Pooled Cohort Equations Research Articles

External Validation of the American Heart Association PREVENT Cardiovascular Disease Risk Equations

The American Heart Association's Predicting Risk of Cardiovascular Disease Events (PREVENT) equations were developed to extend and improve on previous cardiovascular disease (CVD) risk assessments for the purpose of treatment initiation and patient-clinician communication. To assess prognostic capabilities, calibration, and discrimination of the PREVENT equations in a study sample representative of the noninstitutionalized, US general population. This prognostic study used data from the National Health and Nutrition Examination Survey (NHANES) 1999 to 2010 data cycles. Participants included adults for whom 10-year follow-up data were available. Data curation and analyses took place from December 2023 through May 2024. Primary measures were risk estimated by the PREVENT equations, as well as risk estimates from the previous Pooled Cohort Equations (PCEs). The primary outcome was composite CVD-related mortality at 10 years of follow-up. Additional analyses compared the PREVENT equations against the PCEs. Model discrimination was assessed with receiver-operator characteristic curves and Harrell C statistic from proportional hazard regression; model calibration was determined as the slope of predicted versus observed risk. The study cohort, accounting for NHANES complex survey design, consisted of 172.9 million participants (mean age, 45.0 years [95% CI, 44.6-45.4 years]; 52.1% women [95% CI, 51.5%-52.6%]). In analyses adjusted for the NHANES survey design, a 1% increase in PREVENT risk estimates was statistically significantly associated with increased CVD mortality risk (hazard ratio, 1.090; 95% CI, 1.087-1.094). PREVENT risk scores demonstrated excellent discrimination (C statistic, 0.890; 95% CI, 0.881-0.898) but moderate underfitting of the model (calibration slope, 1.13; 95% CI, 1.06-1.21). PREVENT risk models performed statistically significantly better than the PCEs, as assessed by the net reclassification index (0.093; 95% CI, 0.073-0.115). In this prognostic study of the PREVENT equations, PREVENT risk estimates demonstrated excellent discrimination and only modest discrepancies in calibration. These findings provided evidence supporting utilization of the PREVENT equations for application in the intended population as suggested by the American Heart Association.

Comparison of pooled cohort equation and PREVENT™ risk calculator for statin treatment allocation

Comparison of pooled cohort equation and PREVENT™ risk calculator for statin treatment allocation

Hormones, Stress, and Heart Disease in Transgender Women with HIV in LITE Plus

Cardiovascular disease (CVD) is a leading cause of death among transgender women and people with HIV. Exogenous estrogen and psychosocial stressors are known risk factors for CVD. Yet, few studies have used biomarkers to examine the role of stress in CVD risk among transgender women with HIV (TWHIV). This analysis examined whether stress moderates relationships between gender-affirming hormone therapy (GAHT) duration and CVD risk among TWHIV. This cross-sectional analysis of baseline data from an observational cohort of 108 Black and Latina TWHIV in Boston, New York, and Washington, DC, enrolled December 2020 to June 2022, measured sociodemographics, medical diagnoses, medications, smoking history, and perceived stress via interviewer-administered surveys. Physiological stress was measured with 14 biomarkers to calculate allostatic load indices (ALI). Forty participants provided saliva samples used to calculate cortisol awakening response and cortisol daily decline. The 2018 American College of Cardiology Revised Pooled Cohort Equation estimated 10-year CVD risk. Data were analyzed in 2024. GAHT duration was positively associated with CVD risk scores in bivariate regression. In multivariable linear regression models (adjusting for age, income, education), only age and ALI remained significantly associated with CVD risk scores (β 1.13, CI: 1.05, 1.21). No stress measure significantly interacted with GAHT duration to affect CVD risk scores. In visual plots, GAHT duration increased CVD risk scores only for TWHIV experiencing the highest ALI. Stress plays an important role in CVD in TWHIV. More research is needed on non-GAHT factors, which influence CVD health among transgender women.

PREVENT Equation: The Black Sheep among Cardiovascular Risk Scores? A Comparative Agreement Analysis of Nine Prediction Models in High-Risk Lithuanian Women.

Background and Objectives: In the context of female cardiovascular risk categorization, we aimed to assess the inter-model agreement between nine risk prediction models (RPM): the novel Predicting Risk of cardiovascular disease EVENTs (PREVENT) equation, assessing cardiovascular risk using SIGN, the Australian CVD risk score, the Framingham Risk Score for Hard Coronary Heart Disease (FRS-hCHD), the Multi-Ethnic Study of Atherosclerosis risk score, the Pooled Cohort Equation (PCE), the QRISK3 cardiovascular risk calculator, the Reynolds Risk Score, and Systematic Coronary Risk Evaluation-2 (SCORE2). Materials and Methods: A cross-sectional study was conducted on 6527 40-65-year-old women with diagnosed metabolic syndrome from a single tertiary university hospital in Lithuania. Cardiovascular risk was calculated using the nine RPMs, and the results were categorized into high-, intermediate-, and low-risk groups. Inter-model agreement was quantified using Cohen's Kappa coefficients. Results: The study uncovered a significant diversity in risk categorization, with agreement on risk category by all models in only 1.98% of cases. The SCORE2 model primarily classified subjects as high-risk (68.15%), whereas the FRS-hCHD designated the majority as low-risk (94.42%). The range of Cohen's Kappa coefficients (-0.09-0.64) reflects the spectrum of agreement between models. Notably, the PREVENT model demonstrated significant agreement with QRISK3 (κ = 0.55) and PCE (κ = 0.52) but was completely at odds with the SCORE2 (κ = -0.09). Conclusions: Cardiovascular RPM selection plays a pivotal role in influencing clinical decisions and managing patient care. The PREVENT model revealed balanced results, steering clear of the extremes seen in both SCORE2 and FRS-hCHD. The highest concordance was observed between the PREVENT model and both PCE and QRISK3 RPMs. Conversely, the SCORE2 model demonstrated consistently low or negative agreement with other models, highlighting its unique approach to risk categorization. These findings accentuate the need for additional research to assess the predictive accuracy of these models specifically among the Lithuanian female population.

Comparing Cardiovascular Risk Classification of U.S. Adults According to Pooled Cohort Equations and PREVENT Equations: Cross-Sectional Analysis of the National Health and Nutrition Examination Survey.

Comparing Cardiovascular Risk Classification of U.S. Adults According to Pooled Cohort Equations and PREVENT Equations: Cross-Sectional Analysis of the National Health and Nutrition Examination Survey.

Triglyceride-rich lipoproteins cholesterol, 10-years atherosclerotic cardiovascular disease risk, and risk of myocardial infarction and ischemic stroke

Triglyceride-rich lipoproteins cholesterol (TRLs-C) has been associated with atherosclerotic cardiovascular disease (ASCVD), even among individuals with low-density lipoprotein cholesterol in the targeted range. We assessed the associations of TRLs-C with myocardial infarction (MI) and ischemic stroke (IS) and compared the associations with those for other traditional lipids (i.e., triglycerides and non-high-density lipoprotein cholesterol [non-HDL-C]). Included were 327,899 participants from the UK Biobank who were free of MI or IS and did not receive lipid-lowering treatment at baseline. Ten-year risk for ASCVD was estimated by the Pooled Cohort Equations and was grouped as low (<7.5%), intermediate (7.5% to <20%), and high risk (≥20%). Multivariable Cox regression models were used to examine the associations of TRLs-C, triglycerides, and non-HDL-C with risk of MI and IS, overall and by the 10-years risk categories. During a median of 12.3 years of follow-up, 8,358 incident MI and 4,400 incident IS cases were identified. After multivariable adjustment, higher TRLs-C was associated with a higher risk of MI (p-trend <0.0001) but not IS (p-trend = 0.074), with similar associations for triglycerides and non-HDL-C. There were interactions between TRLs-C and 10-years ASCVD risk on risk of MI (p-interaction <0.0001) and IS (p-interaction = 0.0003). Hazard ratios (95% CIs) of MI comparing the highest with the lowest quartiles of TRLs-C were 2.10 (1.23–1.30) in the low-risk group, 1.52 (1.38–1.69) in the intermediate-risk group, and 1.22 (1.03–1.45) in the high-risk group. The corresponding estimates for IS were 1.24 (1.05–1.45), 0.94 (0.83–1.07), and 0.83 (0.67–1.04), respectively. Similar interactions with the 10-years ASCVD risk were observed for triglycerides and non-HDL-C on risk of MI and for triglycerides on risk of IS. Elevated levels of TRLs-C (or triglycerides or non-HDL-C) are associated with a higher risk of developing MI and IS (except non-HDL-C) predominantly among individuals who are typically classified as being low-risk. These findings may have implications for more detailed risk stratification and early intervention.

P129 ASSESS THE ACCURACY OF FOUR RISK ASSESSMENT MODELS (RISKFRS, RISKWHO, RISKACC/AHA, AND RISKJBS) IN PREDICTING 10-YEAR CARDIOVASCULAR EVENT RISK IN INDIAN ACUTE MYOCARDIAL INFARCTION PATIENTS

Background: Despite numerous risk assessment models available for estimating the 10-year risk of cardiovascular (CV) events in individuals requiring primary prevention of CV disease, their applicability and accuracy in the Indian population remain inadequately studied. Objective of the study is to Assess and compare the predictive accuracy of four cardiovascular risk assessment models—RiskFRS, RiskWHO, RiskACC/AHA, and RiskJBS—in determining the 10-year cardiovascular event risk among Indian acute MI patients. Methods: In this study, 250 participants (mean age 59.4 ± 10.6 years; 205 males) without prior cardiovascular disease who experienced acute myocardial infarction (MI) were assessed using four established risk assessment models: Framingham Risk Score (RiskFRS), World Health Organization risk prediction charts (RiskWHO), American College of Cardiology/American Heart Association pooled cohort equations (RiskACC/AHA), and the 3rd Joint British Societies’ risk calculator (RiskJBS). These models estimated the participants’ predicted 10-year risk of cardiovascular events if assessed before the acute MI. Results: RiskWHO provided the lowest risk estimates, with 86.6% of patients estimated to have less than 20% 10-year risk. Conversely, RiskFRS and RiskACC/AHA yielded higher risk estimates (61.7% and 69.8% with less than 20% risk, respectively; p values &lt;0.001 compared to RiskWHO). However, RiskJBS identified the highest proportion of patients as high-risk (only 44.1% at less than 20% risk, p values &lt; 0.01 compared to all other three risk scores). Conclusions: In Indian patients experiencing acute MI, RiskJBS identifies a larger proportion of patients as ’high-risk’ compared to RiskWHO, RiskFRS, and RiskACC/AHA. However, further validation through large-scale prospective studies is necessary. These findings underscore the importance of tailoring risk assessment models to the unique characteristics of the Indian population and highlight the need for additional research to optimize cardiovascular risk prediction and management strategies in this demographic.

Cardiovascular risk in US adults with nonalcoholic steatohepatitis (NASH) vs. matched non-NASH controls, National Health and Nutrition Examination Survey, 2017-2020.

NASH is considered a contributor to atherosclerotic cardiovascular disease (ASCVD) risk; however, its contribution beyond traditional risk factors for CVD, particularly diabetes, is less clearly understood. This study aimed to quantify the cardiovascular-event risk associated with NASH, independent of diabetes status. A cross-sectional analysis was conducted using the 2017-2020 NHANES pre-pandemic cycle. NASH was defined based on presence of steatosis without other causes of liver disease, and FibroScan+AST score from vibration-controlled transient elastography (VCTE). Significant fibrosis (stages F2-F4) was identified by liver stiffness measurement from VCTE. Predicted primary CV-event risk was estimated using both the Pooled Cohort Equations (PCE) and the Framingham Risk Score (FRS). NASH patients were matched with non-NASH controls on age, sex, race/ethnicity, and diabetes status. Weighted logistic regression was conducted, modeling elevated predicted CV risk (binary) as the dependent variable and indicators for NASH / fibrosis stages as independent variables. A sample of 125 NASH patients was matched with 2585 controls. NASH with significant fibrosis was associated with elevated predicted 10-year CV risk, although this association was only statistically significant in PCE analyses (odds ratio and 95% CI 2.34 [1.25, 4.36]). Analyses restricting to ages <65 years showed similar results, with associations of greater magnitude. Independent of diabetes, a significant association was observed between NASH with significant liver fibrosis and predicted primary CV-event risk in US adults, particularly for those <65. These findings suggest the importance of accounting for NASH and liver-fibrosis stage in predicting CV-event risk.

Changes in Atherosclerotic Cardiovascular Disease Risk Scores in a Predominantly Black Cohort with HIV and Associated Comorbidities: A Preliminary Study.

People with HIV (PWH) have an increased risk of atherosclerotic cardiovascular disease (ASCVD) compared to non-PWH, but the reasons for this increased risk remain elusive. We investigated the change in ASCVD risk scores over 4 years to identify clinical factors associated with change in risk scores or high-risk scores. We conducted a preliminary study using retrospective analysis of PWH, between 40 and 75 years old, seen at the Evelyn Jordan Center with at least two routine HIV visits. We collected clinical and demographic data and calculated the ASCVD risk scores using the Pooled Cohort Equation. Exploratory analyses examined change in risk score categories over time. Final adjusted analysis examined factors associated with change in continuous risk scores over time. Our sample included 187 PWH; 166 were black/African American and 79 were female. We found no significant change in ASCVD risk score over time. The risk score was significantly higher in PWH with hepatitis C (7.34%; 95% CI: 2.59, 12.09; p = 0.003) and trended higher in those with dual hepatitis B/C and hepatitis B compared to those without hepatitis (p = 0.07). We found that ASCVD risk did not change over a 4-year period among predominantly black young PWH, but infection with hepatitis C and dual hepatitis B/C were associated with higher ASCVD risk scores. Our findings illustrate the need for further longitudinal studies evaluating change in cardiovascular disease (CVD) risk and investigating viral hepatitis as an added potential contributor to increased CVD risk in high-risk, vulnerable populations.

Cardiovascular predicted risk: A population-based comparison of the pooled cohorts equation and PREVENT

BackgroundWhile the new cardiovascular risk score (PREVENT) has improvements, its implementation may lead to significant changes in the distribution of atherosclerotic cardiovascular diseases (ASCVD) in the United States. We aimed to quantify and characterize the distribution of the 10-year predicted absolute ASCVD risk using the Pooled Cohorts Equation (PCE) and PREVENT. MethodsWe utilized the latest (2017-March 2020) round of the National Health and Nutrition Examination Survey (NHANES). Accounting for the complex survey design of the NHANES, we computed the mean predicted ASCVD risk overall and by sex, race, and education; similarly, we computed the prevalence of cardiovascular risk groups (<5%, 5%–7.4%, 7.5%–19.9%, and ≥ 20%). ResultsThe study included 3845 observations, representing 109,692,509 people. Using the PREVENT calculator resulted in a reduction of the mean 10-year ASCVD absolute risk by half compared to the PCE: 9.1% vs 4.7%. Under the PCE, the high-risk category accounted for 12.5% of the population, whereas under PREVENT it fell to 0.4%. Among those previously classified as high-risk under the PCE, 3.5% would remain in this category with PREVENT, while 93% would be reclassified as intermediate risk. ConclusionsThe adoption of the novel cardiovascular risk score, PREVENT, could lower the average predicted ASCVD risk and reduce the prevalence of high-risk individuals. While this shift might suggest improved cardiovascular health, it could also lead to complacency, potentially undermining ongoing public health efforts aimed at preventing cardiovascular disease.

Risk scores and coronary artery disease in patients with suspected acute coronary syndrome and intermediate cardiac troponin concentrations

BackgroundGuidelines recommend the use of risk scores to select patients for further investigation after myocardial infarction has been ruled out but their utility to identify those with coronary artery disease...

Association Between Kidney Stone History and Cardiovascular Event Risk in US Adults

ObjectivesTo determine the association between kidney stone history and predicted 10-year risk of atherosclerotic cardiovascular disease events in a nationally representative US adult sample without existing cardiovascular disease. MethodsThis was a cross-sectional study of the 2017-2020 National Health and Nutrition Examination Survey that included a nationally representative sample of 3,842 adults aged 40-79 free from cardiovascular disease. Kidney stone history was assessed through self-reporting. The 10-year risk of an atherosclerotic cardiovascular disease event was predicted using the American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort Equations. ResultsThe weighted prevalence of kidney stones was 12.2% (95% CI: 10.5% to 14.1%). In unadjusted analysis, the odds of borderline or higher (≥5%) atherosclerotic cardiovascular disease risk were higher in stone formers (odds ratio=1.56; 95% CI 1.01-2.40; P=0.046). This association persisted after adjustment for demographics and clinical covariates (adjusted odds ratio=1.57; 95% CI=1.02 to 2.43; P=0.04). A significant interaction by biological sex was identified (p=0.002), with excess risk conferred by kidney stones in men but not women. ConclusionsKidney stone history was independently associated with increased 10-year predicted atherosclerotic cardiovascular disease event risk, with excess risk observed among men but not women. Intensified cardiovascular disease screening may be warranted among stone formers given their increased cardiovascular risk.

Titin truncating variants, cardiovascular risk factors and the risk of atrial fibrillation and heart failure.

High-proportion spliced-in (hiPSI) titin truncating variant (TTNtv) carriers have a higher risk of atrial fibrillation and heart failure1. However, the role of cardiovascular risk factors in modifying the risk of atrial fibrillation and heart failure attributed to hiPSI TTNtv carriers is unknown. Here, we investigate the role of cardiovascular risk, quantified using the pooled cohort equations (PCEs), in influencing the hazard of outcomes attributed to hiPSI TTNtvs among UK Biobank participants without baseline cardiovascular disease. The cohort was stratified based on hiPSI TTNtv carrier status and cardiovascular risk (low: <5%, intermediate: 5.0-7.5% and high: >7.5%). The primary outcome was a composite of atrial fibrillation, heart failure or death. TTNtv noncarriers with low cardiovascular risk were used as the reference group for all analyses. Among 179,752 participants (median age: 56 (49, 62) years; 57.5% female), the risk of the primary outcome was lower in hiPSI TTNtv carriers with low cardiovascular risk (adjusted hazard ratio: 2.23 (95% confidence interval: 1.62-3.07)) than those with high cardiovascular risk (adjusted hazard ratio: 8.21 (95% confidence interval: 6.63-10.18)). A favorable cardiovascular risk factor profile may partially offset the risk of clinical outcomes among hiPSI TTNtv carriers.

The association between objectively-measured sedentary behavior patterns and predicted 10-year ASCVD risk

This study aims to investigated the association between sedentary behavior (SB) and predicted 10-year atherosclerotic cardiovascular disease (ASCVD) risk and determine whether the associations differ by how the behavior is accumulated, in US middle-aged and older adults. Cross-sectional data were derived from national health and nutrition examination survey (NHANES) 2003–2006. Seven-day wearing of accelerometer was used to assess SB pattern, exported as total SB, bouts of 1–9, 10–29, 30–59 and ≥ 60 min SB. Predicted 10-year ASCVD risk was calculated using validated pooled cohort equations. Linear regression was used to estimate adjusted coefficients. A total of 2327 participants were enrolled with mean age of 56.9 and mean predicted 10-year ASCVD risk of 10.7%. We observed significant associations of total SB and its longer accumulated patterns with higher 10-year predicted ASCVD risk, in a linear fashion and independent of a list of covariates. A 30 min increment per day of total SB, bouts in 10–29, bouts in 30–59 and bouts in ≥ 60 min were associated with 0.14, 0.14, 0.23 and 0.12% higher multivariable-adjusted 10-year predicted ASCVD risk. There are significant associations of total SB as well as its longer accumulated patterns with higher 10-year predicted ASCVD risk, independent of a list of covariates and in a linear fashion. The result indicates that reducing total sedentary time and interrupting long duration of prolonged SB, could be meaningful to for public guideline to lessen the personal and public health burden of cardiovascular health.

Projected Changes in Statin and Antihypertensive Therapy Eligibility With the AHA PREVENT Cardiovascular Risk Equations

Since 2013, the American College of Cardiology (ACC) and American Heart Association (AHA) have recommended the pooled cohort equations (PCEs) for estimating the 10-year risk of atherosclerotic cardiovascular disease (ASCVD). An AHA scientific advisory group recently developed the Predicting Risk of cardiovascular disease EVENTs (PREVENT) equations, which incorporated kidney measures, removed race as an input, and improved calibration in contemporary populations. PREVENT is known to produce ASCVD risk predictions that are lower than those produced by the PCEs, but the potential clinical implications have not been quantified. To estimate the number of US adults who would experience changes in risk categorization, treatment eligibility, or clinical outcomes when applying PREVENT equations to existing ACC and AHA guidelines. Nationally representative cross-sectional sample of 7765 US adults aged 30 to 79 years who participated in the National Health and Nutrition Examination Surveys of 2011 to March 2020, which had response rates ranging from 47% to 70%. Differences in predicted 10-year ASCVD risk, ACC and AHA risk categorization, eligibility for statin or antihypertensive therapy, and projected occurrences of myocardial infarction or stroke. In a nationally representative sample of 7765 US adults aged 30 to 79 years (median age, 53 years; 51.3% women), it was estimated that using PREVENT equations would reclassify approximately half of US adults to lower ACC and AHA risk categories (53.0% [95% CI, 51.2%-54.8%]) and very few US adults to higher risk categories (0.41% [95% CI, 0.25%-0.62%]). The number of US adults receiving or recommended for preventive treatment would decrease by an estimated 14.3 million (95% CI, 12.6 million-15.9 million) for statin therapy and 2.62 million (95% CI, 2.02 million-3.21 million) for antihypertensive therapy. The study estimated that, over 10 years, these decreases in treatment eligibility could result in 107 000 additional occurrences of myocardial infarction or stroke. Eligibility changes would affect twice as many men as women and a greater proportion of Black adults than White adults. By assigning lower ASCVD risk predictions, application of the PREVENT equations to existing treatment thresholds could reduce eligibility for statin and antihypertensive therapy among 15.8 million US adults.

External validation and comparison of six cardiovascular risk prediction models in the Prospective Urban Rural Epidemiology (PURE)-Colombia study.

To external validate the SCORE2, AHA/ACC Pooled Cohort Equation (PCE), Framingham Risk Score (FRS), Non-Laboratory INTERHEART Risk Score (NL-IHRS), Globorisk-LAC, and WHO prediction models and compare their discrimination and calibration capacity. Validation in individuals aged 40-69 years with at least 10 years follow-up and without baseline use of statins or cardiovascular diseases from the Prospective Urban Rural Epidemiology prospective cohort study (PURE)-Colombia. For discrimination, the C-statistic, and Receiver Operating Characteristic curves with the integrated area under the curve (AUCi) were used and compared. For calibration, the smoothed time-to-event method was used, choosing a recalibration factor based on the integrated calibration index (ICI). In the NL-IHRS, linear regressions were used. In 3,802 participants (59.1% women), baseline risk ranged from 4.8% (SCORE2 women) to 55.7% (NL-IHRS). After a mean follow-up of 13.2 years, 234 events were reported (4.8 cases per 1000 person-years). The C-statistic ranged between 0.637 (0.601-0.672) in NL-IHRS and 0.767 (0.657-0.877) in AHA/ACC PCE. Discrimination was similar between AUCi. In women, higher overprediction was observed in the Globorisk-LAC (61%) and WHO (59%). In men, higher overprediction was observed in FRS (72%) and AHA/ACC PCE (71%). Overestimations were corrected after multiplying by a factor derived from the ICI. Six prediction models had a similar discrimination capacity, supporting their use after multiplying by a correction factor. If blood tests are unavailable, NL-IHRS is a reasonable option. Our results suggest that these models could be used in other countries of Latin America after correcting the overestimations with a multiplying factor.

Adoption of the PREVENT (Predicting Risk of Cardiovascular Disease EVENTs) Risk Algorithm: Potential International Implications

BackgroundThe PREVENT (Predicting Risk of cardiovascular disease EVENTs risk algorithm was developed to better reflect the impact of metabolic factors on cardiovascular risk. ObjectivesThe purpose of this study was to compare the relative performance of PREVENT with standard comparator algorithms (Framingham risk score, pooled cohort equation, SCORE2 [Systematic COronary Risk Evaluation2]) for risk stratification emphasizing the implications of weighing chronic kidney disease. MethodsA simulated cohort was created of males and females aged 40 to 75 years with and without other traditional risk factors and either normal estimated glomerular filtration rates (eGFR 90 or 60 ml/min/1.73 m2) or abnormal eGFR (45 or 30 ml/min/1.73 m2). The concordance and reclassification rates were calculated for each category of risk with emphasis on subjects characterized as moderate risk by the standard comparator algorithms. ResultsPREVENT demonstrated increased risk with progressive decreases in eGFR. When the standard comparator algorithms identified moderate risk, PREVENT was concordant in 6% to 88% of simulations. In simulations with normal eGFR, PREVENT identified a lower risk in 18% to 88% and a higher risk in 0% to 12% of simulations. Conversely, with abnormal eGFR, PREVENT identified lower risk in 0% to 26% and higher risk in 4% to 94% of simulations. ConclusionsPREVENT substantially reclassifies risk and has the potential to alter prevention practice patterns. The tendency to assign a lower risk compared to standard algorithms when eGFR is normal may diminish implementation of preventive therapy. National health care systems need to monitor whether such changes improve overall public health.

Predicted Cardiovascular Risk by the PREVENT Equations in US Adults With Stage 1 Hypertension.

The 2017 American College of Cardiology/American Heart Association blood pressure guideline recommends initiation of antihypertensive medication for adults with stage 1 hypertension (systolic blood pressure, 130-139 mm Hg, or diastolic blood pressure, 80-89 mm Hg) and 10-year atherosclerotic cardiovascular disease (ASCVD) risk ≥10% estimated by the pooled cohort equations (PCEs). In 2023, the American Heart Association published the predicting risk of cardiovascular disease events (PREVENT) equations to estimate ASCVD and total cardiovascular disease risk. We analyzed US National Health and Nutrition Examination Survey data from 2013 to 2020 for 1703 adults aged 30 to 79 years without self-reported cardiovascular disease with stage 1 hypertension. We estimated 10-year ASCVD risk by the PCEs and 10-year ASCVD and total cardiovascular disease risk by the base PREVENT equations. Analyses were weighted to represent noninstitutionalized US adults with stage 1 hypertension. Mean 10-year ASCVD risk was 5.4% (95% CI, 5.0%-5.9%) and 2.9% (95% CI, 2.7%-3.1%) using the PCEs and PREVENT equations, respectively. The proportion with 10-year ASCVD risk of 10% to <15% and ≥15% was 8.1% and 7.8% estimated by the PCEs, respectively, and 3.0% and 0.3% estimated by the PREVENT equations, respectively. No participants had a 10-year ASCVD risk ≥10% on the PREVENT equations and <10% on the PCEs, while 12.5% had a 10-year ASCVD risk ≥10% on the PCEs and <10% on the PREVENT equations. The mean 10-year total cardiovascular disease risk estimated by the PREVENT equations was lower than the mean 10-year ASCVD risk on the PCEs. Among US adults with stage 1 hypertension, the 10-year predicted ASCVD risk estimated by the PREVENT equations was approximately half the risk estimated by the PCEs.

Self-Report Tool for Identification of Individuals With Coronary Atherosclerosis: The Swedish CardioPulmonary BioImage Study.

Coronary atherosclerosis detected by imaging is a marker of elevated cardiovascular risk. However, imaging involves large resources and exposure to radiation. The aim was, therefore, to test whether nonimaging data, specifically data that can be self-reported, could be used to identify individuals with moderate to severe coronary atherosclerosis. We used data from the population-based SCAPIS (Swedish CardioPulmonary BioImage Study) in individuals with coronary computed tomography angiography (n=25 182) and coronary artery calcification score (n=28 701), aged 50 to 64 years without previous ischemic heart disease. We developed a risk prediction tool using variables that could be assessed from home (self-report tool). For comparison, we also developed a tool using variables from laboratory tests, physical examinations, and self-report (clinical tool) and evaluated both models using receiver operating characteristic curve analysis, external validation, and benchmarked against factors in the pooled cohort equation. The self-report tool (n=14 variables) and the clinical tool (n=23 variables) showed high-to-excellent discriminative ability to identify a segment involvement score ≥4 (area under the curve 0.79 and 0.80, respectively) and significantly better than the pooled cohort equation (area under the curve 0.76, P<0.001). The tools showed a larger net benefit in clinical decision-making at relevant threshold probabilities. The self-report tool identified 65% of all individuals with a segment involvement score ≥4 in the top 30% of the highest-risk individuals. Tools developed for coronary artery calcification score ≥100 performed similarly. We have developed a self-report tool that effectively identifies individuals with moderate to severe coronary atherosclerosis. The self-report tool may serve as prescreening tool toward a cost-effective computed tomography-based screening program for high-risk individuals.

Associations of 10-year atherosclerotic cardiovascular disease risk scores with cerebral small vessel disease: the PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events (PRECISE) study.

10-year atherosclerotic cardiovascular disease (ASCVD) risk scores were useful for predicting large vessel disease, but the relationships between them and cerebral small vessel disease (CSVD) were unclear. Our study aimed to evaluate associations of 10-year ASCVD risk scores with CSVD and its magnetic resonance imaging (MRI) markers. Community-dwelling residents from the PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events study were included in this cross-sectional study. At baseline, we collected data related to the Framingham Risk Score (FRS), pooled cohort equation (PCE), prediction for ASCVD risk in China (China-PAR) and Systematic COronary Risk Evaluation model 2 (SCORE2), and classified participants into low, moderate and high groups. Participants underwent brain MRI scans. We evaluated white matter hyperintensity (WMH), lacunes, cerebral microbleeds (CMBs) and enlarged perivascular spaces in basal ganglia (BG-EPVS) according to criteria of Wardlaw and Rothwell, and calculated total CSVD score and modified total CSVD score. A total of 3063 participants were included, and 53.5% of them were female. A higher FRS was associated with higher total CSVD score (moderate vs. low: cOR 1.89, 95% CI 1.53-2.34; high vs. low: cOR 3.23, 95%CI 2.62-3.97), and the PCE, China-PAR or SCORE2 score was positively related to total CSVD score (P < 0.05). Moreover, higher 10-year ASCVD scores were associated with higher odds of WMH (P < 0.05), lacunes (P < 0.05), CMBs (P < 0.05) and BG-EPVS (P < 0.05). The 10-year ASCVD scores were positively associated with CSVD and its MRI markers. These scores provided a method of risk stratification in the population with CSVD.