Risk Estimates Research Articles

Health-Related Behaviors and Risk of Common Age-Related Brain Diseases Across Severities of Genetic Risk.

The 21-point Brain Care Score (BCS) is an index that ranks behaviors and clinical measurements with the aim of encouraging lifestyle adjustments to lower the incidence of age-related brain disease, including stroke, late-life depression (LLD), and dementia. A higher BCS at baseline is associated with a lower risk of these outcomes. We aimed to investigate whether the associations between BCS and stroke, LLD, and dementia risks are independent of genetic predisposition for these conditions and quantify the effect of healthy lifestyle across genetic risk distributions for these outcomes. Using the UK Biobank (UKB) prospective cohort study, we computed baseline BCSs and polygenic scores to estimate genetic predisposition for stroke and LLD and APOE ε allele status to stratify dementia risk. As for outcomes again in UKB, we measured incidence of stroke, LLD, and dementia. We used multivariate Cox proportional hazard models to assess associations between BCS, genetic predisposition, and these outcomes. We also conducted stratified and interaction analyses to estimate the incidence of these outcomes across quartiles of genetic risk and BCS. We included 368,340 UKB participants (median age 58 years (interquartile range 51-63 years), 46.3% male). Independent of genetic risk, a 5-point increase in BCS corresponded to lowered hazards of stroke (hazard ratio [HR] 0.70, 95% CI 0.68-0.73), LLD (HR 0.65, 95% CI 0.63-0.67), and dementia (HR 0.82, 95% CI 0.78-0.85). Incidences of all 3 outcomes were higher among participants with high genetic risk of these outcomes. However, these increased risks were offset for individuals with a higher BCS (incidence rates per 1,000 person-years were 2.76 vs 1.19 for stroke, 7.34 vs 4.46 for LLD, and 3.64 vs 2.05 for dementia, when comparing low and high BCS). Across different genetic predispositions for stroke, LLD, and dementia, healthier lifestyle behaviors are protective for brain health, demonstrating the nondeterminism of genetic risk. Furthermore, differences in BCS behave as aggregate risk estimators of all 3 outcomes. Further work is needed to prospectively investigate the utility and performance of the BCS as a targeted intervention in populations at elevated genetic risk of age-related brain disease.

Risk minimizing framework for solar photovoltaics

The complexity of risk assessment and the challenges in decision-making often impede the application of various models to renewable energy systems. This study introduces a comprehensive framework designed to streamline this process, facilitating informed decisions regarding the estimation of risks associated with solar photovoltaic (PV) technologies. Leveraging data and information available in the literature, the framework is particularly useful for manufacturers in selecting materials that balance low environmental risk with high efficiency. The framework emphasizes early-stage risk minimization by integrating changes during PV development, thereby promoting cleaner production systems. It’s interconnected components encompass various approaches to risk assessment, control, and management, providing a structured methodology for risk reduction. Based on available information, the defined steps guide users through evaluating and mitigating risks. Applying risk minimization by metal substitution approach lowers the oral-ingestion and dermal-contact risk by a magnitude of four and six times, respectively. This framework will guide regulatory bodies throughout each step of the product life cycle, suggesting necessary changes and assessment strategies aligned with the perspectives of various stakeholders. By facilitating the identification and implementation of the most effective risk management strategies, the framework aims to advance the development of sustainable and safe PV technologies.

Evaluating Performance and Agreement of Coronary Heart Disease Polygenic Risk Scores.

Polygenic risk scores (PRSs) for coronary heart disease (CHD) are a growing clinical and commercial reality. Whether existing scores provide similar individual-level assessments of disease susceptibility remains incompletely characterized. To characterize the individual-level agreement of CHD PRSs that perform similarly at the population level. Cross-sectional study of participants from diverse backgrounds enrolled in the All of Us Research Program (AOU), Penn Medicine BioBank (PMBB), and University of California, Los Angeles (UCLA) ATLAS Precision Health Biobank with electronic health record and genotyping data. Polygenic risk for CHD from published PRSs and new PRSs developed separately from testing samples. PRSs that performed population-level prediction similarly were identified by comparing calibration and discrimination of models of prevalent CHD. Individual-level agreement was tested with intraclass correlation coefficient (ICC) and Light κ. A total of 48 PRSs were calculated for 171 095 AOU participants. The mean (SD) age was 56.4 (16.8) years. A total of 104 947 participants (61.3%) were female. A total of 35 590 participants (20.8%) were most genetically similar to an African reference population, 29 801 (17.4%) to an admixed American reference population, 100 493 (58.7%) to a European reference population, and the remaining to Central/South Asian, East Asian, and Middle Eastern reference populations. There were 17 589 participants (10.3%) with and 153 506 participants without (89.7%) CHD. When included in a model of prevalent CHD, 46 scores had practically equivalent Brier scores and area under the receiver operator curves (region of practical equivalence ±0.02). Twenty percent of participants had at least 1 score in both the top and bottom 5% of risk. Continuous agreement of individual predictions was poor (ICC, 0.373 [95% CI, 0.372-0.375]). Light κ, used to evaluate consistency of risk assignment, did not exceed 0.56. Analysis among 41 193 PMBB and 53 092 ATLAS participants yielded different sets of equivalent scores, which also lacked individual-level agreement. CHD PRSs that performed similarly at the population level demonstrated highly variable individual-level estimates of risk. Recognizing that CHD PRSs may generate incongruent individual-level risk estimates, effective clinical implementation will require refined statistical methods to quantify uncertainty and new strategies to communicate this uncertainty to patients and clinicians.

Should South Asian Stock Market Investors Think Globally? Investigating Safe Haven Properties and Hedging Effectiveness

In this study, we examine the critical question of whether global equity and bond assets (both green and non-green) offer effective hedging and safe haven properties against stock market risks in South Asia, with a focus on Bangladesh, India, Pakistan, and Sri Lanka. The increasing integration of global financial markets and the volatility experienced during recent economic crises raise important questions regarding the resilience of South Asian markets and the potential protective role of global assets. Drawing on methods like VaR and CVaR tail risk estimators, the DCC-GJR-GARCH time-varying connectedness approach, and cost-effectiveness tools for hedging, we analyze data spanning from 2014 to 2022 to assess these relationships comprehensively. Our findings demonstrate that stock markets in Bangladesh experience lower levels of downside risk in each quantile; however, safe haven properties from the global financial markets are effective for Bangladeshi, Indian, and Pakistani stock markets during the crisis period. Meanwhile, the Sri Lankan stock market neither receives hedging usefulness nor safe haven benefits from the same marketplaces. Additionally, global green assets, specifically green bond assets, are more reliable sources to ensure the safest investment for South Asian investors. Finally, the portfolio implications suggest that while traditional global equity assets offer ideal portfolio weights for South Asian investors, global equity and bond assets (both green and non-green) are the cheapest hedgers for equity investors, particularly in the Bangladeshi, Pakistani, and Sri Lankan stock markets. Moreover, these results hold significant implications for investors seeking to optimize portfolios and manage risk, as well as for policymakers aiming to strengthen regional market resilience. By clarifying the protective capacities of global assets, particularly green ones, our study contributes to a nuanced understanding of portfolio diversification and financial stability strategies within emerging markets in South Asia.

Changes in the prognosis of CADASIL over time: a 23-year study in 555 individuals

BackgroundCerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most common monogenic form of stroke and is associated with early-onset stroke and dementia. Whether its clinical phenotype...

The Risk of Venous Thromboembolism in Children With Inflammatory Bowel Disease.

Recent studies of children with inflammatory bowel disease (IBD) demonstrate an increased venous thromboembolism (VTE) risk. However, estimates of risk are variable and case numbers are limited. The aim of this study was to provide national estimates of the risk of VTE in children with IBD. Hospital Episode Statistics was used to identify patients diagnosed with either IBD or VTE before reaching 18 years of age between 2001 and 2019. Populations and subgroups are described, and the risks of developing VTE in the general and IBD populations were calculated. Children with VTE following a diagnosis of IBD or in the previous 6 months (n = 85) and with VTE without IBD (n = 4160) were studied. The absolute risk in children with IBD was 9.42 (95% confidence interval [CI], 7.4-11.4) per 10 000 patient-years, compared with 0.18 (95% CI, 18-0.19) in children without IBD. Between 6 months prior to and 1 year following IBD diagnosis was the highest absolute risk period for VTE (18.0; 95% CI, 13.7-22.4). The relative risk of VTE in children with IBD vs children without IBD was greatest in younger patient groups: the relative risk for the age band 0 to 8 years was 96.5 (95% CI, 51.8-179.9) and for 9 to 11 years was 153.1 (95% CI, 81.2-288.8) vs 14.3 (95% CI, 10.3-20.0) for 15 to 17 years. Cerebral venous sinus thrombosis represented 17.6% of pediatric VTE events in IBD patients compared with 4.2% in children without IBD (P = .001). This study confirms the increased risk of VTE in children with IBD compared with children without IBD. The time of greatest VTE risk was around diagnosis. Cerebral venous sinus thrombosis was significantly more common in children with IBD than other children.

Incidence of and risk of mortality after hip fractures in Rheumatoid Arthritis relative to the general population.

Osteoporosis, a known complication of rheumatoid arthritis (RA), increases the risk of hip fracture, which is associated with high morbidity and mortality. Fracture risk estimates in RA patients treated with contemporary treatment strategies are lacking. The objectives were 1) to estimate age- and sex-specific incidence rates and compare the risk of hip fractures in RA relative to age and sex-matched general population controls, and 2) to compare the risk of all-cause mortality in RA and general population controls after hip fracture. A longitudinal study of a population-based incident cohort of RA patients diagnosed between 1997 and 2009, followed until 2014, with age- and sex-matched controls from the general population of British Columbia, using administrative health data. Hip fracture outcomes (ICD9-CM codes 820.0 or 820.2; ICD10-CA code S72.0 to S72.2) and mortality at pre-defined intervals after fracture (in-hospital, 90 days, 1-year, 5-year) were identified. Hip fracture incidence rates for RA and controls, and incidence rate ratios (IRR) were calculated. Cox proportional hazards models compared hip fracture and mortality risk in RA vs. controls; logistic regression compared in-hospital mortality risk. Overall, 1314 hip fractures over 360,521 person-years were identified in 37,616 RA individuals and 2083 over 732,249 person-years in 75,213 controls, yielding a 28% greater fracture risk in RA (IRR 1.28 [95%CI, 1.20;1.37]). Mean age at time of fracture was slightly younger for RA than controls (79.6 + 10.8 vs. 81.6 + 9.3 yrs). Post-fracture mortality risk at 1- and 5-years did not differ between RA and general population controls. Results were similar in a sensitivity analysis including only RA individuals who received disease-modifying antirheumatic drugs (DMARDs). People with RA had a greater risk of hip fractures, but no greater risk of mortality post fracture, than the general population. The relative risk of hip fractures observed was not as high as previously reported, likely reflecting better treatment of inflammation and management of osteoporosis and its risk factors.

The prognostic value of cartilage intermediate layer protein 1 (CILP1) in patients with diabetic cardiomyopathy.

To measure the plasma levels of human cartilage intermediate layer protein 1 (CILP1) in patients with diabetic cardiomyopathy (DCM), and to investigate its association with the occurrence of major adverse cardiovascular events (MACE) in DCM. A total of 336 diabetic patients were enrolled and assigned into two groups based on the presence or absence of DCM (DCM group and N-DCM group). The baseline clinical data including glutamic-pyruvic transaminase (ALT), glutamic oxaloacetic acid transferase (AST), albumin, serum creatinine, glycosylated hemoglobin (HbA1c), C-reactive protein (CRP), and N-terminal pro brain natriuretic peptide (NT-proBNP) were recorded. Subsequently, plasma levels of CILP1 at admission were detected by the enzyme linked immunosorbent assay (ELISA) method. Echocardiographic parameters were also acquired for all patients. The association of CILP1 with LVEF, LVDD and CRP was determined. In addition, the occurrence of MACE was examined during the 12-month follow-up in the DCM group. The concentration of CILP1 in the DCM group was higher than in the N-DCM group [1329.97 (1157.14, 1494.36) ng/L vs. 789.00 (665.75, 937.06) ng/L, P < 0.05], higher in the MACE group than in the non-MACE group [1777.23 (1532.83, 2341.26)ng/L vs. 885.00 (722.40, 1224.91) ng/L, P < 0.05). Correlation analysis revealed that CILP1 expression was associated with LVEF, CRP and LVDD (r = -0.58, 0.29 and 0.44, respectively, P < 0.05). Analysis of a nomogram demonstrated that CILP1, sex, age, BMI, LVEF and LVDD could predict the occurrence of MACE in DCM patients at 12months (P < 0.05). The plasma levels of CILP1 were independently associated with a stronger discriminating power for DCM. Furthermore, inclusion of CILP1 as a covariate in the model caused a significant improvement in risk estimation compared with traditional risk factors for DCM [BASIC: AUC: 0.556, 95%CI: 0.501-0.610; BASIC + CILP1: AUC: 0.913, 95%CI: 0.877-0.941, P < 0.05] and MACE [BASIC: AUC: 0.710, 95%CI: 0.616-0.792; BASIC + CILP1: AUC: 0.871, 95%CI: 0.794-0.928, P < 0.05]. The serum concentration of CILP1 was increased in DCM patients. Elevated fasting plasma CILP1 levels was a robust diagnostic marker of DCM and was independently associated with an increased risk of MACE.

Body mass index and breast cancer risk in premenopausal and postmenopausal East Asian women: a pooled analysis of 13 cohort studies.

It has been suggested that the association between body mass index and breast cancer risk differs between Asian women and Western women. We aimed to assess the associations between body mass index and breast cancer incidence in East Asian women. Pooled analyses were performed using individual participant data of 319,189 women from 13 cohort studies in Japan, Korea, and China. Participants' height and weight were obtained by measurement or self-reports at cohort baseline. Breast cancer was defined as code C50.0-C50.9 according to the International Classification. Using a Cox proportional hazards model, hazard ratios of breast cancer were estimated for each body mass index category, with the reference group set as the group with a body mass index of 21 to < 23 kg/m2. The hazard ratio for a 5kg/m2 increase in body mass index was also calculated. During a mean 16.6 years of follow-up, 4819 women developed breast cancer. Similar to Westerners, a steady increase in breast cancer risk with increasing body mass index was observed in postmenopausal women, but the slope of the risk increase appeared to slow at a body mass index of 26-28 kg/m2. In premenopausal women, the inverse association seen in Westerners was not observed. The risk of developing breast cancer after 50 years of age increased slightly with increasing body mass index, which was more pronounced in the older birth cohort. There was no significant association between body mass index and the risk of developing breast cancer before 50 years of age, but the risk estimates changed from positive to negative as the birth cohort got younger. In East Asia, the role of body mass index in breast cancer in premenopausal women may be changing along with the increase in obesity and breast cancer. The increased risk of postmenopausal breast cancer with a higher body mass index was as robust as that of Western women.

Enhancing risk stratification models in localized prostate cancer by novel validated tissue biomarkers.

Localized prostate cancer (PCa) is a largely heterogeneous disease regarding its clinical behavior. Current risk stratification relies on clinicopathological parameters and distinguishing between indolent and aggressive cases remains challenging. To improve risk stratification, we aimed to identify new prognostic markers for PCa. We performed an in silico analysis on publicly available PCa transcriptome datasets. The top 20 prognostic genes were assessed in PCa tissue samples of our institutional cohort (n = 92) using the NanoString nCounter technology. The three most promising candidates were further assessed by immunohistochemistry (IHC) in an institutional (n = 121) and an independent validation cohort from the EMPACT consortium (n = 199). Cancer-specific survival (CSS) and progression-free survival (PFS) were used as endpoints. Our in silico analysis identified 113 prognostic genes. The prognostic values of seven of the top 20 genes were confirmed in our institutional radical prostatectomy (RPE) cohort. Low CENPO, P2RX5, ABCC5 as well as high ASF1B, NCAPH, UBE2C, and ZWINT gene expressions were associated with shorter CSS. IHC analysis confirmed the significant associations between NCAPH and UBE2C staining and worse CSS. In the external validation cohort, higher NCAPH and ZWINT protein expressions were associated with shorter PFS. The combination of the newly identified tissue protein markers improved standard risk stratification models, such as D'Amico, CAPRA, and Cambridge prognostic groups. We identified and validated high tissue levels of NCAPH, UBE2C, and ZWINT as novel prognostic risk factors in clinically localized PCa patients. The use of these markers can improve routinely used risk estimation models.

An Electronic Medical Record-Based Prognostic Model for Inpatient Falls: Development and Internal-External Cross-Validation.

Effective fall prevention interventions in hospitals require appropriate allocation of resources early in admission. To address this, fall risk prediction tools and models have been developed with the aim to provide fall prevention strategies to patients at high risk. However, fall risk assessment tools have typically been inaccurate for prediction, ineffective in prevention, and time-consuming to complete. Accurate, dynamic, individualized estimates of fall risk for admitted patients using routinely recorded data may assist in prioritizing fall prevention efforts. The objective of this study was to develop and validate an accurate and dynamic prognostic model for inpatient falls among a cohort of patients using routinely recorded electronic medical record data. We used routinely recorded data from 5 Australian hospitals to develop and internally-externally validate a prediction model for inpatient falls using a Cox proportional hazards model with time-varying covariates. The study cohort included patients admitted during 2018-2021 to any ward, with no age restriction. Predictors used in the model included admission-related administrative data, length of stay, and number of previous falls during the admission (updated every 12 hours up to 14 days after admission). Model calibration was assessed using Poisson regression and discrimination using the area under the time-dependent receiver operating characteristic curve. There were 1,107,556 inpatient admissions, 6004 falls, and 5341 unique fallers. The area under the time-dependent receiver operating characteristic curve was 0.899 (95% CI 0.88-0.91) at 24 hours after admission and declined throughout admission (eg, 0.765, 95% CI 0.75-0.78 on the seventh day after admission). Site-dependent overestimation and underestimation of risk was observed on the calibration plots. Using a large dataset from multiple hospitals and robust methods to model development and validation, we developed a prognostic model for inpatient falls. It had high discrimination, suggesting the model has the potential for operationalization in clinical decision support for prioritizing inpatients for fall prevention. Performance was site dependent, and model recalibration may lead to improved performance.

Society of Surgical Oncology Breast Disease Site Working Group Statement on Bilateral Risk-Reducing Mastectomy: Indications, Outcomes, and Risks.

Bilateral risk-reducing mastectomy (BRRM) is the surgical removal of both breasts to reduce the risk of cancer. In this Society of Surgical Oncology position statement, we review the literature addressing the indications, outcomes, and risks of BRRM to update the society's 2017 statement. We held a virtual meeting to outline key topics and conducted a literature search using PubMed to identify relevant articles. After literature review, recommendations were made according to group consensus. Individuals with a high lifetime risk of breast cancer due to pathogenic variants in high penetrance breast cancer-predisposition genes, early chest or breast radiation exposure, or a compelling family history should be counseled on the option of BRRM. However, BRRM is not recommended for most patients with high-risk lesions and may be contraindicated in patients who have other competing cancers and/or a high risk of surgical complications. BRRM effectively reduces the risk of breast cancer development, although the survival benefit is unclear. For patients with low-to-moderate breast cancer risk, alternative management strategies should be encouraged, including lifestyle modifications, high-risk screening, and risk-reducing medications. Discussions of BRRM should cover: (1) breast-cancer risk estimates; (2) the procedure's degree of risk reduction and impact on survival; (3) surgical techniques, potential surgical complications and long-term sequelae; and (4) alternatives to surgery. Surgeons should encourage shared and informed decision making with patients who have an elevated lifetime risk of developing breast cancer.

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 4119052: Redefining the phenotypic continuum of cardiovascular disease using machine learning

Background: Current approaches that define cardiovascular disease rely on assignment of traditional diagnostic labels which may not reflect the natural continuum of phenotypic expression, influenced by genetic and environmental modifiers, or adequately identify groups with shared molecular mechanisms. Machine learning can leverage advances in genetic and imaging characterisation to reclassify phenotypic diversity along a continuum, from health to disease. Research Aims: Our study aims to build a tree-like classification of cardiovascular phenotypes in the community where branches represent subjects with shared features, ordered by their severity. Using dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) as exemplar conditions with opposing phenotypes, we aim to demonstrate the interaction between genetic and environmental modifiers of disease expression. Methods: We analysed cardiovascular magnetic resonance (CMR) imaging, electrocardiogram (ECG), biomarkers and clinical data from participants in the UK Biobank. Using unsupervised learning of multiparametric data, we built a tree of phenotypic expression. We projected the risk of DCM and HCM cases, and associated rare and common variant risk, onto the tree structure. Results: Ten main branches were discovered, using data from 41,525 participants (51.7 % female, median age 65 yrs [IQR: 58, 70]). The extremities of branches 1 and 6 were enriched for DCM cases (p &lt;0.05) and participants with reduced ejection fraction and high left ventricular volumes (p &lt;0.05). Compared with subjects at the tree centre, distal participants in branch 1 had increased blood pressure (BP) and body mass index (BMI), whilst those in branch 6 were more likely to have high HbA1c levels and carry a pathogenic DCM variant (p &lt;0.05). The extremity of branch 5 was enriched for HCM cases, rare sarcomeric variants (p = 0.004) and high polygenic risk (p &lt;0.001). Whilst the ends of branches 3 and 9 had high polygenic risk for HCM, they were less likely to have elevated BP and BMI, and had reduced likelihood of HCM expression, compared with branch 5. A phenomapping model was trained to accurately project unseen subjects onto the tree (R 2 0.98). Conclusions: We present a tree-like continuum of cardiovascular phenotypes, providing a novel framework for mechanistic discovery and exploration of genotype-phenotype associations. Phenomapping of unseen subjects enables personalised estimation of genetic and cardiovascular risk.

Abstract 4137770: Development of a User-Friendly Self-Screening Tool for Assessing Metabolic Syndrome Risk in young adults from economically challenged regions

Background: Metabolic syndrome is a cluster of conditions that increase the risk of heart disease and diabetes. Early identification and management are crucial, particularly in economically challenged regions where access to healthcare may be limited. Research Questions/Hypothesis: User-friendly self-report data accurately predict metabolic outcomes. Aims: To develop and validate nomograms for individualized estimation of metabolic syndrome risk. Methods: Data from 521 college students (60.1% aged 17-20 years; 68.7% female; 28.0% white) were collected in 2022/2023 from two Brazilian cities. These cities are located in the country's poorest states, with Gini indices of 0.56 and 0.43. The potential predictors include demographic and economic variables, school-related factors, behaviors, and body weight. Based on predictors for abdominal obesity identified through multilevel logistic regression, we created a nomogram model. We performed the Hosmer-Lemeshow test to assess model calibration and used a bootstrapping approach (B = 150) for internal validation. To evaluate external validity, we assessed metabolic syndrome in a subset of 375 students. The area under the receiver operating characteristic curve (AUROC), with a threshold of 0.70, was used to evaluate the model's discrimination accuracy. Results: We identified 114 (23.0%) college students who were abdominally obese. We found ten variables associated with the primary outcome: age, biological sex, physical education facilities, enrollment in sports competition (during elementary school); grade retention, preferred subject, physical education classes per week; enrollment in sports training (during secondary school); adherence of 24-hour movement behaviors and body weight. The proposed nomogram showed acceptable performance in the AUROC (0.94 [95% CI: 0.92-0.96). The calibration assessment indicated reasonable consistency of our model (p &gt; 0.05). In the internal validation, we observed a decreased predictive capability (AUROC = 0.86). Conclusion: The 24h-MESYN risk score offers an effective self-screening tool for college students from diverse racial and ethnic backgrounds in economically challenged regions to assess their risk of developing metabolic syndrome.

Abstract 4137927: Physicians’ Misrecognition of Stroke Risk in Patients with Atrial Fibrillation

Background: Current clinical practice guidelines for atrial fibrillation (AF) recommend stroke risk stratification and the use of oral anticoagulants (OACs) for patients at risk. However, physicians’ recognition of patients’ stroke risk may differ from the calculated risk, and the effect of this discrepancy on subsequent care remains unknown. Aims: We aimed to document treating physicians’ estimations of individual patients' stroke risk and assess its association with OAC utilization. Methods: A multicenter, prospective cohort study was conducted in two outpatient practices in Tokyo, Japan, between 2018 to 2020. Participants included patients with newly diagnosed AF or those referred for initial treatment for AF. Treating physicians were asked to document the patient's estimated risk of stroke in numbers. The estimations were categorized as low risk (&lt;1.0%/year), intermediate risk (1.0%≤ to &lt;2.0%/ year), and high risk (2.0%≤/year). We then calculated patients’ baseline CHA 2 DS 2 -VASc scores and divided them into three risk groups: 0 or 1 point as low risk, 2 points as intermediate risk, and 3 or more points as high risk. Higher risk categorization by physicians was defined as "overestimation," while lower risk categorization was defined as "underestimation." The independent association of physician-patient risk concordance with OAC use was explored by multivariable Logistic regression models. Results: Among the 285 patients enrolled in this study (mean age 68±12 years, male 72.6%), the mean CHA 2 DS 2 -VASc score was 2.3±1.6. Physicians correctly estimated stroke risk in 147 patients (51.6%), underestimated it in 25 patients (8.8%) and overestimated it in 113 patients (39.6%). OACs were used in 89.8% of patients whose stroke risk was correctly estimated, 72.0% of those whose stroke risk was underestimated, and 84.1% of patients whose health status was overestimated. After multivariable adjustment, the underestimation of stroke risk was independently associated with less use of OACs (adjusted odds ratio 0.23, 95% CI 0.061-0.85, P=0.028). Conclusions: In this cohort study, physician underestimation of stroke risk was not rare and associated with less use of OACs.

Abstract 4122948: Lipoprotein(a) associated risk of atherosclerotic cardiovascular disease is independent of C-reactive protein

Background: Elevated lipoprotein(a), present in 1 in 5 individuals, is considered a causal risk factor for atherosclerotic cardiovascular disease (ASCVD). Recent studies have reached contrasting conclusions on whether low-grade inflammation measured by elevated C-reactive protein (CRP) modifies the risk of ASCVD from high lipoprotein(a). We tested the hypothesis that high lipoprotein(a) associates with risk of recurrent ASCVD irrespective of elevated or low CRP. Additionally, we performed meta-analyses of previous studies on lipoprotein(a)-associated ASCVD risk stratified by CRP levels and by incident or recurrent events. Methods: We included 3,543 individuals with prevalent ASCVD from the Copenhagen General Population Study (CGPS), a contemporary, prospective Danish cohort study. Hazard ratios (HR) for ASCVD were examined using multivariable adjusted Cox regressions stratified by CRP (&lt;2 mg/L and ≥2 mg/L). Random-effects meta-analyses in primary (incident events) and secondary (recurrent events) prevention were conducted separately, including studies on lipoprotein(a) and risk of ASCVD stratified by CRP. Results: During a median of 7.5 years of follow-up of 3,543 CGPS participants with established ASCVD, 1,425 experienced a recurrent ASCVD event. Multivariable adjusted HRs for ASCVD for high vs. low lipoprotein(a) were 1.41 (95% confidence interval: 1.19-1.67) and 1.31 (1.08-1.59) in individuals with low or elevated CRP with no evidence of effect modification (Figure 1A, p for interaction=0.11). When risk estimates for ASCVD were summarized in separate meta-analyses for primary and secondary prevention settings, a 50 mg/dL higher lipoprotein(a) was robustly associated with increased risk of ASCVD irrespective of CRP levels (Figure 1B). In primary prevention, a 50 mg/dL higher lipoprotein(a) associated with similar summary HRs of 1.18 (1.15-1.20) in low CRP vs. 1.16 (1.14-1.19) in elevated CRP, and likewise in secondary prevention settings, with similar HRs of 1.10 (1.07-1.14) and 1.14 (1.10-1.17), respectively. Conclusion: High lipoprotein(a) was associated with increased risk of ASCVD irrespective of CRP levels both in primary and secondary prevention settings.

Abstract 4135082: Small dense low-density lipoprotein cholesterol and risk of peripheral artery disease

Background: High levels of small dense low-density lipoprotein (sdLDL) is a hallmark of dyslipidemia; however, studies on sdLDL cholesterol levels and risk of peripheral artery disease are sparse and results inconclusive. Hypothesis: We tested the hypothesis that higher levels of sdLDL cholesterol are associated with increased risk of peripheral artery disease in a primary prevention setting. Methods: We studied 31,036 individuals free of lipid-lowering therapy, ischemic stroke, and myocardial infarction at study entry in 2013-2017. All had fresh sample measurements of sdLDL cholesterol. During a median follow-up on 6.2 years, 155 were diagnosed with peripheral artery disease. The association was confirmed using ankle-brachial index (ABI) ≤ 0.9 as endpoint. Lastly, as comparison across different vascular beds risk estimates for myocardial infarction and ischemic stroke were calculated. Results: Higher levels of sdLDL cholesterol were associated with higher risk of peripheral artery disease and an ABI ≤ 0.9 illustrated by cubic splines multivariable adjusted for sex, systolic blood pressure, education, body mass index (BMI), diabetes, large buoyant LDL cholesterol, and age. Per 1 mmol/L (37 mg/dL) higher sdLDL cholesterol hazard ratio for peripheral artery disease was 2.01 (95% CI: 1.41-2.85) and odds ratio for an ABI ≤ 0.9 was 1.51 (95% CI: 1.07-2.14) in multivariable adjusted models. The cumulative incidence of peripheral artery disease was respectively 1.5%, 2.5%, and 3.5% for individuals having a sdLDL cholesterol in the 1 st -50 th , 51 st -90 th , and the 91 st -100 th percentiles at age 80. For the 91 st -100 th versus the 1 st -50 th percentile a hazard ratio on 2.51 (95% CI: 1.50-4.20) for peripheral artery disease, 2.18 (95% CI: 1.58-3.01) for myocardial infarction, and 1.85 (95% CI: 1.37-2.49) for ischemic stroke was found. Furthermore, the association of higher sdLDL cholesterol with increased risk of peripheral artery disease was robust in sensitivity analyses. Conclusion: Higher levels of sdLDL cholesterol were robustly associated with increased risk of peripheral artery disease in a primary prevention setting.

Abstract 4137836: Association of AHA PREVENT Risk Score with Cardiovascular Mortality Across Social Determinants of Health: A Nationwide Retrospective Cohort Study

Introduction/Background: The AHA PREVENT risk calculator was recently developed to accurately predict the risk of cardiovascular disease (CVD) risk, including incident heart failure, stroke, and coronary heart disease. However, the risk prediction of this tool for CVD mortality overall and among groups with increasing social determinants of health (SDOH) burden in a multi-ethnic nationally representative cohort of American adults is unclear. Methods: This retrospective study included adult NHANES participants (age &gt; 30 years) from 1998-2018 cycles without known CVD. Individuals without data for risk estimation were excluded. AHA PREVENT risk was scored from 0 to 100. Multivariable-adjusted Cox regression models were used to estimate the risk of CVD mortality, accounting for 7 SDOH measures (employment, family income, food security, health access, health insurance, housing instability, and being married or living with partner). Population was stratified based on cumulative SDOH burden (1, 2, 3, 4, 5, &gt; 5 unfavorable SDOH markers). Model discrimination was assessed using C-statistics in these groups. Results: Among 19,887 participants (median age 53 years, 49% Female, 54% White, 19% Black), a 1% increase in AHA PREVENT Risk score calculation was associated with 13% higher risk of CVD mortality (HR adj 1.13, 95% CI: 1.12-1.14) with C-statistic of 0.91. While AHA PREVENT Risk score was predictive of CVD mortality across the SDOH burden strata, there was a decline in C-statistic from 0.91 among those without any unfavorable SDOH to 0.81 among those with &gt; 5 unfavorable SDOH measures. Conclusion: The AHA PREVENT Risk score is predictive of CVD mortality even when accounting for SDOH measures. However, the risk discrimination decreases among individuals with a higher SDOH burden. Further investigation is needed to identify means to improve CVD risk prediction among disadvantaged people with high unfavorable SDOH burden.

Abstract 4137169: Artificial Intelligence-Enabled Electrocardiography For The Prediction of Future Type 2 Diabetes Mellitus

Background: Undiagnosed diabetes and prediabetes present a significant global health challenge. Artificial Intelligence-enabled electrocardiography (AI-ECG) has shown promise in identifying subtle ECG changes in a wide range of subclinical diseases. Opportunistic ECG screening could identify prediabetic patients, enabling early interventions to prevent T2DM and adverse cardiovascular events. Aims: To develop the AI-ECG Risk Estimator to diagnose prevalent T2DM and predict future T2DM (AIRE-DM) Methods: AIRE-DM was trained on a real-world secondary care cohort from Beth Israel Deaconess Medical Center (BIDMC) of 1,163,401 ECGs and externally validated in the UK Biobank (UKB, N = 65,606). AIRE-DM employs a residual neural network architecture with a discrete-time survival loss function. Results: AIRE-DM accurately identifies prevalent T2DM (AUROC: BIDMC – 0.712 (0.705-0.719), UKB - 0.731 (0.725 - 0.741) and predicts future T2DM (C-index: BIDMC - 0.666 (0.658-0.675), UKB 0.689 (0.663-0.715). In subjects without T2DM, the high-risk quartile shows a markedly increased risk of future T2DM (HR: BIDMC - 4.67 (4.01-5.45), UKB - 10.10 (5.87-17.40), adjusted for age and sex. Adding AIRE-DM to clinical risk factors in BIDMC and to the American Diabetes Association (ADA) score in the UKB significantly enhanced predictive accuracy for future T2DM (C-index improvement: BIDMC - 0.0359 (0.0354-0.0363), UKB: 0.0337 (0.0324-0.0350), continuous net reclassification index: BIDMC - 0.407 (0.360-0.445), UKB - 0.391 (0.259-0.503)). Using phenome- and genome-wide association studies, we identified biologically plausible associations for AIRE-DM, including glucose regulation, cardiac morphology, diastolic dysfunction, arterial stiffness and lipid metabolism. We identified variants adjacent to CASQ2 , TBX3 , NOS1AP , TKT , VGLL2 and PRDM6 , which are known regulators of cardiac morphology, arterial stiffness and glucose metabolism. Conclusion: AIRE-DM can predict future T2DM in non-diabetics and enhances T2DM risk prediction when integrated with clinical risk scores. Its application holds promise for early identification of individuals at high risk of T2DM, enabling early lifestyle and pharmacological interventions.