The ACC/AHA 2013 pooled cohort equations compared to a Korean Risk Prediction Model for atherosclerotic cardiovascular disease

Effect of lipid-lowering therapy on carotid plaque burden in older adults

BACKGROUND

Little is known about the benefits of lipid-lowering medications in those age ≥ 75 years. We assessed the effect of lipid-lowering medications on progression to severe atherosclerosis in patients age > 75.

METHODS

Data was retrospectively obtained from the Stroke Prevention & Atherosclerosis Research Centre, Canada. Atherosclerosis burden was measured as carotid total plaque area (TPA), a powerful predictor of cardiovascular risk. Survival time free of severe atherosclerosis (SFSA) was defined as the period when TPA remained <1.19 cm2. Kaplan-Meier, multiple Cox proportional hazard and hierarchical mixed-effect models were used to determine the effects of lipid-lowering medications on progression to severe atherosclerosis.

RESULTS

In total 1404 cases (mean age 81 ± 4 years; women 52%) were included. Those taking lipid-lowering medications were more likely to have a history of diabetes and a higher burden of atherosclerosis at baseline. In Kaplan-Meier analysis, the SFSA was significantly longer in those receiving lipid-lowering therapy. In multivariable-adjusted analyses, those not receiving lipid lowering therapy (irrespective of their vascular disease at baseline) were more likely to have TPA > 1.19 cm2 (hazard ratio (HR) = 1.37, 95% confidence interval (CI): 1.09,0.71). Similar findings were observed in mixed effects models when plaque progression was defined as any change >0.05 cm2 per year (odds ratio (OR):2.17, 95% CI:1.38,3.57).

CONCLUSION

Lipid-lowering therapy is effective in controlling the burden of atherosclerosis among older adults with and without vascular disease. The measurement of plaque burden can guide selection and follow-up of those who may benefit from treatment.

A risk stratification model modified from the U.S. guideline could be applied in an Asian population with or without ASCVD: Validation study

BACKGROUND

This study aimed to evaluate the performance of a modified U.S. (MUS) model for risk prediction of cardiovascular (CV) events in Asian patients and compare it to European and Japanese models.

METHODS

The MUS model, based on the US ACC/AHA 2018 lipid treatment guideline, was employed to stratify patients under primary or secondary prevention. Two multi-center prospective observational registry cohorts, T-SPARCLE and T-PPARCLE, were used to validate the scoring system, and the primary outcome was the time to first occurrence/recurrence of major adverse cardiac events (MACEs). The MUS model's performance was compared to other models from Europe and Japan.

RESULTS

A total of 10,733 patients with the mean age of 64.2 (SD: 11.9) and 36.5% female were followed up for a median of 5.4 years. The MUS model was validated, with an AUC score of 0.73 (95% CI 0.68-0.78). The European and Japanese models had AUC scores ranging from 0.6 to 0.7. The MUS model categorized patients into four distinct CV risk groups, with hazard ratios (HRs) as follows: very high- vs. high-risk group (HR = 1.91, 95% CI 1.53-2.39), high- vs. moderate-risk group (HR = 2.08, 95% CI 1.60-2.69), and moderate- vs. low-risk group (HR = 3.14, 95% CI 1.63-6.03). After adjusting for the MUS model, a history of atherosclerotic vascular disease (ASCVD) was not a significant predictor of adverse cardiovascular outcomes within each risk group.

CONCLUSION

The MUS model is an effective tool for risk stratification in Asian patients with and without ASCVD, accurately predicting MACEs and performing comparably or better than other established risk models. Our findings suggest that patient management should focus on background risk factors instead of solely on primary or secondary prevention.

Evaluating cardiovascular disease risk stratification using multiple-polygenic risk scores and pooled cohort equations: insights from a 17-year longitudinal Korean cohort study

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, caused by a complex interplay of genetic and environmental factors. This study aimed to evaluate the combined efficacy of multi-polygenic risk scores and pooled cohort equations (PCE) for predicting future CVD risks in the Korean population. In this longitudinal study, 7,612 individuals from the Ansan and Ansung cohorts were analyzed over a 17-year follow-up period. The participants were genotyped using the Korea Biobank Array, and quality-controlled genetic data were subjected to imputation analysis. The weighted sum of the PRSs (wPRSsum) was calculated using PRS-CS with summary statistics from myocardial infarction, ischemic stroke, coronary artery disease, and hypertension genome-wide association studies. The recalibrated PCE was used to assess clinical risk, and the participants were stratified into risk groups based on the wPRSsum and PCE. Associations between these risk scores and incident CVD were evaluated using Cox proportional hazards models and Kaplan-Meier analysis. The wPRSsum approach showed a significant association with incident CVD (HR = 1.15, p = 7.49 × 10-5), and the top 20% high-risk genetic group had an HR of 1.50 (p = 5.04 × 10-4). The recalibrated PCE effectively differentiated between the low and high 10-year CVD risk groups, with a marked difference in survival rates. The predictive models constructed using the wPRSsum and PCE demonstrated a slight improvement in prediction accuracy, particularly among males aged <55 years (C-index = 0.640). We demonstrated that while the integration of wPRSsum with PCE did not significantly outperform the PCE-only model (C-index: 0.703 for combined and 0.704 for PCE-only), it provided enhanced stratification of CVD risk. The highest risk group, identified through the combination of high wPRSsum and PCE scores, exhibited an HR of 4.99 for incident CVD (p = 1.45 × 10-15). These findings highlight the potential of integrating genetic risk assessments with traditional clinical tools for effective CVD risk stratification. Although the addition of wPRSsum to the PCE provided a marginal predictive improvement, it proved valuable in identifying high-risk individuals and supporting personalized treatment strategies. This study reinforces the utility of multi-PRS in conjunction with clinical risk assessment tools, paving the way for more tailored approaches for CVD prevention and management in diverse populations.

Association between deep learning measured retinal vessel calibre and incident myocardial infarction in a retrospective cohort from the UK Biobank

BACKGROUND

Cardiovascular disease is a leading cause of global death. Prospective population-based studies have found that changes in retinal microvasculature are associated with the development of coronary artery disease. Recently, artificial intelligence deep learning (DL) algorithms have been developed for the fully automated assessment of retinal vessel calibres.

METHODS

In this study, we validate the association between retinal vessel calibres measured by a DL system (Singapore I Vessel Assessment) and incident myocardial infarction (MI) and assess its incremental performance in discriminating patients with and without MI when added to risk prediction models, using a large UK Biobank cohort.

RESULTS

Retinal arteriolar narrowing was significantly associated with incident MI in both the age, gender and fellow calibre-adjusted (HR=1.67 (95% CI: 1.19 to 2.36)) and multivariable models (HR=1.64 (95% CI: 1.16 to 2.32)) adjusted for age, gender and other cardiovascular risk factors such as blood pressure, diabetes mellitus (DM) and cholesterol status. The area under the receiver operating characteristic curve increased from 0.738 to 0.745 (p=0.018) in the age-gender-adjusted model and from 0.782 to 0.787 (p=0.010) in the multivariable model. The continuous net reclassification improvements (NRIs) were significant in the age and gender-adjusted (NRI=21.56 (95% CI: 3.33 to 33.42)) and the multivariable models (NRI=18.35 (95% CI: 6.27 to 32.61)). In the subgroup analysis, similar associations between retinal arteriolar narrowing and incident MI were observed, particularly for men (HR=1.62 (95% CI: 1.07 to 2.46)), non-smokers (HR=1.65 (95% CI: 1.13 to 2.42)), patients without DM (HR=1.73 (95% CI: 1.19 to 2.51)) and hypertensive patients (HR=1.95 (95% CI: 1.30 to 2.93)) in the multivariable models.

CONCLUSION

Our results support DL-based retinal vessel measurements as markers of incident MI in a predominantly Caucasian population.

Sex differences in the applicability of Western cardiovascular disease risk prediction equations in the Asian population

AIMS

Cardiovascular diseases (CVDs) are the most common cause of death, but they can be effectively managed through appropriate prevention and treatment. An important aspect in preventing CVDs is assessing each individual's comprehensive risk profile, for which various risk engines have been developed. The important keys to CVD risk engines are high reliability and accuracy, which show differences in predictability depending on disease status or race. Framingham risk score (FRS) and the atherosclerotic cardiovascular disease risk equations (ASCVD) were applied to the Korean population to assess their suitability.

METHODS

A retrospective cohort study was conducted using National Health Insurance Corporation sample cohort from 2003 to 2015. The enrolled participants over 30 years of age and without CVD followed-up for 10 years. We compared the prediction performance of FRS and ASCVD and calculated the relative importance of each covariate.

RESULTS

The AUCs of FRS (men: 0.750; women: 0.748) were higher than those of ASCVD (men: 0.718; women: 0.727) for both sexes (Delong test P <0.01). Goodness of fits (GOF) were poor for all models (Chi-square P < 0.001), especially, underestimation of the risk was pronounced in women. When the men's coefficients were applied to women's data, AUC (0.748; Delong test P<0.01) and the GOF (chi-square P = 0.746) were notably improved in FRS. Hypertension was found to be the most influential variable for CVD, and this is one of the reasons why FRS, having the highest relative weight to blood pressure, showed better performance.

CONCLUSION

When applying existing tools to Korean women, there was a noticeable underestimation. To accurately predict the risk of CVD, it was more appropriate to use FRS with men's coefficient in women. Moreover, hypertension was found to be a main risk factor for CVD.

Association between toothbrushing and cardiovascular risk factors: a cross-sectional study using Korean National Health and Nutrition Examination Survey 2015-2017

BACKGROUND

Previous studies have suggested that frequent toothbrushing is associated with a lower risk of future cardiovascular events. We sought to investigate further the relationship between toothbrushing, cardiovascular risk factors, and lifestyle behaviours.

METHODS

We analysed a cross-sectional survey including 13,761 adults aged 30 years or older without a history of cardiovascular diseases from the Korean National Health and Nutritional Examination Survey. Conventional cardiovascular risk factors (blood pressure, lipid profiles, and fasting glucose), and inflammatory markers (high-sensitivity C-reactive protein [hsCRP], and white blood cell counts [WBC]) were investigated in relation to the frequency of toothbrushing.

RESULTS

The estimated 10-year atherosclerotic cardiovascular disease (ASCVD) risk, calculated using the pooled cohort equations was 13.7%, 9.1%, and 7.3% for participants who reported toothbrushing 0-1, 2, and ≥ 3 times a day, respectively. Both conventional risk factors and inflammatory markers were significantly associated with frequent toothbrushing. However, after adjusting potential confounding factors such as age, sex, comorbidities, and lifestyle behaviours, only inflammatory markers were remained as significant factors.

CONCLUSIONS

Oral hygiene behaviours are closely linked to cardiovascular risk factors. This study suggests that reduced systemic inflammatory burden may explain the benefit of improved oral hygiene in terms of cardiovascular risk.

Electrocardiography score based on the Minnesota code classification system predicts cardiovascular mortality in an asymptomatic low-risk population

BACKGROUND

The use of a single abnormal finding on electrocardiography (ECG) is not recommended for stratifying the risk of cardiovascular (CV) events in low-risk general populations because of its low discriminative power. However, the value of a scoring system containing multiple abnormal ECG findings for predicting CV death has not been sufficiently evaluated.

METHODS

In a prospective community-based cohort study, 8417 participants without atherosclerotic CV diseases (ASCVDs) and any related symptoms were followed for 18 years. The standard 12-lead ECGs were recorded at baseline and the ECG findings were categorized using the Minnesota code classification. CV deaths were defined as death from myocardial infarction (MI), chronic ischemic heart disease, heart failure, fatal arrhythmia, cerebrovascular event, pulmonary thromboembolism, peripheral vascular disease and sudden cardiac arrest and identified using the Korean National Statistical Office (KOSTAT) database.

RESULTS

In a multivariate Cox proportional hazard (CPH) model, major and minor ST-T wave abnormalities, atrial fibrillation (AF), Q waves in the anterior leads, the lack of Q waves in the posterior leads, high amplitudes of the left and right precordial leads, left axis deviation and sinus tachycardia were associated with higher risks of CV deaths. The ECG score consisted of these findings showed modest predictive values represented by C-statistics that ranged from 0.632 to 760 during the follow-up and performed better in the early follow-up period. The ECG score independently predicted CV death after adjustment for relevant covariates in a multivariate model, and improved the predictive performance of the 10-year ASCVD risk estimator and a model of conventional risk factors including age, diabetes and current smoking. The combined ECG score (Harrell's C-index: 0.852, 95% confidence interval [CI], 0.828-0.876) composed of the ECG score and the conventional risk factors outperformed the 10-year ASCVD risk estimator (Harrell's C-index: 0.806; 95% CI, 0.780-0.833) and the model of the conventional risk factors (Harrell's C-index: 0.841, 95% CI, 0.817-0.865) and exhibited an excellent goodness of fit between the predicted and observed probabilities of CV death.

CONCLUSIONS

The ECG score could be useful to predict CV death independently and may add value to the conventional CV risk estimators regarding the risk stratification of CV death in asymptomatic low-risk general populations.

Validity of the models predicting 10-year risk of cardiovascular diseases in Asia: A systematic review and prediction model meta-analysis

We aimed to review the validity of existing prediction models for cardiovascular diseases (CVDs) in Asia. In this systematic review and meta-analysis, we included studies that validated prediction models for CVD risk in the general population in Asia. Various databases, including PubMed, Web of Science conference proceedings citation index, Scopus, Global Index Medicus of the World Health Organization (WHO), and Open Access Thesis and Dissertations (OATD), were searched up to November 2022. Additional studies were identified through reference lists and related reviews. The risk of bias was assessed using the PROBAST prediction model risk of bias assessment tool. Meta-analyses were performed using the random effects model, focusing on the C-statistic as a discrimination index and the observed-to-expected ratio (OE) as a calibration index. Out of 1315 initial records, 16 studies were included, with 21 external validations of six models in Asia. The validated models consisted of Framingham models, pooled cohort equations (PCEs), SCORE, Globorisk, and WHO models, combined with the results of the first four models. The pooled C-statistic for men ranged from 0.72 (95% CI 0.70 to 0.75; PCEs) to 0.76 (95% CI 0.74 to 0.78; Framingham general CVD). In women, it varied from 0.74 (95% CI 0.22 to 0.97; SCORE) to 0.79 (95% CI 0.74 to 0.83; Framingham general CVD). The pooled OE ratio for men ranged from 0.21 (95% CI 0.018 to 2.49; Framingham CHD) to 1.11 (95%CI 0.65 to 1.89; PCEs). In women, it varied from 0.28 (95%CI 0.33 to 2.33; Framingham CHD) to 1.81 (95% CI 0.90 to 3.64; PCEs). The Framingham, PCEs, and SCORE models exhibited acceptable discrimination but poor calibration in predicting the 10-year risk of CVDs in Asia. Recalibration and updates are necessary before implementing these models in the region.

Performance of Cardiovascular Risk Prediction Models in Korean Patients With New-Onset Rheumatoid Arthritis: National Cohort Study

BACKGROUND

This study aimed to compare the performance of established cardiovascular risk algorithms in Korean patients with new-onset rheumatoid arthritis.

METHODS AND RESULTS

This retrospective cohort study identified patients newly diagnosed with rheumatoid arthritis without a history of cardiovascular diseases between 2013 and 2019 using the National Health Insurance Service database. The cohort was followed up until 2020 for the development of the first major adverse cardiovascular event. General cardiovascular risk prediction algorithms, such as the systematic coronary risk evaluation model, the Korean risk prediction model for atherosclerotic cardiovascular diseases, the American College of Cardiology/American Heart Association pooled equations, and the Framingham Risk Score, were used. The discrimination and calibration of cardiovascular risk prediction models were evaluated. Hazard ratios were estimated using Cox proportional hazards regression. A total of 611 patients among 24 889 patients experienced a major adverse cardiovascular event during follow-up. The median 10-year atherosclerotic cardiovascular diseases risk score was significantly higher in patients with major adverse cardiovascular events than those without. The C-statistics of risk algorithms ranged between 0.72 and 0.74. Compared with the low-risk group, the actual risk of developing major adverse cardiovascular events increased significantly in the intermediate- and high-risk groups for all algorithms. However, the risk predictions calculated from all algorithms overestimated the observed cardiovascular risk in the middle to high deciles, and only the systematic coronary risk evaluation algorithm showed comparable observed and predicted event rates in the low-intermediate deciles with the highest sensitivity.

CONCLUSIONS

The systematic coronary risk evaluation model algorithm and the general risk prediction models discriminated patients with rheumatoid arthritis appropriately. However, overestimation should be considered when applying the cardiovascular risk prediction model in Korean patients.

Machine learning for the prediction of atherosclerotic cardiovascular disease during 3-year follow up in Chinese type 2 diabetes mellitus patients

AIMS/INTRODUCTION

Clinical guidelines for the management of individuals with type 2 diabetes mellitus endorse the systematic assessment of atherosclerotic cardiovascular disease risk for early interventions. In this study, we aimed to develop machine learning models to predict 3-year atherosclerotic cardiovascular disease risk in Chinese type 2 diabetes mellitus patients.

MATERIALS AND METHODS

Clinical records of 4,722 individuals with type 2 diabetes mellitus admitted to 94 hospitals were used. The features included demographic information, disease histories, laboratory tests and physical examinations. Logistic regression, support vector machine, gradient boosting decision tree, random forest and adaptive boosting were applied for model construction. The performance of these models was evaluated using the area under the receiver operating characteristic curve. Additionally, we applied SHapley Additive exPlanation values to explain the prediction model.

RESULTS

All five models achieved good performance in both internal and external test sets (area under the receiver operating characteristic curve >0.8). Random forest showed the highest discrimination ability, with sensitivity and specificity being 0.838 and 0.814, respectively. The SHapley Additive exPlanation analyses showed that previous history of diabetic peripheral vascular disease, older populations and longer diabetes duration were the three most influential predictors.

CONCLUSIONS

The prediction models offer opportunities to personalize treatment and maximize the benefits of these medical interventions.

Prognostic Value of Ankle-Brachial Index in Prediction of Cardiovascular Events in an Asian Population with Multiple Atherosclerotic Risk Factors

We aimed to evaluate the incremental prognostic value after incorporation of the ankle-brachial index (ABI) into the 10-year pool cohort equation (PCE) risk model in patients with multiple risk factors (MRFs). A total of 4332 MRFs patients were divided into 2 groups as ABI ≤.9 or >.9. The primary outcome was hard cardiovascular events (hCVE: including cardiovascular death, myocardial infarction, or ischemic stroke) over a median follow-up of 36 months. The Cox proportional hazards survival model, C-statistic, and net reclassification indices (NRI) were used. The occurrence of the primary outcome in the ABI ≤.9 group (3.7%) was significantly greater than in the ABI > .9 group (1.3%), P < .001. ABI is an independent predictor of hCVE in addition to the variables in the standard risk model (age, gender, and smoking status). ABI modestly improved the C-index when added to the PCE risk model (PCE .70 vs ABI+PCE .74). The addition of ABI to the PCE risk model did not significantly improve the classification of patients (NRI -.029; 95% CI: -.215 to .130). Despite ABI being one of the independent predictors of hCVE, integration of ABI into the PCE model did not improve the efficacy of risk reclassification in patients with MRFs.

Comparative Safety Analysis of Empagliflozin in Type 2 Diabetes Mellitus Patients with Chronic Kidney Disease versus Normal Kidney Function: A Nationwide Cohort Study in Korea

BACKGROUND

Empagliflozin has been shown to reduce cardiovascular morbidity and mortality in patients with type 2 diabetes. Various research on its efficacy in patients with chronic kidney disease (CKD) have been actively conducted. So far, few studies have investigated the safety of these adverse effects specifically in Asians with CKD. We aim to address these safety concerns on a patient population of Asian CKD patients using real-world data.

METHODS

We conducted a retrospective cohort study using health insurance data from the Korean Health Insurance Review & Assessment Service and compared safety outcomes between empagliflozin and sitagliptin in 26,347 CKD patients diagnosed with diabetes. Adverse outcomes, including major adverse cardiac events (MACEs), all-cause mortality, myocardial infarction (MI), stroke, and hospitalization for heart failure (HHF), among others, were assessed.

RESULTS

Among a 1:1 matched cohort (6170 on empagliflozin, 6170 on sitagliptin), empagliflozin was associated with a significant reduction in MACEs, all-cause mortality, MI, hospitalization for unstable angina, coronary revascularization, HHF, hypoglycemic events, and urinary tract infections, but increased the risk of genital tract infections. No significant changes were observed for transient ischemic attack, acute kidney injury, volume depletion, diabetic ketoacidosis, thromboembolic events, and fractures.

CONCLUSIONS

The usage of empagliflozin in diabetic CKD patients shows a significant reduction in many adverse outcomes compared to sitagliptin, but with an increased risk of genital tract infections. These findings provide evidence for future clinical decision-making around the use of empagliflozin in Asian CKD patients.

Evidence supporting the choice of a new cardiovascular risk equation for Australia

This article reviews the risk equations recommended for use in international cardiovascular disease (CVD) primary prevention guidelines and assesses their suitability for use in Australia against a set of a priori defined selection criteria. The review and assessment were commissioned by the National Heart Foundation of Australia on behalf of the Australian Chronic Disease Prevention Alliance to inform recommendations on CVD risk estimation as part of the 2023 update of the Australian CVD risk assessment and management guidelines. Selected international risk equations were assessed against eight selection criteria: development using contemporary data; inclusion of established cardiovascular risk factors; inclusion of ethnicity and deprivation measures; prediction of a broad selection of fatal and non-fatal CVD outcomes; population representativeness; model performance; external validation in an Australian dataset; and the ability to be recalibrated or modified. Of the ten risk prediction equations reviewed, the New Zealand PREDICT equation met seven of the eight selection criteria, and met additional usability criteria aimed at assessing the ability to apply the risk equation in practice in Australia.

Development of a Cardiovascular Disease Risk Prediction Model: A Preliminary Retrospective Cohort Study of a Patient Sample in Saudi Arabia

Saudi Arabia has an alarmingly high incidence of cardiovascular disease (CVD) and its associated risk factors. To effectively assess CVD risk, it is essential to develop tailored models for diverse regions and ethnicities using local population variables. No CVD risk prediction model has been locally developed. This study aims to develop the first 10-year CVD risk prediction model for Saudi adults aged 18 to 75 years. The electronic health records of Saudi male and female patients aged 18 to 75 years, who were seen in primary care settings between 2002 and 2019, were reviewed retrospectively via the Integrated Clinical Information System (ICIS) database (from January 2002 to February 2019). The Cox regression model was used to identify the risk factors and develop the CVD risk prediction model. Overall, 451 patients were included in this study, with a mean follow-up of 12.05 years. Thirty-five (7.7%) patients developed a CVD event. The following risk factors were included: fasting blood sugar (FBS) and high-density lipoprotein cholesterol (HDL-c), heart failure, antihyperlipidemic therapy, antithrombotic therapy, and antihypertension therapy. The Bayesian information criterion (BIC) score was 314.4. This is the first prediction model developed in Saudi Arabia and the second in any Arab country after the Omani study. We assume that our CVD predication model will have the potential to be used widely after the validation study.

Triglyceride-Glucose Index Predicts Future Atherosclerotic Cardiovascular Diseases: A 16-Year Follow-up in a Prospective, Community-Dwelling Cohort Study

BACKGRUOUND

While the triglyceride-glucose (TyG) index is a measure of insulin resistance, its association with cardiovascular disease (CVD) has not been well elucidated. We evaluated the TyG index for prediction of CVDs in a prospective large communitybased cohort.

METHODS

Individuals 40 to 70 years old were prospectively followed for a median 15.6 years. The TyG index was calculated as the Ln [fasting triglycerides (mg/dL)×fasting glucose (mg/dL)/2]. CVDs included any acute myocardial infarction, coronary artery disease or cerebrovascular disease. We used a Cox proportional hazards model to estimate CVD risks according to quartiles of the TyG index and plotted the receiver operating characteristics curve for the incident CVD.

RESULTS

Among 8,511 subjects (age 51.9±8.8 years; 47.5% males), 931 (10.9%) had incident CVDs during the follow-up. After adjustment for age, sex, body mass index, diabetes mellitus, hypertension, total cholesterol, smoking, alcohol, exercise, and C-reactive protein, subjects in the highest TyG quartile had 36% increased risk of incident CVD compared with the lowest TyG quartile (hazard ratio, 1.36; 95% confidence interval, 1.10 to 1.68). Carotid plaque, assessed by ultrasonography was more frequent in subjects in the higher quartile of TyG index (P for trend=0.049 in men and P for trend <0.001 in women). The TyG index had a higher predictive power for CVDs than the homeostasis model assessment of insulin resistance (HOMA-IR) (area under the curve, 0.578 for TyG and 0.543 for HOMA-IR). Adding TyG index on diabetes or hypertension alone gave sounder predictability for CVDs.

CONCLUSION

The TyG index is independently associated with future CVDs in 16 years of follow-up in large, prospective Korean cohort.

Rate of Change in 10-Year Atherosclerotic Cardiovascular Disease Risk and Its Implications for Primary Prevention

BACKGROUND

Contemporary cardiovascular primary prevention is based on the assessment of the 10-year risk of atherosclerotic cardiovascular disease (ASCVD). However, the clinical implications of temporal change in the 10-year ASCVD risk estimate (∆10-year ASCVD risk/year) are unknown.

METHODS

A total of 211 077 participants without established ASCVD and with repetitive 10-year ASCVD risk assessment at an interval of 4 to 5 years were selected from the Korean National Health Insurance Service data. The primary end point was a composite of myocardial infarction, stroke, coronary revascularization, and all-cause death.

RESULTS

ASCVD event rates were proportional to the ∆10-year ASCVD risk/year regardless of the baseline 10-year ASCVD risk. Adjusted hazard ratio for ASCVD events per 1% increase in ∆10-year ASCVD risk/year was 1.53 (95% CI, 1.44-1.63), 1.24 (95% CI, 1.15-1.32), 1.18 (95% CI, 1.13-1.23), and 1.05 (95% CI, 1.00-1.10) in those with a baseline 10-year ASCVD risk of <5%, 5% to 7.5%, 7.5% to 20%, and ≥20%, respectively. Appropriate control of risk factors, including low-density lipoprotein cholesterol, blood pressure, body mass index, exercise habits, and smoking status, was associated with lower ASCVD event rates, whereas failure to control these risk factors resulted in higher ASCVD event rates.

CONCLUSIONS

The temporal change in 10-year ASCVD risk over a period of 4 to 5 years reflects success or failure in controlling major cardiovascular risk factors and indicates the risk of future ASCVD events. The ∆10-year ASCVD risk/year can be used as an indicator of primary prevention and guide the application of preventive measures.

Comparing the performance of machine learning and conventional models for predicting atherosclerotic cardiovascular disease in a general Chinese population

BACKGROUND

Accurately predicting the risk of atherosclerotic cardiovascular disease (ASCVD) is crucial for implementing individualized prevention strategies and improving patient outcomes. Our objective is to develop machine learning (ML)-based models for predicting ASCVD risk in a prospective Chinese population and compare their performance with conventional regression models.

METHODS

A hybrid dataset consisting of 551 features was used, including 98 demographic, behavioral, and psychological features, 444 Electrocardiograph (ECG) features, and 9 Echocardiography (Echo) features. Seven machine learning (ML)-based models were trained, validated, and tested after selecting the 30 most informative features. We compared the discrimination, calibration, net benefit, and net reclassification improvement (NRI) of the ML models with those of conventional ASCVD risk calculators, such as the Pooled Cohort Equations (PCE) and Prediction for ASCVD Risk in China (China-PAR).

RESULTS

The study included 9,609 participants (mean age 53.4 ± 10.4 years, 53.7% female), and during a median follow-up of 4.7 years, 431 (4.5%) participants developed ASCVD. In the testing set, the final ML-based ANN model outperformed PCE, China-PAR, recalibrated PCE, and recalibrated China-PAR in predicting ASCVD. This was demonstrated by the model's higher area under the curve (AUC) of 0.800, compared to 0.777, 0.780, 0.779, and 0.779 for the other models, respectively. Additionally, the model had a lower Hosmer-Lemeshow χ2 of 9.1, compared to 37.3, 67.6, 126.6, and 18.6 for the other models. The net benefit at a threshold of 5% was also higher for the ML-based ANN model at 0.017, compared to 0.016, 0.013, 0.017, and 0.016 for the other models, respectively. Furthermore, the NRI was 0.089 for the ML-based ANN model, while it was 0.355, 0.098, and 0.088 for PCE, China-PAR, and recalibrated PCE, respectively.

CONCLUSIONS

Compared to conventional regression ASCVD risk calculators, such as PCE and China-PAR, the ANN prediction model may help optimize identification of individuals at heightened cardiovascular risk by flexibly incorporating a wider range of potential predictors. The findings may help guide clinical decision-making and ultimately contribute to ASCVD prevention and management.

Normal-weight visceral obesity promotes a higher 10-year atherosclerotic cardiovascular disease risk in patients with type 2 diabetes mellitus-a multicenter study in China

BACKGROUND

Visceral obesity is associated with high cardiovascular events risk in type 2 diabetes mellitus (T2DM). Whether normal-weight visceral obesity will pose a higher atherosclerotic cardiovascular disease (ASCVD) risk than body mass index (BMI)-defined overweight or obese counterparts with or without visceral obesity remains unclear. We aimed to explore the relationship between general obesity and visceral obesity and 10-year ASCVD risk in patients with T2DM.

METHODS

Patients with T2DM (6997) who satisfied the requirements for inclusion were enrolled. Patients were considered to have normal weight when 18.5 kg/m² ≤ BMI < 24 kg/m²; overweight when 24 kg/m² ≤ BMI < 28 kg/m²; and obesity when BMI ≥ 28 kg/m². Visceral obesity was defined as a visceral fat area (VFA) ≥ 100 cm². Patients were separated into six groups based on BMI and VFA. The odd ratios (OR) for a high 10-year ASCVD risk for different combinations of BMI and VFA were analysed using stepwise logistic regression. Receiver operating characteristic (ROC) curves for diagnosing the high 10-year ASCVD risk were constructed, and areas under the ROC curves were estimated. Potential non-linear relationships between VFA levels and high 10-year ASCVD risk were examined using restricted cubic splines (knot = 4). Multilinear regression was used to identify factors affecting VFA in patients with T2DM.

RESULTS

In patients with T2DM, subjects with normal-weight visceral obesity had the highest 10-year ASCVD risk among the six groups, which had more than a 2-fold or 3-fold higher OR than those who were overweight or obese according to BMI but did not have visceral obesity (all P < 0.05). The VFA threshold for high 10-year ASCVD risk was 90 cm². Multilinear regression showed significant differences in the effect of age, hypertension, drinking, fasting serum insulin, fasting plasma glucose, 2 h postprandial C-peptide, triglyceride, total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol on VFA in patients with T2DM (all P < 0.05).

CONCLUSIONS

T2DM patients with normal-weight visceral obesity had a higher 10-year ASCVD risk than BMI-defined overweight or obese counterparts with or without visceral obesity, which should initiate standardised management for ASCVD primary prevention.

Prediction of the 10-year risk of atherosclerotic cardiovascular disease in the Korean population

OBJECTIVES

Proper risk assessment is important for the primary prevention of atherosclerotic cardiovascular disease (ASCVD). However, no validated risk prediction tools are currently in use in Korea. This study sought to develop a 10-year risk prediction model for incident ASCVD.

METHODS

Using the National Sample Cohort of Korea, 325,934 subjects aged 20-80 years without previous ASCVD were enrolled. ASCVD was defined as a composite of cardiovascular death, myocardial infarction, and stroke. The Korean atherosclerotic cardiovas cular disease risk prediction (K-CVD) model was developed separately for men and women using the development dataset and validated in the validation dataset. Furthermore, the model performance was compared with the Framingham risk score (FRS) and pooled cohort equation (PCE).

RESULTS

Over 10 years of follow-up, 4,367 ASCVD events occurred in the overall population. The predictors of ASCVD included in the model were age, smoking status, diabetes, systolic blood pressure, lipid profiles, urine protein, and lipid-lowering and blood pressure-lowering treatment. The K-CVD model had good discrimination and strong calibration in the validation dataset (time-dependent area under the curve=0.846; 95% confidence interval, 0.828 to 0.864; calibration χ2=4.73, goodness-of-fit p=0.32). Compared with our model, both FRS and PCE showed worse calibration, overestimating ASCVD risk in the Korean population.

CONCLUSIONS

Through a nationwide cohort, we developed a model for 10-year ASCVD risk prediction in a contemporary Korean population. The K-CVD model showed excellent discrimination and calibration in Koreans. This population-based risk prediction tool would help to appropriately identify high-risk individuals and provide preventive interventions in the Korean population.

Risk Stratification of Cardiovascular Disease according to Age Groups in New Prevention Guidelines: A Review

Age is a strong risk factor for cardiovascular disease. Accordingly, most cardiovascular risk prediction models have included age as an independent risk factor. There is much evidence that effective management of cardiovascular risk factors improves clinical outcomes even in older adults. However, there are concerns that intensive treatment for older adults increases the risk of adverse events. For hypertensive patients, intensive blood pressure reduction with combination therapy increases the risk of syncope, acute kidney injury, and falls. Intensive glucose-lowering therapy among older patients with diabetes increases the risk of hypoglycemia or cognitive impairment. These findings suggest that a balanced approach for older adults is required to increase the benefits and decrease the risk of side effects. In contrast to older people, the estimated 10-year cardiovascular risk in young and healthy individuals is low. However, the lifetime cardiovascular risk in these patients is actually high. The 2021 European Society of Cardiology guideline on cardiovascular disease prevention in clinical practice has been published. It proposed a different risk stratification and recommendation for treatment according to age group, based on the concept of avoiding undertreatment in young people and overtreatment in older persons. Although the guideline recommends age-dependent risk stratification, risk categories should not be applied to the mandatory initiation of drug treatment. In all age groups, other factors such as lifetime cardiovascular risk, treatment benefit and harm, comorbidities, frailty, and patient preferences should be considered when managing patients for primary prevention.

Ideal cardiovascular health metrics and the risk of nonalcoholic fatty liver disease in Korean adults

BACKGROUND

The association between cardiovascular risk factors and nonalcoholic fatty liver disease (NAFLD) is well established, but whether cardiovascular health (CVH) metrics is associated with NAFLD had not been fully studied. Thus, we examined the association between CVH metrics and NAFLD in the middle-aged Korean population.

METHODS

We used data of 2,928 (851 men and 2,077 women) participants aged 30-64 years from the Cardiovascular and Metabolic Disease Etiology Research Center study. CVH metrics were measured using a modified version of Life's Simple 7 by the American Heart Association. NAFLD diagnosis was based on the fatty liver index or liver-to-spleen ratio on computed tomography. A multiple logistic regression model was used to investigate the cross-sectional and longitudinal associations between CVH metrics and NAFLD.

RESULTS

In the cross-sectional analysis, the odds ratio for NAFLD was lower in participants with ideal CVH (odds ratio [OR], 0.13; 95% confidence interval [CI], 0.08-0.18), while it was higher in individuals with poor CVH (OR, 2.87; 95% CI, 2.13-3.86). Similarly, the risk of new-onset NAFLD was lower in participants with ideal CVH (OR, 0.28; 95% CI, 0.11-0.74), and higher in individuals with poor CVH (OR, 2.20; 95% CI, 0.50-9.72) in the longitudinal analysis of a subgroup.

CONCLUSIONS

Ideal CVH was associated with a lower risk of NAFLD while poor CVH was associated with a higher risk of NAFLD. These findings suggest that making efforts to encourage people to manage their CVH to the ideal level may prevent and manage NAFLD.

The association between incidentally found breast arterial calcification on routine screening mammography and the development of coronary artery disease and stroke: results of a 10-year prospective study

OBJECTIVE

The objective of this study is to assess whether the presence of breast arterial calcifications (BACs) found on routine mammography is prospectively associated with the development of cardiovascular disease (CVD) events after 10 years of follow-up.

METHODS

Women presenting for screening mammography were enrolled in this prospective cohort. Baseline data were collected including history of CVD and CVD risk factors. Mammograms were assessed for the presence or absence of BAC. Participants completed questionnaires 10 years after baseline that assessed the development of CVD (coronary artery disease [CAD] and stroke) and CVD risk factors.

RESULTS

Of the 1,995 participants who enrolled at baseline, complete 10-year follow-up data were available for 1,039; of those, 114 (11.0%) were BAC-positive and 925 (89.0%) were BAC-negative at baseline. After controlling for age, BAC-positive women were more likely to develop CAD (odds ratio, 3.14; 95% confidence interval, 1.86-5.27; P < 0.001) compared with BAC-negative women after 10 years of follow-up. After controlling for age, BAC-positive women were more likely to have had a stroke (odds ratio, 5.10; 95% CI, 1.82-14.30) compared with BAC-negative women after 10 years.

CONCLUSIONS

The presence of BAC on routine screening mammography was associated with a significantly increased risk of developing CAD and stroke after 10 years of follow-up. Additional large prospective, population-based studies are needed to confirm BAC as a predictor of future CVD events and its utility in stratifying a woman's risk of CVD.

Comparison of Framingham risk score and pooled cohort equations for the prediction of coronary atherosclerosis in patients who meet the target LDL-C level of Korean dyslipidemia guideline

This study aims to compare the predicting performance of coronary atherosclerosis between Framingham Risk Score (FRS) and Pooled Cohort Equations (PCE) in moderate to high-risk patients who meet the target low-density lipoprotein cholesterol (LDL-C) level of Korean dyslipidemia guidelines. Among 1207 patients aged 40 to 65 who underwent coronary computed tomography angiography at outpatient for chest discomfort, we included 414 moderate-risk patients (non-diabetes) and 86 high-risk patients (diabetes). They were divided into 3 groups according to FRS and PCE, then compared with coronary artery calcification score (CACS) and plaque burden degree strata. We presented receiver operating characteristic curves for the presence of coronary artery calcification (CAC) and any plaque. In moderate-risk patients, the distribution of CACS and plaque burden degree according to FRS and PCE risk strata showed significant differences between groups and a consistent trend (P < .001). Both FRS and PCE showed good discrimination for the presence of CAC [area under the curve (AUC); 0.711 vs 0.75, P = .02] and any plaque (AUC; 0.72 vs 0.756, P = .025). However, in high-risk patients, there was no significant differences or consistent trend between groups and the AUC values of FRS and PCE were (0.537 vs 0.571, P = .809) for CAC and (0.478 vs 0.65 P = .273) for any plaque showing poor discrimination. In predicting coronary atherosclerosis in moderate to high-risk patients who meet the target LDL-C level of Korean dyslipidemia guidelines, both FRS and PCE can be used in moderate-risk patients but not in high-risk patients.

Overall and cardiovascular mortality according to 10-year cardiovascular risk of the general health checkup: the Kangbuk Samsung Cohort Study

Background

According to the occupational accident status analysis in 2020, of 1,180 occupational deaths, 463 were caused by cardiovascular disease (CVD). Workers should be assessed for CVD risk at regular intervals to prevent work-related CVD in accordance with the rules on occupational safety and health standards. However, no previous study has addressed risk and mortality. Therefore, this longitudinal study was conducted to evaluate the relationship between 10-year cardiovascular risk of the general health checkup and mortality.

Methods

The study included 545,859 participants who visited Kangbuk Samsung Total Healthcare Centers from January 1, 2002, to December 31, 2017. We performed 10-year cardiovascular risk assessment for the participants and the risk was divided into 4 groups (low, moderate, high, and very high). The study used death data from the Korea National Statistical Office for survival status as an outcome variable by December 31, 2019, and the cause of death based on the International Classification of Diseases, 10^th Revision (ICD-10) was identified. Statistical analysis was performed using Cox proportional hazards regression analysis, and the sum of the periods from the first visit to the date of death or December 31, 2019, was used as a time scale. We also performed a stratified analysis for age at baseline and sex.

Results

During 5,253,627.9 person-years, 4,738 overall deaths and 654 cardiovascular deaths occurred. When the low-risk group was set as a reference, in the multivariable-adjusted model, the hazard ratios (HRs) (95% confidence interval [CI]) for overall mortality were 3.36 (2.87-3.95) in the moderate-risk group, 11.08 (9.27-13.25) in the high-risk group, and 21.20 (17.42-25.79) in the very-high-risk group, all of which were statistically significant. In cardiovascular deaths, the difference according to the risk classification was more pronounced. The HRs (95% CI) were 8.57 (4.95-14.83), 38.95 (21.77-69.69), and 78.81 (42.62-145.71) in each group. As a result of a subgroup analysis by age and sex, the HRs of all-cause mortality and cardiovascular mortality tended to be higher in the high-risk group.

Conclusions

This large-scale longitudinal study confirmed that the risk of death increases with the 10-year cardiovascular risk of general health checkup.

Do statins benefit low-risk population for primary prevention of atherosclerotic cardiovascular disease: A retrospective cohort study

The reported beneficial effects of statins on cardiovascular outcome based on risk assessment are inconsistent. Therefore, we investigated statin therapy effectiveness for the primary prevention of cardiovascular disease (CVD), according to the Korean Risk Prediction Model (KRPM). Subjects aged 40–79 years with low density lipoprotein cholesterol (LDL-C) of < 190 mg/dL and without CVD history were categorized as statin users or non-users using the National Health Insurance Service-National Sample Cohort (NHIS-NSC) database, Korea, 2002–2015. The 10-year atherosclerotic CVD (ASCVD) risk was calculated using the validated KRPM and categorized as low, borderline, intermediate, or high-risk groups; the incidence of major adverse cardiovascular events (MACEs) was compared over a mean follow-up period of 5.7 years using Cox proportional hazard models. The MACE incidence risk was decreased in statin users [hazard ratio (HR) 0.90, 95% confidence interval (CI) (0.84–0.98)]. However, there was an increased risk of MACE incidence in low-risk statin users [HR 1.80, 95% CI (1.29–2.52)], and no significant relationship was identified between statin use and MACE in the borderline [HR 1.15, 95% CI (0.86–1.54)] and intermediate-risk [HR 0.94, 95% CI (0.85–1.03)] groups. The risk of MACE incidence decreased only in the high CVD risk group among statin users. Statin use is not associated with MACE reduction in low- to intermediate-risk participants. Therefore, individuals with LDL-C level of < 190 mg/dL and low ASCVD risk should consider statin therapy only when CVD risk is proved obvious using an appropriate ASCVD risk tool.

Carfilzomib's Real-World Safety Outcomes in Korea: Target Trial Emulation Study Using Electronic Health Records

Carfilzomib is a promising anticancer drug for relapsed/refractory multiple myeloma (RRMM). However, real-world evidence has only investigated the cardiovascular safety of carfilzomib, and there is a high demand for thorough safety evaluations. We aimed to comprehensively evaluate the risk of adverse events associated with carfilzomib in Korean patients with RRMM. We followed up with 138 matched patients with RRMM (69 KRd (carfilzomib, lenalidomide, and dexamethasone) and 69 Rd (lenalidomide and dexamethasone) users). A total of 12 adverse events were evaluated. More than 75% of adverse events occurred during the early cycle (1-6 cycles), and the incidence rate showed a tendency to decrease in the later cycle (7-12 and 13-18 cycles). Severities of most adverse events were evaluated as grade 1-2. The KRd regimen were related with significantly increased risks of dyspnea (adjusted HR (aHR) 2.27, 95% confidence interval (CI) 1.24-4.16), muscle spasm (aHR 5.12, 95% CI 1.05-24.9) and thrombocytopenia (aHR 1.84, 95% CI 1.10-3.06). Although the severities were low, carfilzomib has many side effects in treating RRMM; hence, findings on the patterns of its adverse events could lead to both effective and safe use of KRd therapy in real-world settings.

Implications of the heterogeneity between guideline recommendations for the use of low dose aspirin in primary prevention of cardiovascular disease

The most recent primary cardiovascular disease (CVD) prevention clinical guidelines used in Europe, Italy, the USA, China, and South Korea differ in aspects of their approach to CVD risk assessment and reduction. Low dose aspirin use is recommended in certain high-risk patients by most but not all the countries. Assessment of traditional risk factors and which prediction models are commonly used differ between countries. The assessments and tools may not, however, identify all patients at high risk but without manifest CVD. The use of coronary artery calcium (CAC) score to guide decisions regarding primary prevention aspirin therapy is recommended only by the US primary prevention guidelines and the 2021 European Society of Cardiology guidelines. A more consistent and comprehensive global approach to CVD risk estimation in individual patients could help to personalize primary CVD prevention. Wider detection of subclinical atherosclerosis, together with structured assessment and effective mitigation of bleeding risk, may appropriately target patients likely to gain net benefit from low dose aspirin therapy.

Using real-world data for supporting regulatory decision making: Comparison of cardiovascular and safety outcomes of an empagliflozin randomized clinical trial versus real-world data

Aims: In countries where a randomized clinical trial (RCT) is difficult to perform, a real-world evidence (RWE) study with a design similar to an RCT may be an option for drug regulatory decision-making. In this study, the objective was to find out to what extent the safety of empagliflozin from the RWE study in Korea is different from the one in RCT by emulating the design of foreign RCT. The outcome covers various safety outcomes including cardiovascular safety.

Methods: The EMPA-REG OUTCOME trial (NCT01131676) was selected for comparison. The inclusion/exclusion criteria and follow-up method for the RWE were matched to the comparison RCT. Major adverse cardiovascular events (MACEs) were used as a primary outcome and 15 other outcomes were also included for analysis.

Result: We followed 23,126 matched patients with type 2 diabetes mellitus (11,563 empagliflozin users and 11,563 sitagliptin users) for 2.7 years (median). Empagliflozin use was associated with a significantly decreased risk of MACEs [EMPA-REG DUPLICATE RWE: adjusted HR 0.87, 95% confidence interval (CI) 0.79–0.96]. The predefined estimate agreement, regulatory agreement, and standardized difference for RCT duplication were achieved [EMPA-REG OUTCOME RCT: adjusted HR 0.86, 95% (CI) 0.74–0.99]. According to the predefined criteria for 15 outcomes, 10 outcomes were evaluated as good, and three as moderate.

Conclusion: Our study results suggest that RWE in one country in comparison with an RCT has the potential for providing evidence for future regulatory decision-making in an environment where RCT could not be performed.

Prediction performance and fairness heterogeneity in cardiovascular risk models

Prediction models are commonly used to estimate risk for cardiovascular diseases, to inform diagnosis and management. However, performance may vary substantially across relevant subgroups of the population. Here we investigated heterogeneity of accuracy and fairness metrics across a variety of subgroups for risk prediction of two common diseases: atrial fibrillation (AF) and atherosclerotic cardiovascular disease (ASCVD). We calculated the Cohorts for Heart and Aging in Genomic Epidemiology Atrial Fibrillation (CHARGE-AF) score for AF and the Pooled Cohort Equations (PCE) score for ASCVD in three large datasets: Explorys Life Sciences Dataset (Explorys, n = 21,809,334), Mass General Brigham (MGB, n = 520,868), and the UK Biobank (UKBB, n = 502,521). Our results demonstrate important performance heterogeneity across subpopulations defined by age, sex, and presence of preexisting disease, with fairly consistent patterns across both scores. For example, using CHARGE-AF, discrimination declined with increasing age, with a concordance index of 0.72 [95% CI 0.72-0.73] for the youngest (45-54 years) subgroup to 0.57 [0.56-0.58] for the oldest (85-90 years) subgroup in Explorys. Even though sex is not included in CHARGE-AF, the statistical parity difference (i.e., likelihood of being classified as high risk) was considerable between males and females within the 65-74 years subgroup with a value of - 0.33 [95% CI - 0.33 to - 0.33]. We also observed weak discrimination (i.e., < 0.7) and suboptimal calibration (i.e., calibration slope outside of 0.7-1.3) in large subsets of the population; for example, all individuals aged 75 years or older in Explorys (17.4%). Our findings highlight the need to characterize and quantify the behavior of clinical risk models within specific subpopulations so they can be used appropriately to facilitate more accurate, consistent, and equitable assessment of disease risk.

A clinical algorithm to determine target blood pressure in the elderly: evidence and limitations from a clinical perspective

As the elderly population is growing rapidly, management of hypertension in South Korea faces major challenges because the proportion of elderly hypertension patients is also increasing. The characteristics of this population are also much more complex than younger patients. Elderly hypertension is characterized by wide variations in (1) fitness or biological age, (2) white-coat effect, (3) poor functional status or frailty, (4) dependency in activities of daily living or institutionalization, (5) orthostatic hypotension, and (6) multiple comorbidities. All of these should be considered when choosing optimal target blood pressure in individual patients. Recent randomized clinical trials have shown that the benefits of intensive blood pressure control for elderly patients is greater than previously thought. For generalization of these results and implementation of the guidelines based on these studies, defining the clinician's role for individualization is critically important. For individualized decisions for target blood pressure (BP) in the elderly with hypertension, four components should first be checked. These consist of (1) the minimum requirement of functional status and capability of activities of daily living, (2) lack of harmful evidence by the target BP, (3) absence of white-coat hypertension, and (4) standing systolic BP ≥ 110 mmHg without orthostatic symptoms. Risk of decreased organ perfusion by arterial stenosis should be screened before starting intensive BP control. When the target BP differs among comorbidities, the lowest target BP should be given preference. After starting intensive BP lowering therapy, tolerability should be monitored, and the titration should be based on the mean level of blood pressure by office supplemented by out-of-office BPs. Applications of the clinical algorithms will be useful to achieve more standardized and simplified applications of target BP in the elderly.

Integrated approach of brachial-ankle pulse wave velocity and cardiovascular risk scores for predicting the risk of cardiovascular events

Background

The 2013 American College of Cardiology (ACC)/American Heart Association (AHA) atherosclerotic cardiovascular disease (ASCVD) risk score may be insufficient for accurate prediction of major adverse cardiac events (MACE) in Asians. This study was performed to investigate whether brachial-ankle pulse wave velocity (baPWV) has additional prognostic value to the risk score estimated by the ACC/AHA pooled cohort equations (PCEs).

Methods

A total of 6,359 patients (3,534 men and 2,825 women) aged 40–79 years without documented cardiovascular disease who underwent baPWV measurement were retrospectively analyzed. Cardiovascular risk scores were calculated using the 2013 ACC/AHA PCEs. Cardiovascular events, including cardiac death, non-fatal myocardial infarction, coronary revascularization and ischemic stroke, were assessed.

Results

During a median follow-up period of 4.0 years (interquartile range 1.7–6.1 years), cardiovascular events occurred in 129 patients (2.0%). The receiver operating characteristic curve analysis showed that baPWV was stronger in the detection of cardiovascular events than the 2013 ACC/AHA risk score (area under the curve: 0.70 versus 0.62, p<0.001). In the multivariable Cox regression analysis, both baPWV and 2013 ACC/AHA risk score were independently associated with the occurrence of clinical events (p <0.001 for each). The baPWV had incremental prognostic value to the 2013 ACC/AHA risk score in predicting clinical events (global chi-square from 21.23 to 49.51, p<0.001).

Conclusion

The baPWV appears to be a strong predictor of the risk of cardiovascular events in Koreans. Measuring baPWV in addition to the 2013 ACC/AHA risk score helps identify individuals at risk for MACE aged 40–79 years without previous cardiovascular diseases.

Associations between the triglyceride-glucose index and cardiovascular disease in over 150,000 cancer survivors: a population-based cohort study

Background

The prevention of subsequent cardiovascular disease (CVD) is an essential part of cancer survivorship care. We conducted the present study to investigate the association between the TyG index (a surrogate marker of insulin resistance) and the risk of cardiovascular disease (CVD) events in cancer survivors.

Methods

Adult cancer patients, who underwent routine health examinations during 2009–2010 and were survived for more than 5 years as of January 1, 2011, were followed for hospitalization of CVD (either ischemic heart disease, stroke, or heart failure) until December 2020. Cox model was used to calculate hazard ratios associated with baseline TyG index (log_e [fasting triglyceride (mg) × fasting glucose (mg)/2]) for the CVD hospitalization.

Results

A total of 155,167 cancer survivors (mean age 59.9 ± 12.0 years, female 59.1%) were included in this study. A graded positive association was observed between TyG and CVD hospitalization. An 8% elevated risk for CVD hospitalization was observed for a TyG index of 8-8.4 (aHR 1.08 [95% CI 1.01–1.14]); 10% elevated risk for a TyG index of 8.5–8.9 (aHR 1.10 [95% CI 1.03–1.17]); 23% elevated risk for a TyG index of 9.0-9.4 (aHR 1.23 [95% CI 1.15–1.31]); 34% elevated risk for a TyG index of 9.5–9.9 (aHR 1.34 [95% CI 1.23–1.47]); and 55% elevated risk for a TyG index ≥ 10 compared to the reference group (TyG index < 8). Per 1-unit increase in the TyG index, a 16% increase in CVD hospitalization and a 45% increase in acute myocardial infarction hospitalization were demonstrated. Graded positive associations were evident for atherosclerotic CVD subtypes, such as ischemic heart disease, acute myocardial infarction, and ischemic stroke, but not for hemorrhagic stroke or heart failure.

Conclusions

The TyG index may serve as a simple surrogate marker for the risk stratification of future CVD events, particularly atherosclerotic subtypes, in cancer survivors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01490-z.

Cardiovascular risk scores in asymptomatic carotid stenosis: A validation study with ultrasonographic parameters

We evaluated the feasibility of the Framingham stroke risk score (FSRS) and atherosclerotic cardiovascular disease (ASCVD) risk scores for asymptomatic carotid stenosis (ACS). In addition, we developed novel risk prediction models for ischemic stroke and composite outcomes by combining ultrasonographic parameters and conventional cardiovascular risk scores. We retrospectively enrolled 612 patients with ACS greater than 50% over 7 years and evaluated them using transcranial Doppler and carotid duplex ultrasonography. In total, 150 patients were included in the analysis. During the mean 5-year follow-up, 6 ischemic strokes and 25 composite events were detected. Among all ultrasonographic parameters, only a higher peak-systolic velocity/end-diastolic velocity ratio was detected and significantly associated with an increased risk of relevant ischemic stroke (hazard ratio: 1.502, 95% confidence interval: 1.036–1.968). The C-statistics of the FSRS and ASCVD risk scores were 0.646 and 0.649, respectively, for relevant ischemic stroke, and 0.612 and 0.649, respectively, for composite outcomes. C-statistics of the FSRS and ASCVD risk scores combined with ultrasonographic parameters increased to 0.937 and 0.941, respectively, for ischemic stroke, and 0.856 and 0.886, respectively, for composite outcomes. The study suggests that inclusion of ultrasonographic parameters in conventional cardiovascular scores helps identify the risk of further vascular events in ACS patients.

Evaluation of Atherosclerotic Cardiovascular Risk Prediction Models in China: Results From the CHERRY Study

BACKGROUND

Updated American or Chinese guidelines recommended calculating atherosclerotic cardiovascular disease (ASCVD) risk using the Pooled Cohort Equations (PCE) or Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) models; however, evidence on performance of both models in Asian populations is limited.

OBJECTIVES

The authors aimed to evaluate the accuracy of the PCE or China-PAR models in a Chinese contemporary cohort.

METHODS

Data were extracted from the CHERRY (CHinese Electronic health Records Research in Yinzhou) study. Participants aged 40 to 79 years without prior ASCVD at baseline from 2010 to 2016 were included. ASCVD was defined as nonfatal or fatal stroke, nonfatal myocardial infarction, and cardiovascular death. Models were assessed for discrimination and calibration.

RESULTS

Among 226,406 participants, 5362 (2.37%) adults developed a first ASCVD event during a median of 4.60 years of follow-up. Both models had good discrimination: C-statistics in men were 0.763 (95% confidence interval [CI]: 0.754-0.773) for PCE and 0.758 (95% CI: 0.749-0.767) for China-PAR; C-statistics in women were 0.820 (95% CI: 0.812-0.829) for PCE and 0.811 (95% CI: 0.802-0.819) for China-PAR. The China-PAR model underpredicted risk by 20% in men and by 40% in women, especially in the highest-risk groups. However, PCE overestimated by 63% in men and inversely underestimated the risk by 34% in women with poor calibration (both P < 0.001). After recalibration, observed and predicted risks by recalibrated PCE were better aligned.

CONCLUSIONS

In this large-scale population-based study, both PCE and China-PAR had good discrimination in 5-year ASCVD risk prediction. China-PAR outperformed PCE in calibration, whereas recalibration equalized the performance of PCE and China-PAR. Further specific models are needed to improve accuracy in the highest-risk groups.

The Association between Serum Uric Acid Levels and 10-Year Cardiovascular Disease Risk in Non-Alcoholic Fatty Liver Disease Patients

Non-alcoholic fatty liver disease (NAFLD) and serum uric acid (SUA) levels are risk factors for developing cardiovascular disease (CVD). Additionally, previous studies have suggested that high SUA levels increase the risk of having NAFLD. However, no study has investigated the relationship between SUA and CVD risk in NAFLD. This study analyzed the relationship between SUA and CVD in NAFLD. Data for this study used the 2016–2018 Korean National Health and Nutrition Examination Survey, which represents the Korean population. A total of 11,160 NAFLD patients were included. Participants with hepatic steatosis index ≥ 30 were considered to have NAFLD. Ten-year CVD risk was estimated using an integer-based Framingham risk score. Estimated 10-year CVD risk ≥ 20% was considered high risk. Multiple logistic regression was conducted to calculate the odds ratios (ORs) associated with SUA level and CVD risk. High CVD risk OR increases by 1.31 (95% CI 1.26–1.37) times per 1 mg/dL of SUA. After adjustment, SUA still had an increased risk (OR 1.44; 95% CI 1.38–1.51) of CVD. Compared with the lowest SUA quartile group, the highest quartile group showed a significantly higher risk of having CVD before (OR 2.76; 95% CI 2.34–3.25) and after (OR 4.01; 95% CI 3.37–4.78) adjustment. SUA is independently associated with CVS risk in NAFLD.

Risk prediction models for atherosclerotic cardiovascular disease: A systematic assessment with particular reference to Qatar

Background: Atherosclerotic cardiovascular disease (ASCVD) is a common disease in the State of Qatar and results in considerable morbidity, impairment of quality of life and mortality. The American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) is currently used in Qatar to identify those at high risk of ASCVD. However, it is unclear if this is the optimal ASCVD risk prediction model for use in Qatar's ethnically diverse population.

Aims: This systematic review aimed to identify, assess the methodological quality of and compare the properties of established ASCVD risk prediction models for the Qatari population.

Methods: Two reviewers performed head-to-head comparisons of established ASCVD risk calculators systematically. Studies were independently screened according to predefined eligibility criteria and critically appraised using Prediction Model Risk Of Bias Assessment Tool. Data were descriptively summarized and narratively synthesized with reporting of key statistical properties of the models.

Results: We identified 20,487 studies, of which 41 studies met our eligibility criteria. We identified 16 unique risk prediction models. Overall, 50% (n = 8) of the risk prediction models were judged to be at low risk of bias. Only 13% of the studies (n = 2) were judged at low risk of bias for applicability, namely, PREDICT and QRISK3.Only the PREDICT risk calculator scored low risk in both domains.

Conclusions: There is no existing ASCVD risk calculator particularly well suited for use in Qatar's ethnically diverse population. Of the available models, PREDICT and QRISK3 appear most appropriate because of their inclusion of ethnicity. In the absence of a locally derived ASCVD for Qatar, there is merit in a formal head-to-head comparison between PCE, which is currently in use, and PREDICT and QRISK3.

Metabolic Dysfunction-Associated Fatty Liver Disease and Incident Cardiovascular Disease Risk: A Nationwide Cohort Study

BACKGROUND & AIMS

An international expert panel proposed a new definition for metabolic dysfunction-associated fatty liver disease (MAFLD) as a name change from nonalcoholic fatty liver disease (NAFLD). The clinical impact of this change on the assessment of cardiovascular disease (CVD) risk is yet unknown. We evaluated the prevalence of fatty liver disease (FLD) and the associated CVD risk using each of these definitions.

METHODS

From a nationwide health screening database, we included 9,584,399 participants (48.5% male) aged 40-64 years between 2009 and 2010. Participants were categorized by presence of NAFLD and MAFLD, separately, and by the combination of the 2 definitions-Neither-FLD, NAFLD-only, MAFLD-only, or Both-FLD. The primary outcome was a composite CVD event, including myocardial infarction, ischemic stroke, heart failure, or CVD-related death.

RESULTS

The prevalence of NAFLD and MAFLD was 28.0% and 37.3%, respectively. After excluding those with prior CVD, 8,962,813 participants were followed for a median of 10.1 years. NAFLD and MAFLD were each associated with significantly higher risk for CVD events. When the Neither-FLD group was the reference, multivariable-adjusted hazard ratios (95% confidence interval) for CVD events were 1.09 (1.03-1.15) in the NAFLD-only group, 1.43 (1.41-1.45) in the MAFLD-only group, and 1.56 (1.54-1.58) in the Both-FLD group.

CONCLUSIONS

A considerable proportion of middle-aged Korean adults have MAFLD without satisfying the former definition of NAFLD. The change from NAFLD to MAFLD criteria may identify a greater number of individuals with metabolically complicated fatty liver and increased risk for CVD.

Prediction of 8-year risk of cardiovascular diseases in Korean adult population

Although many prediction models for cardiovascular diseases (CVDs) have been developed and validated for Western populations, the development of CVD prediction models for Asians has been slow. Our cohort study retrospectively analyzed the incidence of CVD that occurred between January 1, 2009, and December 31, 2016, in all Koreans who underwent national health screening. This dataset included 21,581,796 adults between the ages of 40 and 79 years (10,412,947 men, 11,168,849 women) without CVD at baseline. The primary outcome, CVD, was defined as the development of any of the following: acute coronary syndrome, cerebral infarction, and cerebral hemorrhage, as defined with health insurance claims data. The prediction model was constructed by Cox proportional hazard regression and validated with tenfold cross-validation. The performance of the models was evaluated through Harrell's C-index and Brier score. The discrimination of the models was assessed by the area under the receiver operating characteristic curve (AUROC). Our model showed an AUROC of 0.762 in men and 0.811 in women. The Brier score of our model was 0.018 in men and 0.010 in women, which was better than the pooled cohort equation (PCE). Our novel model performed better than the FRS and PCE for Koreans.

Management of Cardiovascular Risk in Perimenopausal Women with Diabetes

Cardiovascular disease is the primary cause of mortality in women and men with diabetes. Due to age and worsening of risk factors over the menopausal transition, risk of coronary heart disease events increases in postmenopausal women with diabetes. Randomized studies have conflicted regarding the beneficial impact of estrogen therapy upon intermediate cardiovascular disease markers and events. Therefore, estrogen therapy is not currently recommended for indications other than symptom management. However, for women at low risk of adverse events, estrogen therapy can be used to minimize menopausal symptoms. The risk of adverse events can be estimated using risk engines for the calculation of cardiovascular risk and breast cancer risk in conjunction with screening tools such as mammography. Use of estrogen therapy, statins, and anti-platelet agents can be guided by such calculators particularly for younger women with diabetes. Risk management remains focused upon lifestyle behaviors and achieving optimal levels of cardiovascular risk factors, including lipids, glucose, and blood pressure. Use of pharmacologic therapies to address these risk factors, particularly specific hypoglycemic agents, may provide some additional benefit for risk prevention. The minimal benefit for women with limited life expectancy and risk of complications with intensive therapy should also be considered.

Prediction of 10-year atherosclerotic cardiovascular disease risk among community residents in Shanghai, China - a comparative analysis of risk algorithms

BACKGROUND AND AIMS

The accuracy of various 10-year atherosclerotic cardiovascular disease (ASCVD) risk models has been debatable. We compared two risk algorithms and explored clustering patterns across different risk stratifications among community residents in Shanghai.

METHODS AND RESULTS

A total of 28,201 residents (aged 40-74 years old) who were free of ASCVD were selected from the Shanghai Survey in China. The 10-year ASCVD risk was estimated by applying the 2013 Pooled Cohort Equations (PCEs) and Prediction for ASCVD Risk in China (China-PAR). The agreement was assessed between PCEs and China-PAR using Cohen's kappa statistics. The mean absolute 10-year ASCVD risk calculated by PCEs and China-PAR was about 10.0% and 6.0%, respectively. PCEs estimated that 44.9% of participants [with a 95% confidence interval (CI):44.0%-45.8%] were at high risk, while China-PAR estimated only 16.7% (95%CI:15.8%-18.0%) were at high risk. In both models, the percentage of high ASCVD risk was higher for participants who were older, men, less educated, current smokers, drinkers and manual workers. Among high-risk individuals, almost all participants (PCEs:90.5%; China-PAR:98.6%) had at least one risk factor; hypertension being the most prevalent. The concordance between PCEs and China-PAR was moderate (kappa:0.428, 95%CI: 0.420-0.434) with a better agreement for women (kappa:0.503,95%CI: 0.493-0.513) than for men (kappa:0.211,95%CI: 0.201-0.221).

CONCLUSION

The proportion of participants with a 10-year ASCVD high risk predicted by China-PAR was lower than the results of the PCEs. The risk stratifications of the two algorithms were inconsistent in terms of demographic and life-behaviour characteristics.

Prognostic value of lower bone mineral density in predicting adverse cardiovascular disease in Asian women

OBJECTIVE

We investigated whether the evaluation of bone mineral density (BMD) provides independent and incremental prognostic value for predicting atherosclerotic cardiovascular disease (ASCVD) in women.

METHODS

A total of 12 681 women aged 50-80 years (mean, 63.0±7.8 years) who underwent dual-energy X-ray absorptiometry were retrospectively analysed. We assessed the hazard ratio (HR) for ASCVD events (ASCVD death, non-fatal myocardial infarction and ischaemic stroke) according to the BMD or a clinical diagnosis of osteopenia or osteoporosis, with adjustment for clinical risk factors, including age, body mass index, hypertension, type 2 diabetes, hyperlipidaemia, current smoking and previous fracture. We also evaluated whether the addition of BMD or a clinical diagnosis of osteopenia or osteoporosis to clinical risk factors improved the prediction for ASCVD events.

RESULTS

In total, 468 women (3.7%) experienced ASCVD events during follow-up (median, 9.2 years). Lower BMD at the lumbar spine, femur neck and total hip was independently associated with higher risk for ASCVD events (adjusted HR per 1-standard deviation decrease in BMD: 1.16, p<0.001; 1.29, p<0.001; 1.38, p<0.001; respectively). A clinical diagnosis of osteoporosis was also independently associated with higher risk for ASCVD events (adjusted HR: 1.79, p<0.001). The addition of BMD or a clinical diagnosis of osteopenia or osteoporosis to clinical risk factors demonstrated significant incremental value in discriminating ASCVD events (addition of total hip BMD, p for difference <0.001).

CONCLUSION

The evaluation of BMD provides independent and incremental prognostic value for ASCVD in women and thus may improve risk stratification in women.

Cardiovascular Disease Prediction by Machine Learning Algorithms Based on Cytokines in Kazakhs of China

Background

Cardiovascular disease (CVD) is the leading cause of mortality worldwide. Accurately identifying subjects at high-risk of CVD may improve CVD outcomes. We sought to systematically examine the feasibility and performance of 7 widely used machine learning (ML) algorithms in predicting CVD risks.

Methods

The final analysis included 1508 Kazakh subjects in China without CVD at baseline who completed follow-up. All subjects were randomly divided into the training set (80%) and the test set (20%). L1-penalized logistic regression (LR), support vector machine with radial basis function (SVM), decision tree (DT), random forest (RF), k-nearest neighbors (KNN), Gaussian naive Bayes (NB), and extreme gradient boosting (XGB) were employed for prediction CVD outcomes. Ten-fold cross-validation was used during model developing and hyperparameters tuning in the training set. Model performance was evaluated in the test set in light of discrimination, calibration, and clinical usefulness. RF was applied to obtain the variable importance of included variables. Twenty-two variables, including sociodemographic characteristics, medical history, cytokines, and synthetic indices, were used for model development.

Results

Among 1508 subjects, 203 were diagnosed with CVD over a median follow-up of 5.17 years. All 7 models had moderate to excellent discrimination (AUC ranged from 0.770 to 0.872) and were well calibrated. LR and SVM performed identically with an AUC of 0.872 (95% CI: 0.829–0.907) and 0.868 (95% CI: 0.825–0.904), respectively. LR had the lowest Brier score (0.078) and the highest sensitivity (97.1%). Decision curve analysis indicated that SVM was slightly better than LR. The inflammatory cytokines, such as hs-CRP and IL-6, were identified as strong predictors of CVD.

Conclusion

SVM and LR can be applied to guide clinical decision-making in the Kazakh Chinese population, and further study is required to ensure their accuracies.

Histological severity of nonalcoholic fatty liver disease is associated with 10-year risk for atherosclerotic cardiovascular disease

BACKGROUND AND AIM

Nonalcoholic fatty liver disease (NAFLD) is associated with atherosclerotic cardiovascular disease (ASCVD). However, few studies have investigated the association between the histological severity of NAFLD and ASCVD. Therefore, we investigated whether the histological severity of NAFLD is associated with ASCVD risk.

METHODS

We performed cross-sectional analysis of prospectively enrolled, biopsy-proven NAFLD patients. The 10-year ASCVD risk was assessed using the Korean Risk Prediction Model. The histological spectrum of NAFLD was classified by the nonalcoholic steatohepatitis (NASH) clinical research network histological scoring system. The association between each histological subgroup and ASCVD risk was analyzed using logistic regression analysis.

RESULTS

This study included 398 Korean subjects (mean age, 57.9 years; male, 44.2%) with biopsy-proven NAFLD and 102 no-NALFD controls. Subjects with ASCVD risk ≥ 10% showed more severe grades of hepatocellular ballooning and more advanced stages of fibrosis when compared with subjects with ASCVD risk < 10% (p < 0.05 for each). The presence of NASH (odds ratio [OR] 4.07; 95% confidence interval [CI] 1.40-11.88) or advanced fibrosis (OR 8.11; 95% CI 1.83-35.98) was independently associated with a higher risk of ASCVD even after adjustment for age, sex, body mass index, blood pressure, lipids, liver enzymes, systemic inflammation, and insulin resistance.

CONCLUSIONS

Patients with NASH or advanced fibrosis are at an increased risk of developing ASCVD compared with no-NAFLD controls or subjects with NAFL, independent of conventional metabolic risk factors for CVD. Histological information on NAFLD may be helpful to promote our understanding of extrahepatic complications, such as ASCVD, resulting from NAFLD progression.

Machine Learning-Based Cardiovascular Disease Prediction Model: A Cohort Study on the Korean National Health Insurance Service Health Screening Database

Background: This study proposes a cardiovascular diseases (CVD) prediction model using machine learning (ML) algorithms based on the National Health Insurance Service-Health Screening datasets. Methods: We extracted 4699 patients aged over 45 as the CVD group, diagnosed according to the international classification of diseases system (I20–I25). In addition, 4699 random subjects without CVD diagnosis were enrolled as a non-CVD group. Both groups were matched by age and gender. Various ML algorithms were applied to perform CVD prediction; then, the performances of all the prediction models were compared. Results: The extreme gradient boosting, gradient boosting, and random forest algorithms exhibited the best average prediction accuracy (area under receiver operating characteristic curve (AUROC): 0.812, 0.812, and 0.811, respectively) among all algorithms validated in this study. Based on AUROC, the ML algorithms improved the CVD prediction performance, compared to previously proposed prediction models. Preexisting CVD history was the most important factor contributing to the accuracy of the prediction model, followed by total cholesterol, low-density lipoprotein cholesterol, waist-height ratio, and body mass index. Conclusions: Our results indicate that the proposed health screening dataset-based CVD prediction model using ML algorithms is readily applicable, produces validated results and outperforms the previous CVD prediction models.

Pre-existing and machine learning-based models for cardiovascular risk prediction

Predicting the risk of cardiovascular disease is the key to primary prevention. Machine learning has attracted attention in analyzing increasingly large, complex healthcare data. We assessed discrimination and calibration of pre-existing cardiovascular risk prediction models and developed machine learning-based prediction algorithms. This study included 222,998 Korean adults aged 40-79 years, naïve to lipid-lowering therapy, had no history of cardiovascular disease. Pre-existing models showed moderate to good discrimination in predicting future cardiovascular events (C-statistics 0.70-0.80). Pooled cohort equation (PCE) specifically showed C-statistics of 0.738. Among other machine learning models such as logistic regression, treebag, random forest, and adaboost, the neural network model showed the greatest C-statistic (0.751), which was significantly higher than that for PCE. It also showed improved agreement between the predicted risk and observed outcomes (Hosmer-Lemeshow χ2 = 86.1, P < 0.001) than PCE for whites did (Hosmer-Lemeshow χ2 = 171.1, P < 0.001). Similar improvements were observed for Framingham risk score, systematic coronary risk evaluation, and QRISK3. This study demonstrated that machine learning-based algorithms could improve performance in cardiovascular risk prediction over contemporary cardiovascular risk models in statin-naïve healthy Korean adults without cardiovascular disease. The model can be easily adopted for risk assessment and clinical decision making.

Sex differences in coronary artery calcium progression: The Korea Initiatives on Coronary Artery Calcification (KOICA) registry

Even with increasing awareness of sex-related differences in atherosclerotic cardiovascular disease (ASCVD), it remains unclear whether the progression of coronary atherosclerosis differs between women and men. We sought to compare coronary artery calcium (CAC) progression between women and men. From a retrospective, multicentre registry of consecutive asymptomatic individuals who underwent CAC scoring, we identified 9,675 men and 1,709 women with follow-up CAC scoring. At baseline, men were more likely to have a CAC score >0 than were women (47.8% vs. 28.6%). The probability of CAC progression at 5 years, defined as [√CAC score (follow-up)-√CAC score (baseline)] ≥2.5, was 47.4% in men and 29.7% in women (p<0.001). When we stratified subjects according to the 10-year ASCVD risk (<5%, ≥5% and <7.5%, and ≥7.5%), a sex difference was observed in the low risk group (CAC progression at 5 years, 37.6% versus 17.9%; p<0.001). However, it became weaker as the 10-year ASCVD risk increased (64.2% versus 46.2%; p<0.001, and 74.8% versus 68.7%; p = 0.090). Multivariable analysis demonstrated that male sex was independently associated with CAC progression rate among the entire group (p<0.001). Subgroup analyses showed an independent association between male sex and CAC progression rate only in the low-risk group. The CAC progression rate is higher in men than in women. However, the difference between women and men diminishes as the 10-year ASCVD risk increases.

The quest for cardiovascular disease risk prediction models in patients with nondialysis chronic kidney disease

PURPOSE OF REVIEW

Cardiovascular disease (CVD) is the leading cause of death in patients with chronic kidney disease (CKD). However, traditional CVD risk prediction equations do not work well in patients with CKD, and inclusion of kidney disease metrics such as albuminuria and estimated glomerular filtration rate have a modest to no benefit in improving prediction.

RECENT FINDINGS

As CKD progresses, the strength of traditional CVD risk factors in predicting clinical outcomes weakens. A pooled cohort equation used for CVD risk prediction is a useful tool for guiding clinicians on management of patients with CVD risk, but these equations do not calibrate well in patients with CKD, although a number of studies have developed modifications of the traditional equations to improve risk prediction. The reason for the poor calibration may be related to the fact that as CKD progresses, associations of traditional risk factors such as BMI, lipids and blood pressure with CVD outcomes are attenuated or reverse, and other risk factors may become more important.

SUMMARY

Large national cohorts such as the US Veteran cohort with many patients with evolving CKD may be useful resources for the developing CVD prediction models; however, additional considerations are needed for the unique composition of patients receiving care in these healthcare systems, including those with multiple comorbidities, as well as mental health issues, homelessness, posttraumatic stress disorders, frailty, malnutrition and polypharmacy. Machine learning over conventional risk prediction models may be better suited to handle the complexity needed for these CVD prediction models.

Cardiovascular Risk Calculators and their Applicability to South Asians

BACKGROUND

Estimation of absolute cardiovascular disease (CVD) risk and tailoring therapies according to the estimated risk is a fundamental concept in the primary prevention of CVD is assessed in this study. Numerous CVD risk scores are currently available for use in various populations but unfortunately, none exist for South Asians who have much higher CVD risk as compared to their western counterparts.

METHODS

A literature search was done using PubMed and Google search engines to prepare a narrative review on this topic.

RESULTS

Various currently available CVD risk scores and their pros and cons are summarized. The studies performed in native as well as migrant South Asians evaluating the accuracy of these risk scores for estimation of CVD risk are also summarized. The findings of these studies have generally been inconsistent, but it appears that the British risk scores (e.g. QRISK versions) may be more accurate because of inclusion of migrant South Asians in the derivation of these risk scores. However, the lack of any prospective study precludes our ability to draw any firm conclusions. Finally, the potential solution to these challenges, including the role of recalibration and subclinical atherosclerosis imaging, is also discussed.

CONCLUSION

This review highlights the need to develop large, representative, prospectively followed databases of South Asians providing information on various CVD risk factors and their contribution to incident CVD. Such databases will not only allow the development of validated CVD risk scores for South Asians but will also enable application of machine-learning approaches to provide personalized solutions to CVD risk assessment and management in these populations.

Antidepressant Use and the Risk of Major Adverse Cardiovascular Events in Patients Without Known Cardiovascular Disease: A Retrospective Cohort Study

Aims: Conflicting data exist on whether an association exists between antidepressants and the risk of major adverse cardiovascular events (MACEs) in patients with depression. This may be due to the use of various study designs and residual or unmeasured confounding. We aimed to assess the association between antidepressant use and the risk of MACEs while considering various covariates, including severity of depression and the cardiovascular disease (CVD) risk score.

Methods: Patients newly diagnosed with depression with no history of ischemic heart disease and stroke were followed-up from 2009 to 2015. We conducted Cox proportional hazard regression analysis to estimate hazard ratios (HRs) for each antidepressant for MACE risk.

Result: We followed-up (median, 4.4 years) 31,830 matched patients with depression (15,915 antidepressant users and 15,915 non-users). In most patients (98.7%), low-dose tricyclic antidepressants (TCAs) were related with a significantly increased risk of MACEs [adjusted HR = 1.20, 95% confidence interval (CI) = 1.03–1.40]. Duration response relationship showed a gradually increasing HR from 1.15 (95% CI = 0.98–1.33; <30 days of use) to 1.84 (95% CI = 1.35–2.51; ≥365 days of use) (p for trend <0.01). High Korean atherosclerotic CVD risk score (≥7.5%) or unfavorable lifestyle factors (smoking, alcohol intake, and exercise) were significantly associated with MACEs.

Conclusion: Even at low doses, TCA use was associated with MACEs during primary prevention. Longer duration of TCA use correlated with higher HR. Careful monitoring is needed with TCA use in patients with no known CVD history.