10-year Risk Research Articles

Corrigendum: Association between admission inflammatory indicators and 3-year mortality risk in geriatric patients after hip fracture surgery: a retrospective analysis of a prospective cohort study

Corrigendum: Association between admission inflammatory indicators and 3-year mortality risk in geriatric patients after hip fracture surgery: a retrospective analysis of a prospective cohort study

Impact of arteriovenous fistula formation on trajectory of kidney function decline: a target trial emulation

Abstract Background Prior nonrandomised studies have suggested nephroprotective effects of arteriovenous fistula (AVF) formation, but these are plausibly susceptible to immortal time and selection biases. Methods We studied patients attending nephrology clinics in the West of Scotland during 2010-2022 with an eGFR ≤15mL/min/1.73m2 and no prior AVF. Using target trial emulation and a sequential trial design, we simulated a hypothetical trial that would randomise patients to either undergo AVF formation immediately or not to undergo AVF formation. The primary outcome was the difference in eGFR slope for the first six months of follow-up, estimated using a mixed-effects model. The secondary outcomes were 5-year absolute risks of dialysis and death, estimated using the Aalen-Johansen and Kaplan-Meier estimators respectively. Results 1,364 unique patients (mean age 51.1, 55.7% male) contributed 3,125 person-trials, with 561 in the AVF and 2,564 in the no AVF group. Mean eGFR was 12.6mL/min/1.73m2 and the median number of eGFR measurements per person-trial was 7 (IQR 4 – 12). Slope of eGFR decline did not differ significantly between the AVF and no AVF groups (between group difference -0.67mL/min/1.73m2/year, 95%CI -1.43, 0.10). The 5-year absolute risk of dialysis was 87% (95%CI 84, 91) in the AVF group and 75% (95%CI 73, 77) in the no AVF group and the 5-year survival probability was 77% (95%CI 70, 83) in the AVF group and 67% (95%CI 64, 69) in the no AVF group. Conclusions In this study of patients with advanced CKD, there was no evidence of a nephroprotective effect of AVF formation.

Guideline-directed antihypertensive medication use among young adult participants with uncontrolled hypertension at enrollment in the MyHEART study.

Hypertension is a major risk factor for heart disease, heart failure and stroke. Lifestyle changes are recommended as first-line treatment for management of high blood pressure for young adults, when 10-year atherosclerotic cardiovascular disease risk score is < 10%. If lifestyle changes alone do not control blood pressure, then providers have access to four classes of first-line blood pressure lowering agents to treat hypertension, when other contra-indications are not present. This is a cross-sectional, retrospective, secondary analysis performed of the MyHEART trial on study participants at enrollment to determine they were prescribed anti-hypertensive medication. Of those prescribed medications, we aimed to determine the frequency first-line medications including thiazide or thiazide-like diuretics, angiotensin converting-enzyme inhibitors, angiotensin receptor blockers, and calcium channel blockers were prescribed. This analysis categorized participants into four medication status categories: no antihypertensive medication, prescribed only first-line antihypertensives, prescribed only non-first-line antihypertensives, and prescribed a combination of first-line and non-first-line antihypertensives. Participant clinical and sociodemographic factors by medication use were evaluated. Linear regression models were fit to determine the association between antihypertensive medication and blood pressure. At enrollment, 157/311 (50.5%) participants were not on antihypertensives. Of the 154 on antihypertensives, reported use included monotherapy 97/154 (63.0%), combined therapy 57/154 (37.0%), only first-line antihypertensive 111/154 (72.0%), and only non-first-line antihypertensives 21/154 (13.6%), and combination of first-line and non-first-line antihypertensives 22/154 (14.2%). Antihypertension medication use varied based on age (p < 0.001), sex (p = 0.008), race (p = 0.001), body mass index (BMI) kg/m2 (p = 0.016), anxiety and/or depression (p = 0.048), diabetes (p = 0.007), and sodium intake (p = 0.042). Participants with only first-line medications had lower in-office systolic (-4.66 mmHg, CI -8.31 to -1.02, p = 0.013) and diastolic (-3.51 mmHg, CI -6.30 to -0.71, p = 0.015), and lower ambulatory diastolic (-2.12 mmHg, CI -4.15 to -0.09, p = 0.041) blood pressure than those without antihypertensives. Among MyHEART study participants, all of which had uncontrolled hypertension, 50.5% were not on an antihypertensive at enrollment. This finding supports the call to improve management of blood pressure earlier in life to potentially contribute to the reduction of long-term cardiovascular disease. Of the participants who were prescribed blood pressure medication, providers prescribed guideline-based antihypertensive therapy the majority of the time, however, this study indicates there may be an opportunity to increase the use of first-line, guideline-based antihypertensives, regardless of age, sex, or type of hypertension to lower long-term cardiovascular risk. https://www. gov Identifier: NCT03158051, registered 5-15-2017. IRB approval obtained: IRB # 2017 - 0372.

Learning health system linchpins: information exchange and a common data model.

To demonstrate the potential for a centrally managed health information exchange standardized to a common data model (HIE-CDM) to facilitate semantic data flow needed to support a learning health system (LHS). The Rhode Island Quality Institute operates the Rhode Island (RI) statewide HIE, which aggregates RI health data for more than half of the state's population from 47 data partners. We standardized HIE data to the Observational Medical Outcomes Partnership (OMOP) CDM. Atherosclerotic cardiovascular disease (ASCVD) risk and primary prevention practices were selected to demonstrate LHS semantic data flow from 2013 to 2023. We calculated longitudinal 10-year ASCVD risk on 62,999 individuals. Nearly two-thirds had ASCVD risk factors from more than one data partner. This enabled granular tracking of individual ASCVD risk, primary prevention (ie, statin therapy), and incident disease. The population was on statins for fewer than half of the guideline-recommended days. We also found that individuals receiving care at Federally Qualified Health Centers were more likely to have unfavorable ASCVD risk profiles and more likely to be on statins. CDM transformation reduced data heterogeneity through a unified health record that adheres to defined terminologies per OMOP domain. We demonstrated the potential for an HIE-CDM to enable observational population health research. We also showed how to leverage existing health information technology infrastructure and health data best practices to break down LHS barriers. HIE-CDM facilitates knowledge curation and health system intervention development at the individual, health system, and population levels.

Polygenic Risk Scores and Extreme Coronary Artery Calcium Phenotypes (CAC=0 and CAC≥1000) in Adults ≥75 Years Old: The ARIC Study.

Coronary artery calcium (CAC) is heterogeneous in older age and is incompletely explained by traditional atherosclerotic cardiovascular disease risk factors. The extremes of subclinical atherosclerosis burden are strongly associated with either a low or high 10-year risk of incident atherosclerotic cardiovascular disease, respectively. However, the genetic underpinnings of differences in arterial aging remain unclear. We sought to determine the independent association of 2 polygenic scores for coronary heart disease (CHD) with CAC in adults ≥75 years of age. There were 1865 ARIC (Atherosclerosis Risk in Communities) participants who underwent genetic testing at visit 1 (1987-1989) and CAC scans at visit 7 (2018-2019). In the primary analysis, an externally derived multi-ancestry polygenic CHD risk score was calculated for both White and Black participants. Results were confirmed using a separate ARIC-derived polygenic CHD risk score, including ≥6 million variants computed for White participants. We used multivariable logistic regression models to assess the association of polygenic CHD risk with CAC, after adjusting for baseline, time-averaged lifestyle, traditional risk factors, and local ancestry principal components. In the primary analysis, the average age was 80.6 years old, 61.6% were women, and the median CAC score was 246 (189 participants with CAC=0, 364 participants with CAC≥1000). Compared with persons below the 20th percentile of polygenic CHD risk, persons with polygenic-CHD risk above the 80th percentile had 82% lower odds of having CAC=0 (odds ratio, 0.18 [95% CI, 0.09-0.37]) and had >4-fold higher odds of CAC≥1000 (odds ratio, 4.77 [95% CI, 2.88-7.88]). On a continuous scale, each SD increment increase in the polygenic risk score was associated with a 78% higher CAC score. Results were nearly identical using a second confirmatory polygenic CHD risk score in White participants. Polygenic CHD risk is robustly associated with a lower prevalence of CAC=0 and a higher prevalence of CAC≥1000 in adults ≥75 years of age, beyond lifestyle and traditional risk factors. These results suggest a heritable contribution to distinct healthy and unhealthy arterial aging phenotypes that persist throughout the life course.

Abstract 4136554: Comparison of short- and long-term atherosclerotic cardiovascular disease risk assessment tools in US young adults

Background: In 2023, the AHA published the PREVENT equations for estimating atherosclerotic cardiovascular disease (ASCVD) risk in adults aged 30-79 years. Research Questions: In young adults aged 20-39 years, does PREVENT improve risk prediction for 10- and 30-year ASCVD compared with existing risk assessment tools recommended in the current US guidelines (i.e., Pooled Cohort Equations [PCEs] and Pencina et al. equations)? Aims: To compare the performance of PREVENT vs. PCEs in predicting 10-year ASCVD, and PREVENT vs. Pencina equations in predicting 30-year ASCVD in young adults. Methods: We analyzed data from two complementary sources: (1) pooled data from two large cohorts: Coronary Artery Risk Development in Young Adults (CARDIA) and Framingham Heart Study (FHS; including the Offspring, Third Generation, Omni 1, and Omni 2 cohorts), and (2) electronic health records from Kaiser Permanente Southern California (KPSC). We included adults aged 20-39 years without a history of ASCVD at baseline. The outcome was incident ASCVD (defined as myocardial infarction, fatal coronary heart disease, fatal and nonfatal stroke) at 10 or 30 years. Model discrimination (Harrell’s C) and mean calibration (estimated as the ratio of predicted to observed event rates) were calculated for the overall population and stratified by sex and race/ethnicity. Results: We included 7,606 young adults (mean age 29 years, 53% female, 30% Black) from the pooled cohorts, and 284,667 (mean age 32 years, 61% female, 8% Black, 46% Hispanic) from KPSC. When predicting 10-year risk, PREVENT improved discrimination in both the pooled cohort (ΔHarrell’s C=0.052; 95% CI: 0.014, 0.095) and KPSC (ΔHarrell’s C=0.039; 95% CI: 0.028, 0.049) compared with the PCEs. PREVENT had good calibration (mean calibration ranged from 0.77 to 1.54), whereas the PCEs overestimated 10-year risk (mean calibration ranged from 1.99 to 4.82). When predicting 30-year risk, discrimination was similar for PREVENT and Pencina equations, but both algorithms underestimated 30-year risk with PREVENT showing worse calibration (mean calibration 0.61). Conclusion: PREVENT improved 10-year ASCVD risk prediction in young adults compared to the PCEs but underestimated 30-year risk.

Abstract 4125263: Influence of sexual orientation-related nondiscrimination laws on 30-year CVD risk among sexual minority and heterosexual adults

Introduction: Discriminatory policies are associated with worse mental health and substance use outcomes among sexual minority adults. Despite a higher risk of cardiovascular disease (CVD) than heterosexual adults, there is limited evidence on structural determinants of cardiovascular health among sexual minority adults. Therefore, we examined whether changes in sexual orientation-related nondiscrimination laws were associated with 30-year CVD risk among sexual minority and heterosexual adults. Hypothesis: We hypothesized that changes in sexual orientation-related nondiscrimination laws would be more strongly associated with 30-year CVD risk among sexual minority adults relative to exclusively heterosexual adults. Methods: We used longitudinal data from Waves III (2001-2002), IV (2008-2009), and V (2016-2018) of the National Longitudinal Study of Adolescent to Adult Health. We assessed changes in four state-level sexual orientation-related nondiscrimination laws (i.e., employment discrimination, same-sex marriage, hate crime statutes, and same-sex adoption) between Waves III and IV. Changes in sexual orientation-related nondiscrimination laws were categorized as unchanged (reference), improved, or worsened. We assessed 30-year CVD risk using the Framingham Risk Score at Wave V. We ran sex-stratified linear regression models adjusted for demographic factors to examine whether the association between change in nondiscrimination laws with 30-year CVD risk was moderated by sexual orientation (i.e., exclusively heterosexual, mostly heterosexual, homosexual/bisexual). Results: The sample included 3,827 participants with a mean age of 28.7 (±1.75) years, of whom 83.1% identified as exclusively heterosexual, 51% as female, and 15% as Black. Compared to heterosexual participants of the same sex, an improvement in nondiscrimination laws was associated with lower 30-year CVD risk among mostly heterosexual women (B -4.57, 95% CI = -8.06, -1.08) and homosexual/bisexual men (B -10.91, 95% CI = -19.33, -2.49). In contrast, compared to exclusively heterosexual women, a worsening of nondiscrimination laws was associated with higher 30-year CVD risk among homosexual/bisexual women (B 5.26, 95% CI = 0.30, 10.21). No differences were found between mostly heterosexual and exclusively heterosexual men. Conclusions: Findings suggest that efforts to enhance policies prohibiting sexual orientation-related discrimination may significantly reduce CVD risk among sexual minority adults.

Abstract 4138488: Association Between Guideline-directed Medical Therapy and Reintervention Risk at 2 Years Following Peripheral Vascular Interventions

Introduction: Patients with peripheral artery disease (PAD) undergoing peripheral vascular interventions (PVI) face frequent reinterventions. The association between the use of guideline-directed medical therapy (GDMT) and reintervention risk is unclear, we therefore aimed to study the association between GDMT and 2-year reintervention risk using the largest national vascular registry. Methods: PVI procedures in patients with claudication or chronic limb-threatening ischemia between 2017-2018 were abstracted from the Vascular Quality Initiative (VQI) registry. GDMT was defined as statin, antiplatelet, and ACE/ARB if hypertensive prescribed at discharge. Reintervention was obtained from Medicare claims data. Propensity score of no GDMT vs. GDMT was calculated using 22 preprocedural variables followed by 1:1 matching of patients. The 2-year cumulative incidence of reintervention and subhazard ratios (sHR) for 2-year reintervention risk in no GDMT vs. GDMT were assessed using Aalen-Johansen method and Fine-Gray model, respectively, to account for the competing risk of death. Results: A total of 13,244 patients (6,622 by GDMT group) were included after 1:1 matching (mean age 72.0 ± 9.9, female 38.9%, white 79.4% Black or African American 15.3%) . At 2 years, the cumulative incidence of reintervention was 43.0% (95% CI 41.0%-44.9%) for patients with no GDMT vs. 41.2% (95%CI 39.4-43.0) for the GDMT group (P=0.293). Not receiving GDMT was not associated with 2-year risk of reintervention (sHR: 1.03 95%CI 0.97-1.10; P=0.293). Conclusion: Around 40% of patients undergoing a PVI will have a reintervention at 2 years. The receipt of GDMT at discharge was not associated with a lower reintervention risk at 2 years, as currently assessed. Further granular measures of GDMT should integrate adherence information, as well as information on other lifestyle and cardiovascular risk management to obtain a more complete assessment of a potential association with reintervention risk.

Abstract 4137527: Evaluation of 10-Year Atherosclerotic Cardiovascular Risk Prediction Performance using the PREVENT versus Pooled Cohort Equations in a US Integrated Healthcare System

Background: The American Heart Association published the new PREVENT equations for estimating atherosclerotic cardiovascular disease (ASCVD) risk. Question: Do the PREVENT equations improve risk prediction for 10-year ASCVD compared with the pooled cohort equations (PCEs) in a large diverse population? Aim: To assess ASCVD risk prediction performance of the two PREVENT equations [PREVENT Base, PREVENT Base plus optional predictors including urine albumin-to-creatinine ratio, glycated hemoglobin, and social deprivation index (PREVENT Full)] compared with the PCEs. Methods: We included adults aged 40-75 years without a history of ASCVD or diabetes from Kaiser Permanente Southern California in 2009 and followed them through 2019. Outcome was incident ASCVD defined as myocardial infarction, fatal coronary heart disease, fatal and nonfatal stroke. We compared model discrimination (Harrell’s C), mean calibration (estimated as the ratio of predicted to observed event rates), and calibration curve among the overall population and stratified by sex and race/ethnicity. Results: Of the 559,111 adults (mean age 54, 11% Black, 32% Hispanic), 10,695 developed an ASCVD event during a median follow-up of 10 years. Harrell’s C among the overall population was 0.741 (95% CI 0.736-0.745) for PREVENT Base, 0.743 (0.738-0.748) for PREVENT Full, and 0.741 (0.736-0.746) for the PCEs ( Table ). Compared with the PCEs, both PREVENT equations improved Harrell’s C in men but not in women, and in Black adults but not in other racial/ethnic groups. Both PREVENT equations were well-calibrated (mean calibration ranged 0.83-1.37; calibration slope ranged 0.71-1.28), while the PCEs overestimated 10-year ASCVD risk (mean calibration ranged 1.80-2.20; calibration slope ranged 0.34-0.45) ( Table &amp; Figure ). Conclusion: Compared with the PCEs, both PREVENT Base and Full equations improved calibration in predicting 10-year ASCVD risk, with minimal improvement in discrimination in men and Black adults only.

Abstract 4135754: Prediction of Incident Atrial Fibrillation Using Handheld Single-Lead Electrocardiograms from the VITAL-AF Trial

Background: Deep learning of 12-lead electrocardiograms (ECGs) can estimate future atrial fibrillation (AF) risk. Whether these models can be applied to single-lead ECGs (1L ECGs) from wearable or handheld devices is unknown. Aim: To apply a previously published deep learning model to estimate 2-year incident AF risk using handheld 1L ECGs obtained prospectively in a large AF screening trial. Methods: In the VITAL-AF trial (NCT03515057), over 16,000 primary care patients aged ≥65 years underwent AF screening with handheld 1L ECG. We applied our published deep learning model (ECG-AI) derived using single leads of over 450,000 standard 12-lead ECGs external to the VITAL-AF study (1L ECG-AI). We compared the performance of 1L ECG-AI to the validated CHARGE-AF clinical risk score and calculated net reclassification indices. Results: Among 15,694 individuals enrolled in VITAL-AF and without prevalent AF (age 74±7 years, 9,104 [58%] women), 1L ECG-AI discriminated 2-year incident AF (area under receiver operating characteristic curve [AUROC] 0.666 [95% CI 0.603-0.721]). With addition of age and sex (1L ECG-AI AS), 2-year AF discrimination (0.695 [0.637-0.742]) was comparable to the 11-component CHARGE-AF clinical risk score (0.679 [0.625-0.729]). Two-year AF incidence was markedly higher with 1L ECG-AI AS in the top 5% (8.0% [5.7-10.2]) vs bottom 5% (0.89% [0.23-0.55]). At a threshold of ≥3% estimated 2-year AF risk, AF incidence was progressively higher among patients at high risk according to neither model (1.5% [1.2-1.8]), one model (1L ECG-AI: 3.3% [2.3-4.2]; CHARGE-AF 3.4% [2.2-4.6]), and both models (5.8% [5.0-6.5]), implying that clinical risk and ECG-AI signals are complementary ( Figure ). Compared to screening all individuals at the guideline-based threshold of ≥65 years, 1L ECG-AI AS resulted in favorable net reclassification improvement (0.27 [0.22-0.32]). Conclusion: An ECG-AI algorithm developed using single leads of a 12-lead ECG combined with age and sex can discriminate AF risk using real-world handheld 1L ECGs with comparable performance to the CHARGE-AF score. 1L ECG-AI signals complement clinical risk factors. ECG-AI applied to 1L ECG may increase the reach and efficiency of AF screening.

Abstract 4114461: Low-density lipoprotein cholesterol, prevalence of cardiovascular disease risk factors, and predicted cardiovascular disease risk among young adults: National Health and Nutrition Examination Survey 2015-2020

Introduction: It is unclear if young adults with hyperlipidemia are also more likely to have non-lipid cardiovascular disease (CVD) risk-factors or higher long-term CVD risk. As such, we assessed associations between low-density lipoprotein cholesterol (LDL-C) levels and non-lipid CVD risk factors as well as 10- and 30-year risk of CVD in young adults. Methods: We included a nationally representative sample of adults 20-&lt;40 years from the National Health and Nutrition Examination Survey (January 2015-March 2020). We described sociodemographic characteristics and CVD risk factors by LDL-C level. We used simple logistic regression to determine associations between LDL-C level and each CVD risk factor. We then calculated the median 10- and 30-year CVD risk by LDL-C category for each participant using the PREVENT risk estimating equations. Results: Among 2,133 (weighted estimation: 90.3 million) young adults, 51.0%, 32.6%, 12.5%, and 3.9% had an LDL-C &lt;100 mg/dL, 100-&lt;130 mg/dL, 130-&lt;160 mg/dL, and 160-&lt;190 mg/dL, respectively. Compared to participants with an LDL-C &lt;100mg/dL, those with an LDL-C 100-&lt;130 mg/dL, 130-&lt;160 mg/dL, and 160-189 mg/dL were more likely to have metabolic syndrome, an enlarged waist, hypertension, elevated glucose, diabetes mellitus, high triglycerides, and high hs-CRP (Table). The median 10-year risk of CVD was approximately 1% across all baseline LDL-C levels. Over a 30-year time horizon, the median risk of incident CVD exceeded 5% only in the 130-&lt;160mg/dL and 160-189mg/dL LDL-C categories (6.0% and 7.6%, respectively). LDL-C and the interaction between LDL-C and CVD risk enhancing factors were independently associated with 30-year predicted risk of CVD (p=0.006 and p=0.005, respectively). Discussion: Many young adults with an elevated LDL-C have concomitant high-risk CVD characteristics. The risk/benefit calculous for addressing this modifiable risk factor in these patients should be further explored.

Abstract 4134977: Utility of Coronary Artery Calcium Scoring in Low-Risk Patients: the Multi-Ethnic Study of Atherosclerosis (MESA)

Introduction: Coronary artery calcium (CAC) scoring is a powerful tool for atherosclerotic cardiovascular disease (ASCVD) risk assessment. Guidelines recommend consideration of CAC scoring in intermediate risk patients, but it’s utility in low and borderline risk patients is less clear. Methods: We used data from 2,894 participants from MESA with low (&lt;5%) or borderline (5-&lt;7.5%) 10-year ASCVD risk defined by the pooled cohort equations (PCE). We evaluated the association between CAC score and coronary heart disease (CHD) and ASCVD risk using multivariable adjusted Cox proportional hazard models. We also evaluated if the addition of CAC to the pooled cohort equations (PCE) improved risk prediction using Harrell’s C-index and net reclassification improvement (NRI). Results/Data: Mean age was 54.1 ± 5.8 years with 66.9% women. Among low-risk individuals, the ASCVD event rate was 3.3% with CAC=0, and 7.8% with CAC&gt;0, and 4.7% vs. 11.4% among borderline-risk individuals. Natural-log transformed CAC score was associated with increased ASCVD risk in low-risk (HR 1.35, 95% CI 1.22-1.50) and borderline-risk (HR 1.29, 95% CI 1.15-1.45) individuals. Similar results were seen for CHD with higher HRs ( Table 1 ). The addition of CAC to the PCE improved the C-index (SE) among low/borderline risk individuals from 0.620 (0.023) to 0.671 (0.024). Continuous NRI was also significant with the addition of CAC to the PCE in low/borderline risk (0.422, 95% CI 0.248-0.611). Greater improvement was seen for CHD ( Table 2 ). Conclusions: The presence of CAC in low and borderline risk individuals is associated with increased ASCVD and CHD risk. The addition of CAC scoring to the PCE improved risk prediction in low and borderline risk individuals, suggesting potential clinical utility in this population.

Abstract 4136592: Comparative performance of PREVENT and Pooled Cohort Equations to predict cardiovascular disease in multisite healthcare populations

Introduction: The American Heart Association’s race-agnostic Predicting Risk of cardiovascular EVENTs (PREVENT) framework has emerged to better capture multilevel determinants of health in contemporary population. Whether PREVENT better predicts incident atherosclerotic cardiovascular disease (ASCVD) than the preceding Pooled Cohort Equations (PCE) is unknown in healthcare populations. We evaluated calibration and discrimination of the two equations across three major U.S. healthcare networks. Methods: We retrospectively evaluated electronic health records of 209,879 individuals (Mass General Brigham [MGB]: 118,801; Mount Sinai Healthcare System: 38,834; Penn Medicine: 52,424) aged 40-79 years and without prior ASCVD between 2010-2012. Calibration was assessed using discordance ratio between 10-year observed and predicted risk. Discrimination was evaluated by Harrell’s C-index. Results: Based on PREVENT, the mean [SD] estimated 10-year ASCVD risk ranged from 5.5 [4.7] % in MGB (mean age 56y, 42% female), 6.6 [5.6]% in Mount Sinai (59y, 54% female), and 6.4 [5.2]% in Penn (60y, 55% female). PREVENT substantially underestimated empirical 10-year ASCVD incidence in MGB (16.9%) and Mount Sinai (10.9%), whereas it closely mirrored the observed rate in Penn (5.5%). Both PCE and PREVENT had comparable discrimination C-index [95% CI] across MGB (0.69 [0.69-0.70] vs. 0.69 [0.68-0.69]), Mount Sinai (0.72 [0.71-0.73] vs. 0.70 [0.70-0.71]), and Penn (0.68 [0.67-0.69] vs. 0.67 [0.66-0.68]). Nevertheless, compared to PREVENT, PCE demonstrated better overall calibration in MGB (-70% vs. -42%) and Mount Sinai (-36% vs. +5%), whereas largely overestimated risk in Penn (+3% vs +94%). Calibration varied across demographics with PREVENT consistently underestimating risk in Hispanics, Asians, Black and African Americans across all sites, whereas PCE largely overestimated risk for White or multiracial Penn healthcare patients. Conclusions: The race-agnostic PREVENT model discriminated ASCVD incidence comparably or better than the race-informed PCE across three geographically distinct academic health systems in the Northeast. However, calibration metrics between the two models varied widely across health systems and demographics.

Abstract 4120670: Pericoronary Adipose Tissue Inflammation as a Marker of Increased Coronary Plaque Burden in Patients With Chronic Coronary Artery Disease With Zero Calcium Score

Background: Dysfunctional or excess adiposity plays pivotal role in the development of coronary atherosclerosis. It remains unclear whether pericoroanry adipose tissue (PCAT) inflammation is associated with increased coronary plaque burden in its early stage of atherosclerosis, independent of traditional coronary risks or cardiovascular-kidney metabolic health. Purpose: To investigate the association of PCAT inflammation with coronary plaque burden in patients with newly suspected with chronic coronary artery disease (CAD) and zero calcium score who underwent coronary computed tomography angiography (CCTA). Methods: This retrospective CCTA study consists of 294 chronic CAD patients with zero calcium score (59 years, male 51 %). Chronic CAD was defined as stable condition with presence of increased non-calcified plaque burden on CCTA (Figure 1A-D). PCAT attenuation (PCATA) was assessed by fat attenuation index in the major three coronary arteries (right coronary artery, RCA; left anterior descending artery; LAD, and left circumflex coronary artery, LCX)(Figure 1C and D). Multivariable analysis using linear regression model was performed to determine independent predictors of increased %PV by adjusting for traditional coronary risks, metabolic risks, and chronic kidney disease (CKD). Hisayama Risk Score (HRS) was calculated to estimate 10-year cardiovascular risks. Results: Mean %plaque volume (PV) and PCATA-RCA was 44±4.0％ and -77±8.8 HU. %PV was correlated with age (p&lt;0.05), systolic blood pressure (p&lt;0.05), non-HDL cholesterol (p&lt;0.05), Hisayama risk score (p&lt;0.05, Figure 2), PCATA-RCA (p&lt;0.001, Figure 3), PCATA-LAD (p&lt;0.001), and LCX-PCATA (p&lt;0.001). In a multivariable linear regression model adjusting for age, sex, hypertension, diabetes, dyslipidemia, and current smoking (model 1), PCATA-RCA was independently associated with %PV [beta, 0.17; 95% confidential interval (CI) 0.115-0.217, p &lt; 0.001]. In a model adjusting for age, sex, metabolic syndrome, body mass index ≥23kg/mm 2 , and CKD (model 2), PCATA-RCA (beta, 0.18; 95% CI 0.128-0.232, p&lt;0.001) and high-risk HRS (beta, 3.1; 95% CI 1.35−4.87, p&lt;0.001) were independently associated with %PV. Similarly, independent associations of PCATA in LAD and LCX with %PV was observed. Conclusion: This study demonstrates that PCATA is a robust marker related to increased burden of coronary atherosclerosis even in the early stage of atherosclerosis as defined by zero coronary artery calcium score.

Abstract 4138647: Opportunistic Screening for Cardiovascular Risk Using Chest X-Rays and Deep Learning: Associations with Coronary Artery Disease in the Project Baseline Health Study and Mass General Brigham Biobank

Introduction/Background: We previously demonstrated that an open-source deep learning model (CXR-CVD Risk) can predict 10-year major adverse cardiovascular events (myocardial infarction&amp;stroke), based on a chest radiograph image (CXR). As deep learning models are black boxes, establishing the biological processes the model captures to predict risk may help build understanding and trust in the model. Research Questions/Hypothesis: To test associations between deep-learning derived CXR-CVD Risk and markers of cardiovascular disease including coronary artery calcium (CAC) and stenosis ≥50% on CT, systolic blood pressure (SBP), ankle brachial index (ABI), and prevalent myocardial infarction and stroke. Methods/Approach: We conducted external validation of CXR-CVD-Risk in two cohorts: 1) 2,097 volunteers in the Project Baseline Health Study (PBHS) and 2) 1,644 Mass General Brigham Biobank (MGBB) patients. The CXR-CVD-Risk model estimated 10-year cardiovascular event risk (probability between 0 and 1) from a CXR image. We calculated linear associations with SBP, ABI, and the logarithm of coronary artery calcium and odds ratios for prevalent hypertension, myocardial infarction, stroke, and, in the MGBB, coronary artery stenosis ≥50%. Analyses were adjusted for age, BMI, sex, smoking status, and enrolling site. Results/Data: CXR-CVD-Risk was associated with CAC in both populations (PBHS: 1.11-fold increase, 95% CI: [1.07-1.16]; MGBB: 1.03-fold increase [1.01-1.05] in CAC per 1% increase in CXR-CV-Risk). CXR-CVD-Risk was also associated with SBP (0.59 mmHg increase [0.24-0.93] in SBP per 1% increase in CXR-CV-Risk), history of hypertension, history of myocardial infarction, and stroke. There was an inverse association with ABI (0.010 decrease [0.005-0.014] in ABI) in the PBHS. In the MGBB, CXR-CVD-Risk was associated with coronary artery stenosis ≥50% (OR = 1.004 [1.002-1.007]). All estimates are after covariate adjustment. Conclusion: This deep learning CXR risk score was associated with coronary artery disease (calcium score and stenosis ≥50%), CVD risk factors, and prevalent CVD. Opportunistic screening using CXRs in the electronic record can identify patients at high risk of CVD who may benefit from prevention.

Abstract 4132341: Systematic Examination of the AHA PREVENT Equations

Background: The novel AHA Predicting Risk of CVD Events (PREVENT) equations newly incorporate predictors (estimated glomerular filtration rate [eGFR]) and outcomes (heart failure [HF]) relevant to the novel construct of cardiovascular-kidney-metabolic (CKM) syndrome. Aims: We sought to characterize the intrinsic properties of the PREVENT equations by simulating different risk profiles across the age and CKM risk spectrum. Methods: We applied the PREVENT base equations to estimate 10-year predicted risk for total CVD, which includes atherosclerotic CVD and HF. First, we calculated risk estimates for a hypothetical individual varying age from 30-79 years with an average risk factor profile (mean population risk factor levels based on National Health and Nutrition Examination Survey 2011-2020 data without diabetes, not on anti-hypertensive or statin medication, and who does not smoke). Second, we examined at which age a hypothetical individual would exceed the previously defined intermediate risk threshold ≥7.5% established by national guidelines. Lastly, we examined the differences in predicted risk with or without diabetes and/or Stage 3 CKD (defined as eGFR 44.5 mL/min/1.73m 2 ). Results: For hypothetical individuals aged 30-79 years with average risk factor levels, predicted 10-year CVD risk is shown in the figure for females (Panel A) and males (Panel B). The predicted risk would exceed the intermediate risk threshold at age 68 years if female and 63 years if male. If the individual had Stage 3 CKD, the predicted risk would exceed the intermediate risk threshold at 60 if female and 55 years if male. If the individual had diabetes, the predicted risk would exceed the intermediate risk threshold at 59 if female and 52 years if male. If both diabetes and Stage 3 CKD were present, the predicted risk would exceed the intermediate risk threshold at age 42 years if female and 35 years if male. Conclusions: The PREVENT equations enable more granular differentiation of risk among individuals with varying CKM profiles. Understanding risk estimates across the spectrum of age and CKM can support interpretability among clinicians and patients.

Abstract 4119941: Identification of individuals who benefit from omega-3 fatty acid supplementation to prevent coronary heart disease: A machine-learning analysis of the VITAL

Backgrounds: Randomized controlled trials (RCTs) have demonstrated benefits of marine omega-3 polyunsaturated fatty acids (omega-3 FA) supplementation for the prevention of coronary heart disease (CHD). However, it has not been clear which individuals would benefit the most from the supplementation. We sought to predict the individual treatment effect of omega-3 FA supplementation on CHD prevention and to develop an omega-3 effect score to stratify individuals according to their expected benefit from the supplementation. Methods: Among the 25,871 randomized participants without history of CVD in the VITamin D and OmegA-3 TriaL (VITAL), we applied machine-learning (ML) approaches to predict individual treatment effect of omega-3 FA supplementation on 5-year CHD risk (a composite of myocardial infarction, coronary revascularization, and CHD death) using 11 covariates pre-specified in the VITAL trial protocol. A 10-fold cross-validation was used and held-out test dataset was used for the evaluation. An omega-3 effect score was developed such that each covariate contributed linearly, and utility of the score was further evaluated by transportability analysis using the National Health and Nutrition Examination Survey (NHANES) data as the target population. Results: Omega-3 FA intervention led to absolute 0.48% [SE: 0.20] reduction in CHD in the total population. ML algorithms effectively stratified participants by their expected benefit according to individual factors; decreased CHD risk was observed in those with quintile 1 and 2 of the expected benefit (absolute CHD risk reduction %: 1.30 % [0.55] and 1.32 % [0.51] in quintile 1 and 2, respectively). Race, diabetes, and fish intake most contributed to the omega-3 effect score. CHD incidence rates per 1000 person-year were 5.5 [0.44] if treated and 8.5 [0.55] if not treated (35.3% reduction) in individuals with the score ≥11 (upper 40th percentile), and 3.9% [0.31] if treated and 3.4% [0.55] if not treated (14.7% increase) in those with the score &lt;11, respectively. The transportability of the utility of the score to baseline NHANES data was confirmed. Conclusion: In VITAL, ML approaches identified individuals who experienced greater CHD reduction from the omega-3 FA intervention, and an omega-3 effect score stratified the expected benefit. Although it warrants testing in a new RCT, the omega-3 effect score holds promise for guiding the indication of omega-3 FA supplementation in US primary prevention population.

Abstract 4129533: Phenotypes and clinical outcome of heart failure with preserved ejection fraction (HFpEF) patients in China: Findings from the Chinese Cardiovascular Association Database-Heart Failure Center Registry

Background: Heart failure with preserved ejection fraction (HFpEF) is a heterogenous syndrome with 5 phenotypes. We aimed to evaluate the clinical outcome of HFpEF patients with various phenotypes in China. Methods and Results: Data from the Chinese Cardiovascular Association (CCA) Database-HF Center Registry between January 2017 and December 2021 were analyzed, 51,466 hospitalized HFpEF patients with 1-year follow-up results were included in this analysis. The patients were categorized into five phenotypes based on published phenotyping method. Clinical characteristics and 1-year outcome and related risk factors of HFpEF patients with various phenotypes were explored. Results demonstrated significant differences in baseline characteristics and clinical outcomes among the phenotypes, patients with phenotype-3 (right heart and pulmonary-related HFpEF), phenotype-4 (valvular- and rhythm-related HFpEF) and phenotype-5 (extracardiac disease-related HFpEF) exhibited high incidence of adverse outcomes. Phenotype-3 and -4 exhibited high risk of heart failure rehospitalization, whereas phenotype-5 showed high cardiovascular mortality. The independent prognostic risk factors varied across different phenotypes as well. Conclusion: One-year outcome differs among HFpEF patients with various phenotyping. Future studies are warranted to validate if personalized treatment strategies based on HFpEF phenotypes could improve the individual outcome of HFpEF patients, especially for phenotype-3, -4 and -5 HFpEF patients. Keywords: Heart failure with preserved ejection fraction, phenotype, prognosis, population study, risk factors.

Sex differences in survival following acute coronary syndrome with and without standard modifiable risk factors.

This meta-analysis investigates the sex differences in mortality risk between the acute coronary syndrome (ACS) population without standard modifiable risk factors (SMuRF-less) and those with at least one standard modifiable risk factor (SMuRF), and analyses mortality rates between males and females within the SMuRF-less cohort. The MEDLINE and Embase databases were searched for cohort studies with sex-stratified outcomes for SMuRF-less versus SMuRF patients with ACS till 15 December 2023. The analysis of variables reported in proportions was carried out by utilizing a meta-analysis with a generalized linear mixed model while continuous variables were analyzed by a meta-analysis of means, using an inverse variance method. Eight studies were included in the current paper, with 82,395 SMuRF-less ACS patients and 607,558 SMuRF ACS patients. Excess in-hospital mortality found in SMuRF-less ACS, compared to those with SMuRFs, were only observed in females (RR 1.56, 95%CI 1.08-2.25, p = 0.029), but not in males (RR 1.59, 95%CI 0.90-2.80, p = 0.088). On longer follow-up, the 1- and 2-year post-ACS mortality rates were similar across the SMuRF-less and SMuRF cohorts, for both sexes. The subgroup analysis of SMuRF-less ACS individuals revealed that SMuRF-less females had higher in-hospital (RR 1.52, 95%CI 1.30-1.78, p = 0.002), 1-year (RR 1.51, 95%CI 1.34-1.71, p = 0.005) and 2-year mortality risks (RR 1.40, 95%CI 1.13-1.75, p = 0.016) compared to the SMuRF-less male counterparts. Paradoxical excess mortality in SMuRF-less ACS, compared to those with SMuRFs, was only observed in females. Females without cardiovascular risk factors are at the highest risk of short- and medium-term mortality following ACS.

Abstract 4140142: Neighborhood Perceptions Associate with Lipid Biomarkers in African-American Women with Cardiovascular-Kidney-Metabolic Syndrome: Data from the Step It Up Digital Health-Enabled, Community-Engaged Physical Activity Intervention

Background: Cardiovascular-kidney metabolic (CKM) syndrome is exacerbated among individuals experiencing chronic exposure to both environmental and psychosocial stressors. Both neighborhood and individual-level stressors increase chronic inflammation resulting in worsened CKM factors, such as hypertension, diabetes, and dys/hyperlipidemia. However, associations between neighborhood perceptions (NP) and lipid profiles remain understudied. Therefore, we examined associations between NP domains and lipid profiles among African-American (AA) women with ≥Stage 1 CKM syndrome (overweight/obesity) residing in resource-limited neighborhoods within the Washington, DC area. Methods: Participants were enrolled in Step It Up, a technology-enabled, community-engaged physical activity (PA) intervention. Fasting blood samples were drawn at baseline to measure lipoproteins using Nuclear Magnetic Resonance (NMR) spectroscopy. Factor analysis of overall NP identified four perception sub-scores: disorder, social cohesion, violence, and safety (higher score=favorable perception). Associations between NP domains and lipoprotein particles were analyzed using multivariable regression adjusting for BMI, ASCVD 10-year risk score, and lipid-lowering therapy. Results: Participants (n=169) had mean age=57.16 ± 12.00 and BMI 35.99 ± 6.57. Perceptions of safety were positively associated with LDL concentrations (LDLc) and large LDL particles (L-LDLp) (β=4.70 [SD=2.41], p=0.05, β= 43.75 [17.70], p= 0.01), respectively). Perceptions about neighborhood violence were positively associated with L-LDLp (marginally) and very-low-density lipoprotein size (VLDLz) (β= 7.10 [3.96], p=0.08, β= 0.31 [0.14], p= 0.02, respectively). No associations were found between disorder and social cohesion with lipid biomarkers. Conclusions: After adjusting for BMI, ASCVD risk, and lipid-lowering therapy, there were significant associations between neighborhood perceptions of safety and violence with lipid profiles among AA women with CKM syndrome. Greater perceived safety was associated with higher LDLc and L-LDLp while more favorable perception about neighborhood violence was associated with higher L-LDLp. Future work should examine whether improving neighborhood resources and perceptions may improve CKM health among urban AA women.