comprehensive health screening exam with simultaneous echocardiography and CAC scan, there was strong association between CAC and DD. If patients had both subclinical parameters, their risk of mortality further increased compared to those who had only one. Moreover, the presence of a significant CAC score (≥ 100) might affect the progression of DD independent of other clinical factors. These findings highlight the potential of CAC as a biomarker for preclinical HFpEF and the importance of considering subclinical parameters for risk assessment in the general population. Abbreviations ASE American Society of Echocardiography BMI body mass index CAC coronary artery calcium CI confidence interval CT computed tomography DD diastolic dysfunction EACVI European Association of Cardiovascular Imaging EF ejection fraction HF heart failure HFpEF heart failure with preserved ejection fraction HR hazard ratio IPW inverse probability weights LAVI left atrial volume index LV left ventricle TR tricuspid regurgitation Declarations Acknowledgement: None Funding/Support : None Conflict of Interest Disclosures : The authors have no conflicts of interest to declare. Reproducible Research Statement: Anonymized patient-level data will be made available by the corresponding author in response to reasonable requests. Consent was not obtained for data sharing, but the presented data are anonymized, and the risk of identification is minimal. Author contributions: Drs. Ki Hong Choi, Danbee Kang, Soo Jin Cho, and Jeong Hoon Yang had full access to all data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis. Conceived and designed the research: Ki Hong Choi, Danbee Kang, Soo Jin Cho, Jeong Hoon Yang Acquisition, analysis, or interpretation of data : Ki Hong Choi, Danbee Kang Drafting of the manuscript : Ki Hong Choi, Danbee Kang, Soo Jin Cho, Jeong Hoon Yang Made critical revision of the manuscript for key intellectual content: Seung Hun Lee, Darae Kim, Sung Won Cho, Soo-Hee Choi, Taek Kyu Park, Joo Myung Lee, Young Bin Song, Joo-Yong Hahn, Seung-Hyuk Choi, Hyeon-Cheol Gwon, Jeong Hoon Yang Statistical analysis : Danbee Kang References Nagueh Sherif F. Left Ventricular Diastolic Function. JACC: Cardiovasc Imaging. 2020;13(1Part2):228–44. https://doi.org/10.1016/j.jcmg.2018.10.038 . Zile MR, Baicu CF, Gaasch WH. 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Left Ventricular Diastolic Dysfunction in the Community: Impact of Diagnostic Criteria on the Burden, Correlates, and Prognosis. J Am Heart Assoc. 2018;7(11):e20180601. https://doi.org/10.1161/jaha.117.008291 . Budoff MJ, Shaw LJ, Liu ST, Weinstein SR, Mosler TP, Tseng PH, et al. Long-term prognosis associated with coronary calcification: observations from a registry of 25,253 patients. J Am Coll Cardiol. 2007;49(18):1860–70. https://doi.org/10.1016/j.jacc.2006.10.079 . Budoff MJ, Young R, Burke G, Jeffrey Carr J, Detrano RC, Folsom AR, et al. Ten-year association of coronary artery calcium with atherosclerotic cardiovascular disease (ASCVD) events: the multi-ethnic study of atherosclerosis (MESA). Eur Heart J. 2018;39(25):2401–8. https://doi.org/10.1093/eurheartj/ehy217 . Mehta A, Pandey A, Ayers CR, Khera A, Sperling LS, Szklo MS, et al. Predictive Value of Coronary Artery Calcium Score Categories for Coronary Events Versus Strokes: Impact of Sex and Race: MESA and DHS. Circ Cardiovasc Imaging. 2020;13(8):e010153. https://doi.org/10.1161/circimaging.119.010153 . Detrano R, Guerci AD, Carr JJ, Bild DE, Burke G, Folsom AR, et al. Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N Engl J Med. 2008;358(13):1336–45. https://doi.org/10.1056/NEJMoa072100 . Leening MJ, Elias-Smale SE, Kavousi M, Felix JF, Deckers JW, Vliegenthart R, et al. Coronary calcification and the risk of heart failure in the elderly: the Rotterdam Study. JACC Cardiovasc Imaging. 2012;5(9):874–80. https://doi.org/10.1016/j.jcmg.2012.03.016 . Bakhshi H, Ambale-Venkatesh B, Yang X, Ostovaneh MR, Wu CO, Budoff M, et al. Progression of Coronary Artery Calcium and Incident Heart Failure: The Multi-Ethnic Study of Atherosclerosis. J Am Heart Assoc. 2017;6(4). https://doi.org/10.1161/jaha.116.005253 . Yared GS, Moreira HT, Ambale-Venkatesh B, Vasconcellos HD, Nwabuo CC, Ostovaneh MR, et al. Coronary Artery Calcium From Early Adulthood to Middle Age and Left Ventricular Structure and Function. Circ Cardiovasc Imaging. 2019;12(6):e009228. https://doi.org/10.1161/circimaging.119.009228 . Mitchell C, Rahko PS, Blauwet LA, Canaday B, Finstuen JA, Foster MC, et al. Guidelines for Performing a Comprehensive Transthoracic Echocardiographic Examination in Adults: Recommendations from the American Society of Echocardiography. J Am Soc Echocardiogr. 2019;32(1):1–64. https://doi.org/10.1016/j.echo.2018.06.004 . Lang RM, Badano LP, Mor-Avi V, Afilalo J, Armstrong A, Ernande L, et al. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. J Am Soc Echocardiogr. 2015;28(1):1–e3914. https://doi.org/10.1016/j.echo.2014.10.003 . Nagueh SF, Smiseth OA, Appleton CP, Byrd BF 3rd, Dokainish H, Edvardsen T, et al. Recommendations for the Evaluation of Left Ventricular Diastolic Function by Echocardiography: An Update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. J Am Soc Echocardiogr. 2016;29(4):277–314. https://doi.org/10.1016/j.echo.2016.01.011 . Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr., Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990;15(4):827–32. Crabb DW, Im GY, Szabo G, Mellinger JL, Lucey MR. Diagnosis and Treatment of Alcohol-Associated Liver Diseases: 2019 Practice Guidance From the American Association for the Study of Liver Diseases. Hepatology. 2020;71(1):306–33. https://doi.org/10.1002/hep.30866 . Royston P, Parmar MK. Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects. Stat Med. 2002;21(15):2175–97. https://doi.org/10.1002/sim.1203 . Almeida JG, Fontes-Carvalho R, Sampaio F, Ribeiro J, Bettencourt P, Flachskampf FA, et al. Impact of the 2016 ASE/EACVI recommendations on the prevalence of diastolic dysfunction in the general population. Eur Heart J - Cardiovasc Imaging. 2018;19(4):380–6. https://doi.org/10.1093/ehjci/jex252 . Chung YJ, Choi KH, Lee SH, Shin D, Hong D, Park S, et al. Prognostic Impact of Indeterminate Diastolic Function in Patients With Functionally Insignificant Coronary Stenosis. J Am Soc Echocardiogr. 2023;36(3):295–e3065. https://doi.org/10.1016/j.echo.2022.11.014 . Nicoll R, Zhao Y, Ibrahimi P, Olivecrona G, Henein M. Diabetes and Hypertension Consistently Predict the Presence and Extent of Coronary Artery Calcification in Symptomatic Patients: A Systematic Review and Meta-Analysis. Int J Mol Sci. 2016;17(9). https://doi.org/10.3390/ijms17091481 . Chang Y, Kim BK, Yun KE, Cho J, Zhang Y, Rampal S, et al. Metabolically-healthy obesity and coronary artery calcification. J Am Coll Cardiol. 2014;63(24):2679–86. https://doi.org/10.1016/j.jacc.2014.03.042 . Mortensen MB, Gaur S, Frimmer A, Bøtker HE, Sørensen HT, Kragholm KH, et al. Association of Age With the Diagnostic Value of Coronary Artery Calcium Score for Ruling Out Coronary Stenosis in Symptomatic Patients. JAMA Cardiol. 2022;7(1):36–44. https://doi.org/10.1001/jamacardio.2021.4406 . Mohammed SF, Hussain S, Mirzoyev SA, Edwards WD, Maleszewski JJ, Redfield MM. Coronary microvascular rarefaction and myocardial fibrosis in heart failure with preserved ejection fraction. Circulation. 2015;131(6):550–9. https://doi.org/10.1161/circulationaha.114.009625 . Westermann D, Lindner D, Kasner M, Zietsch C, Savvatis K, Escher F, et al. Cardiac inflammation contributes to changes in the extracellular matrix in patients with heart failure and normal ejection fraction. Circ Heart Fail. 2011;4(1):44–52. https://doi.org/10.1161/circheartfailure.109.931451 . Mansour MJ, Chammas E, Hamoui O, Honeine W, AlJaroudi W. Association between left ventricular diastolic dysfunction and subclinical coronary artery calcification. Echocardiography. 2020;37(2):253–9. https://doi.org/10.1111/echo.14580 . Haddad F, Cauwenberghs N, Daubert MA, Kobayashi Y, Bloomfield GS, Fleischman D, et al. Association of left ventricular diastolic function with coronary artery calcium score: A Project Baseline Health Study. J Cardiovasc Comput Tomogr. 2022;16(6):498–508. https://doi.org/10.1016/j.jcct.2022.06.003 . Maragiannis D, Schutt RC, Gramze NL, Chaikriangkrai K, McGregor K, Chin K, et al. Association of Left Ventricular Diastolic Dysfunction with Subclinical Coronary Atherosclerotic Disease Burden Using Coronary Artery Calcium Scoring. J Atheroscler Thromb. 2015;22(12):1278–86. https://doi.org/10.5551/jat.29454 . Castro-Diehl C, Song RJ, Mitchell GF, McManus D, Cheng S, Vasan RS, et al. Association of subclinical atherosclerosis with echocardiographic indices of cardiac remodeling: The Framingham Study. PLoS ONE. 2020;15(5):e0233321. https://doi.org/10.1371/journal.pone.0233321 . Eleid MF, Appleton CP, Lopez AG, Cha S, Hurst RT. Coronary artery plaque burden does not affect left ventricular diastolic function in asymptomatic adults with normal ejection fraction. J Am Soc Echocardiogr. 2011;24(8):909–14. https://doi.org/10.1016/j.echo.2011.03.017 . Playford D, Strange G, Celermajer DS, Evans G, Scalia GM, Stewart S, et al. Diastolic dysfunction and mortality in 436 360 men and women: the National Echo Database Australia (NEDA). Eur Heart J - Cardiovasc Imaging. 2021;22(5):505–15. https://doi.org/10.1093/ehjci/jeaa253 . Halley CM, Houghtaling PL, Khalil MK, Thomas JD, Jaber WA. Mortality Rate in Patients With Diastolic Dysfunction and Normal Systolic Function. Arch Intern Med. 2011;171(12):1082–7. https://doi.org/10.1001/archinternmed.2011.244 . Additional Declarations No competing interests reported. Supplementary Files 3.SupplementaryAppendixCACDD20240612.docx Cite Share Download PDF Status: Published Journal Publication published 28 Feb, 2025 Read the published version in BMC Medicine → Version 1 posted Editorial decision: Revision requested 08 Nov, 2024 Reviews received at journal 08 Nov, 2024 Reviews received at journal 16 Sep, 2024 Reviewers agreed at journal 04 Sep, 2024 Reviewers agreed at journal 02 Sep, 2024 Reviewers agreed at journal 02 Sep, 2024 Reviews received at journal 30 Aug, 2024 Reviewers agreed at journal 28 Aug, 2024 Reviewers invited by journal 21 Jun, 2024 Editor assigned by journal 17 Jun, 2024 Submission checks completed at journal 17 Jun, 2024 First submitted to journal 15 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-4585013","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":320532687,"identity":"e673b485-d111-4c91-a53f-8079467fe1a4","order_by":0,"name":"Ki Hong Choi","email":"","orcid":"","institution":"Samsung Medical Center, Sungkyunkwan University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ki","middleName":"Hong","lastName":"Choi","suffix":""},{"id":320532688,"identity":"2a8125a7-d8fc-4a38-a5f5-df4154fcb079","order_by":1,"name":"Danbee Kang","email":"","orcid":"","institution":"SAIHST, Sungkyunkwan 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Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAu0lEQVRIiWNgGAWjYBACxhlgygbEbDxAipY0ELOBOC0MEmDyMJgkTgvz7B7jTzdqztutbT8MtKXGJpqww+acMZPOOXY7eduZRKCWY2m5DQS1zMgxY85tuJ1sdgCohbHhMFFajD/nNpxLNjv/kHgtBtK5DQfszG4Qb0taGdAvyQlmN4C2JBDjF8MZyZs/59TY2ZudT3/44EONDRFaGjgMQHQiWGUCIeUgIM/A/gBE2xOjeBSMglEwCkYoAAA+20jUbaMkSwAAAABJRU5ErkJggg==","orcid":"","institution":"Samsung Medical Center, Sungkyunkwan University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Jeong","middleName":"Hoon","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2024-06-15 05:47:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4585013/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4585013/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12916-025-03956-9","type":"published","date":"2025-02-28T15:57:07+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60435522,"identity":"b2a58abe-7172-45a7-be60-a0421740be9e","added_by":"auto","created_at":"2024-07-16 17:23:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":10616222,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociations between CAC and LVEF (A) and E/e’ (B)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe linear p-value for CAC with LVEV was 0.47, and that with E/e' was 0.001.\u003c/p\u003e\n\u003cp\u003eAbbreviations: CAC: coronary artery calcium; LVEF, left ventricular ejection fraction.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4585013/v1/28b9d6e3d15cb42e57ffdf02.png"},{"id":60436163,"identity":"ad942dec-d44c-4069-a5f6-d1ca74adb206","added_by":"auto","created_at":"2024-07-16 17:31:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":450219,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan Meier curve for all-cause mortality by DD and CAC score\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations: CAC: coronary artery calcium; DD, diastolic dysfunction.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4585013/v1/b4f921f2685f32a251c34e93.png"},{"id":60435519,"identity":"b29fe116-8241-4679-a557-7e174577cd8c","added_by":"auto","created_at":"2024-07-16 17:23:26","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":446772,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan Meier curve for incidence of definite (A) and definite or probable (B) DD by CAC score\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations: CAC, coronary artery calcium; DD, diastolic dysfunction.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4585013/v1/3c8b7dd70cdad81c09c615f7.png"},{"id":60436164,"identity":"80ce4317-e2a9-4701-a529-c127a4845a6b","added_by":"auto","created_at":"2024-07-16 17:31:26","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1484288,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAverage trajectories of E/e’ by CAC group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTrajectories were obtained from mixed linear models for longitudinal data with random intercepts and random slopes. Models were adjusted for age, sex, BMI category, smoking status (never, ever, or missing), drinking status, diabetes, hypertension, hyperlipemia, atrial fibrillation, history of cancer, aspirin use, and statin use at baseline.\u003c/p\u003e\n\u003cp\u003eAbbreviations: BMI, body mass index; CAC: coronary artery calcium.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4585013/v1/b8103b7db603f9f73bb84ff4.png"},{"id":77622381,"identity":"ed6f3341-1068-4cf4-a0dd-9e79029a50c4","added_by":"auto","created_at":"2025-03-03 16:05:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":12478006,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4585013/v1/ebe21cc5-9c75-417c-b381-7ede3a4d0f3f.pdf"},{"id":60435521,"identity":"6fe014e2-9845-4797-894b-45aa3f2ae3af","added_by":"auto","created_at":"2024-07-16 17:23:26","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":70053,"visible":true,"origin":"","legend":"","description":"","filename":"3.SupplementaryAppendixCACDD20240612.docx","url":"https://assets-eu.researchsquare.com/files/rs-4585013/v1/085e755b7372ad69af01bcac.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of Coronary Artery Calcium on Progression of Diastolic Dysfunction: A Cohort Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLeft ventricular (LV) diastolic dysfunction (DD) is highly prevalent and represents a pattern of relaxation abnormality, leading to elevated filling pressure in the LV despite a normal ejection fraction (EF).[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] Established risk factors for DD include advanced age, obesity, hypertension, diabetes, and atrial fibrillation.[\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] The manifestation of DD is recognized to independently increase the risk of major cardiovascular events, encompassing cardiac mortality, heart failure (HF), and atherosclerotic events, even in the general population.[\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] These results emphasize the importance of early recognition and initiation of appropriate preventative treatments for DD in the subclinical stage.\u003c/p\u003e \u003cp\u003eThe coronary artery calcium (CAC) scan measured by computed tomography (CT) has become popular for individuals at risk for atherosclerotic cardiovascular disease. The CAC is strongly associated with atherosclerotic burden and predicts coronary artery disease events and mortality, regardless of age, sex, race, or atherosclerotic cardiovascular disease risk.[\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] Recently, there has been great interest in better understanding the relationship between DD and CAC. It has been shown in several studies that CAC burden or CAC progression is associated with a risk of HF with preserved ejection fraction (HFpEF), suggesting a potential connection between CAC and DD.[\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] However, there are limited data regarding the synergistic effects on mortality of DD and CAC, both of which are subclinical disease subsets in the general population. More importantly, the relationship between CAC and progression of DD over time with longitudinal follow-up is poorly understood.\u003c/p\u003e \u003cp\u003eTherefore, our study aimed to evaluate the association of CAC score with prevalence of DD assessed by resting echocardiography at baseline and to explore the combined effect of CAC and DD on mortality in the general population using a large cohort from a health screening examination program in Korea. We also sought to evaluate the incidence rates of progression of DD during follow-up according to the baseline CAC score in a longitudinal dataset.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective cohort analysis of men and women\u0026thinsp;\u0026ge;\u0026thinsp;18 years of age who underwent a comprehensive health screening exam with simultaneous echocardiography and CAC scan at the Samsung Medical Center Health Promotion Center, Republic of Korea, from January 2010 and December 2019 (N\u0026thinsp;=\u0026thinsp;15,830). We excluded 1,978 participants who had history of cardiovascular disease (N\u0026thinsp;=\u0026thinsp;571) or LVEF\u0026thinsp;\u0026lt;\u0026thinsp;50% at baseline (N\u0026thinsp;=\u0026thinsp;31). Among the eligible participants (N\u0026thinsp;=\u0026thinsp;15,228), we further excluded 35 who had missing data for lipid profile, blood pressure, and body mass index (BMI) at baseline. The final sample size was 15,193. The Institutional Review Board of Samsung Medical Center approved this study and waived the requirement for informed consent as we used only de-identified data routinely collected during health screening visits.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eEchocardiography\u003c/h2\u003e \u003cp\u003e All echocardiography measurements were performed in health screening practice in accordance with guidelines using a commercially available systems (Vivid7, GE Medical Systems, Horten, Norway; Vivid9, GE Medical Systems, Horten, Norway; SC2000, Siemens Medical Solution, Mountain View, CA, USA).[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] The inter-ventricular septum thickness, posterior wall thickness, and LV dimensions in diastole and systole were measured from M-mode images, and the LV mass (g) was calculated using the American Society of Echocardiography (ASE) and the European Association of Cardiovascular Imaging (EACVI) equation.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] LVEF was assessed using the biplane Simpson technique, M-mode, or visual estimation. Left atrial volume was measured by the biplane method using dedicated apical 4- and 2-chamber views at the end-systolic frame to avoid foreshortening. The left atrial volume index (LAVI) was calculated as left atrial volume / body surface area (mL/m\u003csup\u003e2\u003c/sup\u003e). Trans-mitral inflow velocities (E and A) were obtained by pulsed-wave Doppler analysis performed in the apical-4 chamber plane. Tissue Doppler imaging was used to obtain early (e\u0026rsquo;) and late (a\u0026rsquo;) atrial diastolic annular velocities in the apical 4-chamber view. Peak tricuspid regurgitation (TR) velocity was recorded using continuous Doppler.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eDefinitions of DD\u003c/h2\u003e \u003cp\u003eDD was defined according to the 2016 ASE/EACVI recommendations.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] Four main echocardiographic parameters were considered, and abnormal cutoffs were as follows: septal e\u0026rsquo; \u0026lt;7 cm/s, septal E/e\u0026rsquo; \u0026gt;15, LAVI\u0026thinsp;\u0026gt;\u0026thinsp;34 mL/m\u003csup\u003e2\u003c/sup\u003e, and TR velocity\u0026thinsp;\u0026gt;\u0026thinsp;2.8 m/s. The presence of at least 3 of 4 abnormal DD parameters were mandatory to classify definite DD, even if some of the four diastolic parameters were missing. Similarly, the presence of at least 2 of 4 abnormal DD parameters was evaluated as a separate binary variable and defined as \u0026lsquo;definite or probable DD.\u0026rsquo;[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] Each DD index was also evaluated as a continuous variable to complement the binary assessment of DD using previously determined cutoffs.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCoronary CT scans\u003c/h2\u003e \u003cp\u003eImaging data for the evaluation of CAC were acquired using Brilliance 40 (Philips Medical Systems), VCT LightSpeed 64 (GE Healthcare), or Discovery 750HD (GE Healthcare) multidetector CT scanners. The analysis of the scans was performed on Extended Brilliance Workspace (Philips Medical Systems) or Advantage (GE Healthcare) workstations. CAC scores were calculated as described by Agatston et al.[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eAt each visit, demographic characteristics, smoking status, alcohol consumption, medical history, and medication use were collected through standardized, self-administered questionnaires. Smoking status was categorized into never, former, or current smoker. Alcohol consumption was categorized into none, light (\u0026lt;\u0026thinsp;10 g/day in women and \u0026lt;\u0026thinsp;20 g/day in men), moderate (10\u0026ndash;\u0026lt;40 g/day in women and 20\u0026ndash;\u0026lt;60 g/day in men), and heavy (\u0026ge;\u0026thinsp;40 g/day in women and \u0026ge;\u0026thinsp;60 g/day in men).[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] Height, weight, waist circumference, and sitting blood pressure were measured by trained nurses. BMI was calculated as weight in kilograms divided by height in meters squared. Hypertension was defined as a systolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;140 mmHg, a diastolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;90mmHg, a self-reported history of hypertension, or current use of anti-hypertensive medications. Diabetes mellitus was defined as a fasting serum glucose\u0026thinsp;\u0026ge;\u0026thinsp;126mg/dL, a self-reported history of diabetes, or self-reported use of insulin or oral hypoglycemic medications.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eMortality\u003c/h2\u003e \u003cp\u003eMortality data were obtained from a health screening center registry through December 31, 2019, ascertained by the Korean Ministry of the Interior and Safety.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics were used to summarize the characteristics of participants by CAC category. To test for linear trends, we included the median value of each CAC category as a continuous variable in the regression models. To compare the parameters of echocardiography by CAC, we conducted multivariable linear regression models to control age, sex, BMI, smoking status, drinking status, diabetes, hypertension, hyperlipemia, statin use, and aspirin use. To evaluate the association between CAC category and the prevalence of definite or probable DD, we calculated its prevalence and 95% confidence interval (CI) for definite or probable DD by CAC category. We also used log-binomial regression to estimate adjusted prevalence ratios and 95% CIs after adjusting for age, sex, BMI, smoking status, alcohol consumption, diabetes, hypertension, hyperlipidemia, statin use, and aspirin use.\u003c/p\u003e \u003cp\u003eTo estimate the synergistic effects of CAC and DD on mortality, we generated 4 groups of CAC\u0026thinsp;\u0026lt;\u0026thinsp;100 without definite DD, CAC\u0026thinsp;\u0026lt;\u0026thinsp;100 with definite DD, CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 without definite DD, and CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 with definite DD. Participants were followed from the time of their first health screening exam until death or December 31, 2019, whichever came first. We used a proportional hazards model to assess the associations between the 4 groups at baseline and all-cause mortality.\u003c/p\u003e \u003cp\u003eParticipants without definite or probable DD at baseline were followed for development of definite or probable DD using all available echocardiography until the last available echocardiography follow-up at the time of data extraction (31 December 2019). Since the development of DD occurred at an unknown time point between the visit of detection and the previous visit (interval censoring), we used a flexible parametric proportional hazards model to assess the association between the CAC status at baseline and the development of DD.[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] Since participants in our analyses had to have undergone at least 2 screening visits (N\u0026thinsp;=\u0026thinsp;5,706), we used inverse probability weights (IPWs) to correct for potential selection bias. The IPWs of study participants were reweighted so that participants who were similar to those lost to follow-up after the first echocardiography were assigned a higher weight. IPWs were obtained from a logistic regression model including all those screened with at least one echocardiography and with similar selection criteria to those used in this analysis (N\u0026thinsp;=\u0026thinsp;9,487).\u003c/p\u003e \u003cp\u003eWe also compared the quantitative trajectories of e\u0026rsquo; and E/e\u0026rsquo; by CAC status at baseline using linear mixed models for longitudinal data with random intercepts and random slopes. We estimated the changes of e\u0026rsquo; and E/e\u0026rsquo; (with 95% CIs) relative to those of participants with CAC\u0026thinsp;=\u0026thinsp;0.\u003c/p\u003e \u003cp\u003eAll reported P values were two-sided, and the significance level was set to 0.05. All analyses were performed using STATA version 16 (StataCorp LP, College Station, TX, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Characteristics\u003c/h2\u003e \u003cp\u003eThe mean (standard deviation) age of study participants was 55.8 (8.6) years. The median CAC score at baseline was 0 (52.6% participants had a CAC score of 0). The prevalence of CAC by category was categorized as follows: 52.6% had a score of 0, 30.7% had a 0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100, and 16.7% had a CAC\u0026thinsp;\u0026ge;\u0026thinsp;100. Age, male, current smoker, and metabolically unhealthy were positively associated with CAC (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of study participants by CAC group\u003c/p\u003e \u003c/div\u003e \u003c/caption\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=\"char\" char=\".\" 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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAC\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCAC\u0026thinsp;\u0026ge;\u0026thinsp;100\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;7,995)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;4,661)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;2,537)\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\u003e52.9 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.2 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62.1 (9.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex, male\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6041 (75.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3902 (83.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2227 (87.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI, kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.0 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.7 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.0 (2.8)\u003c/p\u003e \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\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\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3067 (38.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1456 (31.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e674 (26.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4572 (57.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2994 (64.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1727 (68.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e356 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e211 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e136 (5.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrinking status\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\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1759 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e998 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e562 (22.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLittle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4380 (54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2441 (52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1257 (49.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1007 (12.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e685 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e358 (14.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e506 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e310 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e223 (8.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e343 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e227 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e137 (5.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\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\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e727 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e819 (17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e719 (28.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2392 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2222 (47.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1580 (62.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4198 (52.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3101 (66.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1845 (72.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtrial fibrillation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26 (1.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e463 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e373 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e252 (9.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory findings\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\u003eLVEF, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.6 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64.9 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65.2 (5.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNT-proBNP, pg/mL (N\u0026thinsp;=\u0026thinsp;8,308)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.6 (45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.9 (58.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.8 (135.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol, mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e193.8 (34.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e192.5 (36.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e179.8 (37.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C, mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125.6 (31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125.2 (33.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e112.8 (33.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C, mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.6 (15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54.2 (14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.9 (14.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehsCRP, mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1 (0.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipoprotein (a), mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.6 (17.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.3 (19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.1 (22.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine, mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9 (0.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedication\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\u003eStatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e891 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1078 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e880 (34.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e442 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e712 (15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80 (3.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eValues are mean (SD), median (IQR), or number (%).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAll P for trends comparing baseline characteristics of the three groups were \u0026lt;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: BMI, body mass index; CAC: coronary artery calcium; HDL-C, high-density lipoprotein cholesterol, hsCRP, high-sensitivity C-reactive protein; IQR, interquartile range; LDL-C, low-density lipoprotein cholesterol; LVEF, left ventricular ejection fraction; NT-proBNP, N-Terminal pro-B-type natriuretic peptide; SD, standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAssociations Between CAC and Baseline Echocardiographic Parameters\u003c/h2\u003e \u003cp\u003eIn terms of the parameters of echocardiography, the CAC was linearly associated with lower septal e\u0026prime;, higher E/e\u0026rsquo;, LV mass, and TR velocity among the groups (\u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e). On the other hand, CAC showed no linear association with E velocity. When performing association analysis between CAC as a continuous variable and LVEF or E/e\u0026rsquo;, the linear adjusted p-value for LVEF was 0.47, but the linear p-value was 0.001 for E/e' (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). At baseline, the prevalence of definite and probable DD was 2.6%, and 12.2%, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe prevalence ratio for definite DD was 1.34 (95% CI: 0.98\u0026ndash;1.69) and 1.72 (95% CI: 1.23\u0026ndash;2.22) in the groups of 0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100 and CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 compared to the CAC\u0026thinsp;=\u0026thinsp;0 group, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The prevalence ratio for definite or probable DD when comparing the groups of 0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100 and CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 with the CAC\u0026thinsp;=\u0026thinsp;0 group was 1.34 (95% CI: 0.98\u0026ndash;1.70) and 1.83 (95% CI: 1.31\u0026ndash;2.36), respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Higher CAC score was positively associated with the prevalence of definite and probable DD regardless of age (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence ratio for incidence of diastolic dysfunction by CAC score\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAC score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of DD cases (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted prevalence ratio (95% CI)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDefinite DD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAC\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e108 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e145 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.34 (0.98, 1.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAC\u0026thinsp;\u0026ge;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e154 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.72 (1.23, 2.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDefinite or probable DD\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAC\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e555 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e654 (14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.34 (0.98, 1.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAC\u0026thinsp;\u0026ge;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e648 (25.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83 (1.31, 2.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e*\u003c/sup\u003eAdjusted for age, sex, BMI category, smoking status (never, ever, or missing), drinking status, diabetes, hypertension, hyperlipemia, atrial fibrillation, history of cancer, aspirin use, and statin use at baseline.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviations: BMI, body mass index; CAC: coronary artery calcium; CI, confidence interval; DD, diastolic dysfunction.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEffects of CAC and DD on Mortality\u003c/h2\u003e \u003cp\u003eFrom baseline to date at vital status confirmation (median follow-up was 5.1 years, maximum 9.5 years), 117 individuals died. The CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 with definite DD group at baseline showed the highest cumulative mortality rate among 4 groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Compared with CAC\u0026thinsp;\u0026lt;\u0026thinsp;100 without definite DD, the adjusted HRs (95% CIs) for all-cause mortality of CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 without definite DD and CAC\u0026thinsp;\u0026lt;\u0026thinsp;100 with definite DD were 2.56 (95% CI: 1.67\u0026ndash;3.94) and 3.08 (95% CI: 1.28\u0026ndash;7.39), respectively. The risk of mortality was highest in patients with CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 and definite DD (adjusted HR:3.91, 95% CI: 1.68\u0026ndash;9.10, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHazard ratio for mortality by CAC score and diastolic dysfunction\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8-year cumulative mortality,% (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted hazard ratio (95% CI)\u003csup\u003e*\u003c/sup\u003e\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\u003eCAC\u0026thinsp;\u0026lt;\u0026thinsp;100 without definite DD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.96 (0.68, 1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCAC\u0026thinsp;\u0026ge;\u0026thinsp;100 without definite DD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.62 (2.56, 5.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.56 (1.67, 3.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCAC\u0026thinsp;\u0026lt;\u0026thinsp;100 with definite DD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.27 (1.47, 7.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.08 (1.28, 7.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCAC\u0026thinsp;\u0026ge;\u0026thinsp;100 with definite DD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.94 (4.51, 21.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.91 (1.68, 9.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e*\u003c/sup\u003eAdjusted for age, sex, BMI, smoking status (never, ever, or missing), drinking status, diabetes, hypertension, hyperlipemia, atrial fibrillation, history of cancer, aspirin use, and statin use at baseline.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviations: BMI, body mass index; CAC: coronary artery calcium; CI, confidence interval; DD, diastolic dysfunction.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAssociation Between CAC and Progression of DD\u003c/h2\u003e \u003cp\u003eAmong the participants, those without definite or probable DD at the time of CAC measurement who had at least two available echocardiographic measurements were 4,938 and 5,221, respectively. The average duration of follow-up was 4.1 years (maximum 9.9 years; average number of visits per participant was 4.5). During the follow-up period, the annual average incidence rates of definite DD in participants with CAC\u0026thinsp;=\u0026thinsp;0, 0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100, and CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 at baseline were 0.46, 0.91 and 1.91, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The multivariable adjusted hazard ratios (HRs) of definite DD (95% CI) for comparing participants with CAC\u0026thinsp;=\u0026thinsp;0 to those with 0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100 and CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 were 1.32 (95% CI: 0.90\u0026ndash;1.95) and 1.95 (95% CI: 1.16\u0026ndash;3.26), respectively (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The annual average incidence rates of definite or probable DD in participants with CAC\u0026thinsp;=\u0026thinsp;0, 0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100, and CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 were 1.82, 3.08 and 5.23, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). The multivariable adjusted HRs of definite or probable DD (95% CI) comparing participants with CAC\u0026thinsp;=\u0026thinsp;0 to those with 0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100 and CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 were 1.17 (95% CI: 0.96\u0026ndash;1.44) and 1.46 (95% CI: 1.13\u0026ndash;1.88), respectively (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHazard ratios for incidence of diastolic dysfunction by CAC score among participants without dysfunction at baseline\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of events\u003c/p\u003e \u003cp\u003e(Incidents% per a year)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted hazard ratio (95% CI)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDefinite DD (N\u0026thinsp;=\u0026thinsp;5,221)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAC\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56 (0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69 (0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.32 (0.90, 1.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAC\u0026thinsp;\u0026ge;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23 (1.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.95 (1.16, 3.26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDefinite or probable DD (N\u0026thinsp;=\u0026thinsp;4,938)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAC\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e217 (1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e218 (3.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.17 (0.96, 1.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAC\u0026thinsp;\u0026ge;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e171 (5.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.46 (1.13, 1.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e*\u003c/sup\u003eAdjusted for age, sex, BMI, smoking status (never, ever, or missing), drinking status, diabetes, hypertension, hyperlipemia, atrial fibrillation, history of cancer, aspirin use, and statin use at baseline.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eThe hazard ratio was estimated using inverse probability weighting (see text for details) for generalizability.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviations: BMI, body mass index; CAC, coronary artery calcium; CI, confidence interval; DD, diastolic dysfunction.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong participants without definite or probable DD, the 0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100 (difference: 0.03, 95% CI: 0.00-0.06, P\u0026thinsp;=\u0026thinsp;0.042) and CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 (difference: 0.06; 95% CI: 0.02\u0026ndash;0.10, P\u0026thinsp;=\u0026thinsp;0.003) groups showed faster increasing trends of E/e\u0026rsquo; compared to the CAC\u0026thinsp;=\u0026thinsp;0 group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe current study investigated the relationship between CAC score and prevalence of DD, their effects on mortality, and the progression of DD over time according to CAC score in a general population using a large longitudinal cohort from a health screening examination program (\u003cb\u003eCentral Illustration\u003c/b\u003e). The principal findings of this study were as follows. First, the prevalence ratio of definite or probable DD was significantly higher in participants with CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 compared to those without CAC, even after adjustment for confounding factors including age. In particular, CAC was significantly correlated with baseline E/e\u0026rsquo; but not with LVEF. Second, after stratification according to CAC score and definite DD, individuals with CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 and definite DD showed the highest risk of mortality. Third, in longitudinal analysis, significant CAC (\u0026ge;\u0026thinsp;100) was associated with accelerated progression in DD over time, with more rapid elevation of LV filling pressure as measured by E/e\u0026rsquo;.\u003c/p\u003e \u003cp\u003eThe historical inconsistency in defining and grading diastolic dysfunction has presented a formidable challenge for clinicians. As a result, the 2016 ASE/EACVI was newly recommended for diagnosis of DD to provide a streamlined stepwise hierological assessment using four key variables in the absence of myocardial disease (e\u0026rsquo; velocity, E/e\u0026rsquo; ratio, TR velocity, and LAVI).[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] The application of this guideline resulted in a much lower prevalence of DD compared to previous recommendations.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] Furthermore, a substantial portion of individuals have \u0026lsquo;indeterminate\u0026rsquo; diastolic function, indicating reduced sensitivity of the diagnostic criteria. Given a previous report that indeterminate DD was not a benign disease and showed a significantly increased risk of cardiovascular death or HF readmission compared to no evidence of DD,[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] we defined participants categorized as indeterminate (2 of 4 abnormal DD parameters) as \u0026lsquo;probable DD\u0026rsquo; and used this as one of the outcomes.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eAssociations between CAC and DD and their Effects on Mortality\u003c/h2\u003e \u003cp\u003eBoth CAC and DD were associated with advanced age, hypertension, diabetes mellitus, and obesity.[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] These comorbidities are believed to trigger a systemic proinflammatory state, leading to coronary microvascular dysfunction, followed by structural and functional alterations such as myocardial inflammation and interstitial fibrosis,[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and these changes may affect both LV diastolic stiffness and formation of calcified coronary plaques. In this regard, several previous studies have been conducted to evaluate the association between CAC and DD.[\u003cspan additionalcitationids=\"CR31 CR32 CR33\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] However, none of these studies had a large sample size. Therefore, the association between CAC and DD is currently inconclusive, with conflicting results after adjusting for common shared comorbidities. The current study found an independent association between CAC score and DD, even after adjustment for various comorbidities in a large cohort of a general population without previous history of cardiovascular disease. Interestingly, CAC score was continuously correlated with baseline E/e\u0026rsquo;. In addition, higher CAC score was associated with the prevalence of DD irrespective of age category. These results imply that CAC score offers incremental information beyond traditional risk factors for predicting DD or high filling pressure.\u003c/p\u003e \u003cp\u003eThe presence of both CAC and DD is an independent predictor of cardiovascular outcomes in numerous cohorts.[\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] However, there is a scarcity of data regarding the effects on mortality when patients have both subclinical CAC and DD. In the current study, participants with either DD or a significant CAC score (\u0026ge;\u0026thinsp;100) had an increased risk of all-cause mortality during follow-up compared to those without DD and significant CAC. More important, the integration of subclinical parameters including CAC and DD further increased the risk of all-cause mortality in the general population. These results indicate that subclinical CAC and DD, even without definitive symptoms or signs of ischemia or HF, are independent risk factors of all-cause mortality. Furthermore, rapid detection of and response to pathophysiological changes, such as a chronic inflammatory process that affects both CAC and DD, is thought to be necessary to reduce the long-term mortality rate in the general population.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eProgression of DD According to Presence of CAC\u003c/h2\u003e \u003cp\u003eAlthough CAC and DD share some pathophysiology and risk factors, their independent effects on each other are not well characterized. Therefore, we hypothesized that participants with a significant CAC score at baseline have more highly accelerated progression of DD over time than those without CAC, independent of other clinical characteristics. If substantiated, this would establish CAC as a crucial biomarker for preclinical HFpEF, enhancing its utility in guiding more effective preventive interventions. In our longitudinal dataset of participants with a significant CAC score and no DD at baseline, 1.9% developed definite and 5.2% developed definite or probable DD each year. This was 2.0 and 1.5 times more frequent compared to participants without DD, respectively, independent of age, sex, BMI, or other potential confounders including comorbidities. Furthermore, a significant CAC score was associated with more rapid increase of E/e\u0026rsquo; during follow-up than in patients without CAC. To our knowledge, this is the first study to confirm that significant CAC affects the progression of DD independently of other clinical factors. These findings suggest that individuals with higher CAC scores are at an increased risk of developing subclinical or overt HFpEF, emphasizing the need for early recognition by active surveillance and timely intervention.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eSeveral limitations should be considered in the interpretation of our findings. First, this study was derived from retrospective observational data; therefore, unmeasured confounding factors could have influenced the study results. Second, the severity of symptoms related to DD or CAC was not quantified in this study. Third, additional echocardiographic parameters from the 2016 ASE/EACVI recommendations, such as pulmonary venous flow or deceleration time or LV strain, were not included in the current study and could provide helpful guidance in the accurate assessment of diastolic function. Fourth, in the longitudinal dataset, there was a loss of sample size in the analysis of DD progression according to CAC by requiring participants to have undergone at least two echocardiograms. However, there were near 5000 participants in whom progression of DD was confirmed; therefore, the number of samples was sizable. Fifth, the follow-up duration was not standardized, potentially leading to variations in the timing of subsequent evaluations. Consequently, patients with more severe conditions might have undergone more frequent assessments, influencing the diagnosis of DD during follow-up. Sixth, our study was conducted in Korean men and women attending regular health screening examinations, and our findings may not be generalizable to other populations, particularly other ages, or race/ethnicity.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn a general population that underwent a comprehensive health screening exam with simultaneous echocardiography and CAC scan, there was strong association between CAC and DD. If patients had both subclinical parameters, their risk of mortality further increased compared to those who had only one. Moreover, the presence of a significant CAC score (\u0026ge;\u0026thinsp;100) might affect the progression of DD independent of other clinical factors. These findings highlight the potential of CAC as a biomarker for preclinical HFpEF and the importance of considering subclinical parameters for risk assessment in the general population.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican Society of Echocardiography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebody mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecoronary artery calcium\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\"\u003eCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecomputed tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ediastolic dysfunction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEACVI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEuropean Association of Cardiovascular Imaging\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eejection fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eheart failure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHFpEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eheart failure with preserved ejection fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehazard ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIPW\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einverse probability weights\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLAVI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eleft atrial volume index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eleft ventricle\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etricuspid regurgitation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement:\u003c/strong\u003e None\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding/Support\u003c/strong\u003e: None\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Disclosures\u003c/strong\u003e:\u0026nbsp;The authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReproducible Research Statement:\u0026nbsp;\u003c/strong\u003eAnonymized patient-level data will be made available by the corresponding author in response to reasonable requests. Consent was not obtained for data sharing, but the presented data are anonymized, and the risk of identification is minimal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e Drs. Ki Hong Choi, Danbee Kang, Soo Jin Cho, and Jeong Hoon Yang had full access to all data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConceived and designed the research:\u003c/em\u003e Ki Hong Choi, Danbee Kang, Soo Jin Cho,\u0026nbsp;Jeong Hoon Yang\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcquisition, analysis, or interpretation of data\u003c/em\u003e: Ki Hong Choi, Danbee Kang\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDrafting of the manuscript\u003c/em\u003e: Ki Hong Choi, Danbee Kang, Soo Jin Cho,\u0026nbsp;Jeong Hoon Yang\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMade critical revision of the manuscript for key intellectual content:\u003c/em\u003e Seung Hun Lee, Darae Kim, Sung Won Cho, Soo-Hee Choi, Taek Kyu Park, Joo Myung Lee, Young Bin Song, Joo-Yong Hahn, Seung-Hyuk Choi, Hyeon-Cheol Gwon, Jeong Hoon Yang\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e: Danbee Kang\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNagueh Sherif F. 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Arch Intern Med. 2011;171(12):1082\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/archinternmed.2011.244\u003c/span\u003e\u003cspan address=\"10.1001/archinternmed.2011.244\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\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":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmed","sideBox":"Learn more about [BMC Medicine](http://bmcmedicine.biomedcentral.com/)","snPcode":"12916","submissionUrl":"https://submission.nature.com/new-submission/12916/3","title":"BMC Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"coronary artery calcium, diastolic dysfunction, mortality, echocardiography, heart failure","lastPublishedDoi":"10.21203/rs.3.rs-4585013/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4585013/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe relationship between coronary artery calcium (CAC) and progression of diastolic dysfunction (DD) during longitudinal follow-up is uncertain. This study aimed to investigate the prevalence and progression of DD according to severity of CAC and understand their synergistic effect on mortality.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis was a population-based cohort study. All 15,193 adults who underwent a health screening exam with simultaneous echocardiography and CAC scan were enrolled. Definite DD (\u0026ge;\u0026thinsp;3/4 abnormal parameters for DD [e\u0026rsquo;, E/e\u0026rsquo;, tricuspid regurgitation-velocity, and left atrial volume index) and definite or probable DD (\u0026ge;\u0026thinsp;2/4) were defined. All-cause mortality was assessed based on the CAC and DD.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong the population, 7,995 participants (52.6%) had CAC\u0026thinsp;=\u0026thinsp;0; 4,661 (30.7%) had 0\u0026thinsp;\u0026lt;\u0026thinsp;CAC\u0026thinsp;\u0026lt;\u0026thinsp;100; and 2,537 (16.7%) had CAC\u0026thinsp;\u0026ge;\u0026thinsp;100. The prevalence ratios for definite (adjusted-ratio:1.72, 95% CI:1.23\u0026ndash;2.22) and definite or probable DD (adjusted-ratio:1.83, 95% CI:1.31\u0026ndash;2.36) were significantly higher in individuals with CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 than in those with CAC\u0026thinsp;=\u0026thinsp;0. There was significant linear association of CAC with E/e\u0026rsquo; (adjusted p-for linearity\u0026thinsp;=\u0026thinsp;0.001). Compared with CAC\u0026thinsp;\u0026lt;\u0026thinsp;100 without definite DD, the adjusted HRs with 95% CI for mortality of CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 without definite DD, CAC\u0026thinsp;\u0026lt;\u0026thinsp;100 with definite DD, and CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 with definite DD were 2.56 (95% CI:1.67\u0026ndash;3.94), 3.08 (95% CI:1.28\u0026ndash;7.39), and 3.91 (95% CI:1.68\u0026ndash;9.10). Among participants without DD at CAC measurement who had at least two echocardiographic measurements, the presence of significant CAC (\u0026ge;\u0026thinsp;100) was significantly associated with accelerated progression in definite DD over time (adjusted-HR:1.46, 95% CI:1.13\u0026ndash;1.88), with more rapid elevation of E/e\u0026rsquo; during follow-up (difference:0.06, 95% CI:0.02\u0026ndash;0.10, p\u0026thinsp;=\u0026thinsp;0.003).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn the general population, there was a significant relationship between CAC and prevalence of DD, and both subclinical parameters were associated with increased mortality. Moreover, CAC\u0026thinsp;\u0026ge;\u0026thinsp;100 significantly affects the progression of DD independently of other clinical factors.\u003c/p\u003e","manuscriptTitle":"Impact of Coronary Artery Calcium on Progression of Diastolic Dysfunction: A Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-16 17:23:21","doi":"10.21203/rs.3.rs-4585013/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-08T12:46:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-08T12:40:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-16T15:14:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"334833678557013198879265807765866711980","date":"2024-09-04T14:32:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"58842745146410626042026067994828848654","date":"2024-09-02T16:09:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13433795221691148162709320710353562039","date":"2024-09-02T07:21:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-30T11:09:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"225967992556630178925995287082244775279","date":"2024-08-28T10:44:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-21T08:25:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-17T08:59:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-17T08:38:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medicine","date":"2024-06-15T05:45:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmed","sideBox":"Learn more about [BMC Medicine](http://bmcmedicine.biomedcentral.com/)","snPcode":"12916","submissionUrl":"https://submission.nature.com/new-submission/12916/3","title":"BMC Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"821856d3-aecc-49eb-a5d5-5a1a3de8378e","owner":[],"postedDate":"July 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-03T15:59:42+00:00","versionOfRecord":{"articleIdentity":"rs-4585013","link":"https://doi.org/10.1186/s12916-025-03956-9","journal":{"identity":"bmc-medicine","isVorOnly":false,"title":"BMC Medicine"},"publishedOn":"2025-02-28 15:57:07","publishedOnDateReadable":"February 28th, 2025"},"versionCreatedAt":"2024-07-16 17:23:21","video":"","vorDoi":"10.1186/s12916-025-03956-9","vorDoiUrl":"https://doi.org/10.1186/s12916-025-03956-9","workflowStages":[]},"version":"v1","identity":"rs-4585013","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4585013","identity":"rs-4585013","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}