Deep learning evaluation of echocardiograms to identify occult atrial fibrillation.

Atrial fibrillation (AF) often escapes detection, given its frequent paroxysmal and asymptomatic presentation. Deep learning of transthoracic echocardiograms (TTEs), which have structural information, could help identify occult AF. We created a two-stage deep learning algorithm using a video-based convolutional neural network model that (1) distinguished whether TTEs were in sinus rhythm or AF and then (2) predicted which of the TTEs in sinus rhythm were in patients who had experienced AF within 90 days. Our model, trained on 111,319 TTE videos, distinguished TTEs in AF from those in sinus rhythm with high accuracy in a held-out test cohort (AUC 0.96 (0.95-0.96), AUPRC 0.91 (0.90-0.92)). Among TTEs in sinus rhythm, the model predicted the presence of concurrent paroxysmal AF (AUC 0.74 (0.71-0.77), AUPRC 0.19 (0.16-0.23)). Model discrimination remained similar in an external cohort of 10,203 TTEs (AUC of 0.69 (0.67-0.70), AUPRC 0.34 (0.31-0.36)). Performance held across patients who were women (AUC 0.76 (0.72-0.81)), older than 65 years (0.73 (0.69-0.76)), or had a CHA2DS2VASc ≥2 (0.73 (0.79-0.77)). The model performed better than using clinical risk factors (AUC 0.64 (0.62-0.67)), TTE measurements (0.64 (0.62-0.67)), left atrial size (0.63 (0.62-0.64)), or CHA2DS2VASc (0.61 (0.60-0.62)). An ensemble model in a cohort subset combining the TTE model with an electrocardiogram (ECGs) deep learning model performed better than using the ECG model alone (AUC 0.81 vs. 0.79, p = 0.01). Deep learning using TTEs can predict patients with active or occult AF and could be used for opportunistic AF screening that could lead to earlier treatment.

Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study.

BACKGROUND: Preoperative risk assessments used in clinical practice are insufficient in their ability to identify risk for postoperative mortality. Deep-learning analysis of electrocardiography can identify hidden risk markers that can help to prognosticate postoperative mortality. We aimed to develop a prognostic model that accurately predicts postoperative mortality in patients undergoing medical procedures and who had received preoperative electrocardiographic diagnostic testing. METHODS: In a derivation cohort of preoperative patients with available electrocardiograms (ECGs) from Cedars-Sinai Medical Center (Los Angeles, CA, USA) between Jan 1, 2015 and Dec 31, 2019, a deep-learning algorithm was developed to leverage waveform signals to discriminate postoperative mortality. We randomly split patients (8:1:1) into subsets for training, internal validation, and final algorithm test analyses. Model performance was assessed using area under the receiver operating characteristic curve (AUC) values in the hold-out test dataset and in two external hospital cohorts and compared with the established Revised Cardiac Risk Index (RCRI) score. The primary outcome was post-procedural mortality across three health-care systems. FINDINGS: 45 969 patients had a complete ECG waveform image available for at least one 12-lead ECG performed within the 30 days before the procedure date (59 975 inpatient procedures and 112 794 ECGs): 36 839 patients in the training dataset, 4549 in the internal validation dataset, and 4581 in the internal test dataset. In the held-out internal test cohort, the algorithm discriminates mortality with an AUC value of 0·83 (95% CI 0·79-0·87), surpassing the discrimination of the RCRI score with an AUC of 0·67 (0·61-0·72). The algorithm similarly discriminated risk for mortality in two independent US health-care systems, with AUCs of 0·79 (0·75-0·83) and 0·75 (0·74-0·76), respectively. Patients determined to be high risk by the deep-learning model had an unadjusted odds ratio (OR) of 8·83 (5·57-13·20) for postoperative mortality compared with an unadjusted OR of 2·08 (0·77-3·50) for postoperative mortality for RCRI scores of more than 2. The deep-learning algorithm performed similarly for patients undergoing cardiac surgery (AUC 0·85 [0·77-0·92]), non-cardiac surgery (AUC 0·83 [0·79-0·88]), and catheterisation or endoscopy suite procedures (AUC 0·76 [0·72-0·81]). INTERPRETATION: A deep-learning algorithm interpreting preoperative ECGs can improve discrimination of postoperative mortality. The deep-learning algorithm worked equally well for risk stratification of cardiac surgeries, non-cardiac surgeries, and catheterisation laboratory procedures, and was validated in three independent health-care systems. This algorithm can provide additional information to clinicians making the decision to perform medical procedures and stratify the risk of future complications. FUNDING: National Heart, Lung, and Blood Institute.

Risk Factors for the Development of New-Onset Persistent Atrial Fibrillation: Subanalysis of the VITAL Study.

BACKGROUND: Sustained forms of atrial fibrillation (AF) are associated with lower treatment success rates and poorer prognosis compared with paroxysmal AF. Yet, little is known about risk factors that predispose to persistent AF on initial presentation. Our objective was to define risk factors associated with new-onset persistent AF. METHODS: We prospectively examined the differential associations between lifestyle, clinical, and socioeconomic risk factors and AF pattern (persistent versus paroxysmal) at the time of diagnosis among 25 119 participants without a history of cardiovascular disease, AF, or cancer in the VITAL rhythm study (Vitamin D and Omega-3). RESULTS: During a median follow-up of 5.3 years, 900 participants developed AF and 346 (38.4%) were classified as persistent at the time of diagnosis. In multivariable competing risk models, increasing age, male sex, White race, height, weight, body mass index ≥30 kg/m2, hypertension, current or past smoking, alcohol intake ≥2 drinks/day, postcollege education, and randomized treatment with vitamin D were significantly associated with incident persistent AF. Compared with paroxysmal AF, increasing age, male sex, weight, body mass index ≥30 kg/m2, and postcollege education were more strongly associated with persistent AF in multivariable models regardless of whether interim cardiovascular disease and heart failure events were censored. CONCLUSIONS: In a prospective cohort without baseline AF or cardiovascular disease, over one-third of AF at the time of diagnosis is persistent. Older age, male sex, postcollege education, and obesity were preferentially associated with persistent AF and represent a high-risk AF subset for population-based intervention.

Air Pollution and Temperature: a Systematic Review of Ubiquitous Environmental Exposures and Sudden Cardiac Death.

PURPOSE OF REVIEW: Environmental exposures have been associated with increased risk of cardiovascular mortality and acute coronary events, but their relationship with out-of-hospital cardiac arrest (OHCA) and sudden cardiac death (SCD) remains unclear. SCD is an important contributor to the global burden of cardiovascular disease worldwide. RECENT FINDINGS: Current literature suggests a relationship between environmental exposures and cardiovascular disease, but their relationship with OHCA/SCD remains unclear. A literature search was conducted in PubMed, Embase, Web of Science, and Global Health. Of 5138 studies identified by our literature search, this review included 30 studies on air pollution, 42 studies on temperature, 6 studies on both air pollution and temperature, and 1 study on altitude exposure and OHCA/SCD. Particulate matter air pollution, ozone, and both hot and cold temperatures are associated with increased risk of OHCA/SCD. Pollution and other exposures related to climate change play an important role in OHCA/SCD incidence.

Marine n-3 Fatty Acids and Prevention of Cardiovascular Disease: A Novel Analysis of the VITAL Trial Using Win Ratio and Hierarchical Composite Outcomes.

This study aimed to investigate whether n-3 fatty acid supplementation reduced cardiovascular disease (CVD) events in a novel analysis using hierarchical composite CVD outcomes based on win ratio in the VITamin D and OmegA-3 TriaL (VITAL). This was a secondary analysis of our VITAL randomized trial, which assessed the effects of marine n-3 fatty acids (1 g/day) and vitamin D3 on incident CVD and cancer among healthy older adults (n = 25,871). The primary analysis estimated win ratios of a composite of major CVD outcomes prioritized as fatal coronary heart disease, other fatal CVD including stroke, non-fatal myocardial infarction (MI), and non-fatal stroke, comparing n-3 fatty acids to placebo. The primary result was a nonsignificant benefit of this supplementation for the prioritized primary CVD outcome (reciprocal win ratio [95% confidence interval]: 0.90 [0.78-1.04]), similar to the 0.92 (0.80-1.06) hazard ratio in our original time-to-first event analysis without outcome prioritization. Its benefits came from reducing MI (0.71 [0.57-0.88]) but not stroke (1.01 [0.80 to 1.28]) components. For the primary CVD outcome, participants with low fish consumption at baseline benefited (0.79 [0.65-0.96]) more than those with high consumption (1.05 [0.85-1.30]). These results are consistent with, but slightly stronger than, those without outcome prioritization.

The Lancet Commission to reduce the global burden of sudden cardiac death: a call for multidisciplinary action.

Despite major advancements in cardiovascular medicine, sudden cardiac death (SCD) continues to be an enormous medical and societal challenge, claiming millions of lives every year. Efforts to prevent SCD are hampered by imperfect risk prediction and inadequate solutions to specifically address arrhythmogenesis. Although resuscitation strategies have witnessed substantial evolution, there is a need to strengthen the organisation of community interventions and emergency medical systems across varied locations and health-care structures. With all the technological and medical advances of the 21st century, the fact that survival from sudden cardiac arrest (SCA) remains lower than 10% in most parts of the world is unacceptable. Recognising this urgent need, the Lancet Commission on SCD was constituted, bringing together 30 international experts in varied disciplines. Consistent progress in tackling SCD will require a completely revamped approach to SCD prevention, with wide-sweeping policy changes that will empower the development of both governmental and community-based programmes to maximise survival from SCA, and to comprehensively attend to survivors and decedents' families after the event. International collaborative efforts that maximally leverage and connect the expertise of various research organisations will need to be prioritised to properly address identified gaps. The Commission places substantial emphasis on the need to develop a multidisciplinary strategy that encompasses all aspects of SCD prevention and treatment. The Commission provides a critical assessment of the current scientific efforts in the field, and puts forth key recommendations to challenge, activate, and intensify efforts by both the scientific and global community with new directions, research, and innovation to reduce the burden of SCD worldwide.

Risk of Arrhythmic Death in Patients With Nonischemic Cardiomyopathy: JACC Review Topic of the Week.

Nonischemic cardiomyopathy (NICM) is common and patients are at significant risk for early mortality secondary to ventricular arrhythmias. Current guidelines recommend implantable cardioverter-defibrillator (ICD) therapy to decrease sudden cardiac death (SCD) in patients with heart failure and reduced left ventricular ejection fraction. However, in randomized clinical trials comprised solely of patients with NICM, primary prevention ICDs did not confer significant mortality benefit. Moreover, left ventricular ejection fraction has limited sensitivity and specificity for predicting SCD. Therefore, precise risk stratification algorithms are needed to define those at the highest risk of SCD. This review examines mechanisms of sudden arrhythmic death in patients with NICM, discusses the role of ICD therapy and treatment of heart failure for prevention of SCD in patients with NICM, examines the role of cardiac magnetic resonance imaging and computational modeling for SCD risk stratification, and proposes new strategies to guide future clinical trials on SCD risk assessment in patients with NICM.

A randomized clinical trial of omega-3 fatty acid and vitamin D supplementation on electrocardiographic risk profiles.

Beneficial and adverse associations with arrhythmias have been reported for omega-3 fatty acids (omega-3 FA) and Vitamin D. The 12 lead electrocardiogram (ECG) contains quantitative measures reflecting diverse aspects of electrophysiology that might provide insights into mechanisms underlying these associations. In a pre-specified ancillary study of the VITaminD and omegA-3 (VITAL) trial, we examined the effect of 1 g of marine omega-3 FA per day, comprised of 460 mg eicosapentanoic acid and 380 mg of docosahexaenoic acid, and 2000 IU VitaminD3 per day on ECG characteristics associated with atrial and ventricular arrhythmias among individuals age 50 years or greater. A total of 911 study participants underwent ECGs at baseline and again at 2 years after the randomization. Individuals randomized to active omega-3 FA demonstrated significant net increase in PR-interval duration (p = 0.005) and P-wave duration (p = 0.03) as well significant net decrease in P-wave amplitude (p = 0.037) as compared to placebo. RMSSD increased to a greater extent in the omega-3 FA arm compared to placebo (p = 0.040). For Vitamin D3, the Cornell voltage increased to a lesser extent in the participants assigned to active treatment as compared to placebo (p = 0.044). There were no other significant differences in QRS, QTc, Cornell voltage or heart rate. Thus, randomized treatment with omega-3 FA supplements resulted in changes on the ECG that are potentially reflective of heightened vagal tone and/or slowing of intraatrial and AV conduction. Vitamin D3 supplementation resulted in modest reductions in progressive LV voltage suggestive of a potential antihypertrophic effect.Trial registration ClinicalTrials.gov Identifiers: NCT01169259, NCT02178410 (06/26/2010 and 06/30/2014).

Omega-3 Fatty Acid Biomarkers and Incident Atrial Fibrillation.

BACKGROUND: The relationship between omega-3 fatty acids and atrial fibrillation (AF) remains controversial. OBJECTIVES: This study aimed to determine the prospective associations of blood or adipose tissue levels of eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA) with incident AF. METHODS: We used participant-level data from a global consortium of 17 prospective cohort studies, each with baseline data on blood or adipose tissue omega-3 fatty acid levels and AF outcomes. Each participating study conducted a de novo analyses using a prespecified analytical plan with harmonized definitions for exposures, outcome, covariates, and subgroups. Associations were pooled using inverse-variance weighted meta-analysis. RESULTS: Among 54,799 participants from 17 cohorts, 7,720 incident cases of AF were ascertained after a median 13.3 years of follow-up. In multivariable analysis, EPA levels were not associated with incident AF, HR per interquintile range (ie, the difference between the 90th and 10th percentiles) was 1.00 (95% CI: 0.95-1.05). HRs for higher levels of DPA, DHA, and EPA+DHA, were 0.89 (95% CI: 0.83-0.95), 0.90 (95% CI: 0.85-0.96), and 0.93 (95% CI: 0.87-0.99), respectively. CONCLUSIONS: In vivo levels of omega-3 fatty acids including EPA, DPA, DHA, and EPA+DHA were not associated with increased risk of incident AF. Our data suggest the safety of habitual dietary intakes of omega-3 fatty acids with respect to AF risk. Coupled with the known benefits of these fatty acids in the prevention of adverse coronary events, our study suggests that current dietary guidelines recommending fish/omega-3 fatty acid consumption can be maintained.

Deep learning-enabled analysis of medical images identifies cardiac sphericity as an early marker of cardiomyopathy and related outcomes.

BACKGROUND: Quantification of chamber size and systolic function is a fundamental component of cardiac imaging. However, the human heart is a complex structure with significant uncharacterized phenotypic variation beyond traditional metrics of size and function. Examining variation in cardiac shape can add to our ability to understand cardiovascular risk and pathophysiology. METHODS: We measured the left ventricle (LV) sphericity index (short axis length/long axis length) using deep learning-enabled image segmentation of cardiac magnetic resonance imaging data from the UK Biobank. Subjects with abnormal LV size or systolic function were excluded. The relationship between LV sphericity and cardiomyopathy was assessed using Cox analyses, genome-wide association studies, and two-sample Mendelian randomization. FINDINGS: In a cohort of 38,897 subjects, we show that a one standard deviation increase in sphericity index is associated with a 47% increased incidence of cardiomyopathy (hazard ratio [HR]: 1.47, 95% confidence interval [CI]: 1.10-1.98, p = 0.01) and a 20% increased incidence of atrial fibrillation (HR: 1.20, 95% CI: 1.11-1.28, p < 0.001), independent of clinical factors and traditional magnetic resonance imaging (MRI) measurements. We identify four loci associated with sphericity at genome-wide significance, and Mendelian randomization supports non-ischemic cardiomyopathy as causal for LV sphericity. CONCLUSIONS: Variation in LV sphericity in otherwise normal hearts predicts risk for cardiomyopathy and related outcomes and is caused by non-ischemic cardiomyopathy. FUNDING: This study was supported by grants K99-HL157421 (D.O.) and KL2TR003143 (S.L.C.) from the National Institutes of Health.

Epidemiology and modifiable risk factors for atrial fibrillation.

The global prevalence of atrial fibrillation (AF) has increased substantially over the past three decades and is currently approximately 60 million cases. Incident AF and its clinical consequences are largely the result of risk factors that can be modified by lifestyle changes. In this Review, we provide evidence that the lifetime risk of AF is modified not only by sex and race but also through the clinical risk factor and comorbidity burden of individual patients. We begin by summarizing the epidemiology of AF, focusing on non-modifiable and modifiable risk factors, as well as targets and strategies for the primary prevention of AF. Furthermore, we evaluate the role of modifiable risk factors in the secondary prevention of AF as well as the potential effects of risk factor interventions on the frequency and severity of subsequent AF episodes. We end the Review by proposing strategies that require evaluation as well as global policy changes that are needed for the prevention of incident AF and the management of recurrent episodes in patients already affected by AF.

Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing.

Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.

Transforming Atrial Fibrillation Research to Integrate Social Determinants of Health: A National Heart, Lung, and Blood Institute Workshop Report.

Importance: Only modest attention has been paid to the contributions of social determinants of health to atrial fibrillation (AF) risk factors, diagnosis, symptoms, management, and outcomes. The diagnosis of AF provides unique challenges exacerbated by the arrhythmia's often paroxysmal nature and individuals' disparate access to health care and technologies that facilitate detection. Social determinants of health affect access to care and management decisions for AF, increasing the likelihood of adverse outcomes among individuals who experience systemic disadvantages. Developing effective approaches to address modifiable social determinants of health requires research to eliminate the substantive inequities in health care delivery and outcomes in AF. Observations: The National Heart, Lung, and Blood Institute convened an expert panel to identify major knowledge gaps and research opportunities in the field of social determinants of AF. The workshop addressed the following social determinants: (1) socioeconomic status and access to care; (2) health literacy; (3) race, ethnicity, and racism; (4) sex and gender; (5) shared decision-making in systemically disadvantaged populations; and (6) place, including rurality, neighborhood, and community. Many individuals with AF have multiple adverse social determinants, which may cluster in the individual and in systemically disadvantaged places (eg, rural locations, urban neighborhoods). Cumulative disadvantages may accumulate over the life course and contribute to inequities in the diagnosis, management, and outcomes in AF. Conclusions and Relevance: Workshop participants identified multiple critical research questions and approaches to catalyze social determinants of health research that address the distinctive aspects of AF. The long-term aspiration of this work is to eradicate the substantive inequities in AF diagnosis, management, and outcomes across populations.

Genetic diversity fuels gene discovery for tobacco and alcohol use.

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Hypertension and atrial fibrillation.

Hypertension is the most prevalent cardiovascular risk factor underlying atrial fibrillation and is present in up to 40% of patients with atrial fibrillation. Furthermore, attributable risk studies have shown that a history of hypertension contributes to up to 24% of incident atrial fibrillation. New data suggest that even early forms of hypertension (prehypertension and aortic stiffness) are associated with an increased risk of atrial fibrillation development. Hypertension and prehypertension are therefore critical mediators for the development of atrial fibrillation. Mechanisms for the association between hypertension and atrial fibrillation include diffuse electro-structural changes to the left atrium, driven by the haemodynamic and neurohormonal influences of hypertension and other, frequently coexisting, cardiovascular risk factors. Management of hypertension in atrial fibrillation should focus not only on blood pressure reduction but also on a comprehensive risk factor modification strategy. Such strategies have been shown to be associated with significant improvements in atrial fibrillation symptom burden as well as improved arrhythmia-free survival and reversal of the progression of atrial fibrillation. These strategies should focus on dietary modifications as well as prescribed exercise programmes involving a multidisciplinary team and patient-centred atrial fibrillation care. Risk factor management, supplemented by antihypertensive medications as needed, provides the optimum strategy for improving outcomes and even reversing the natural progression of atrial fibrillation in patients with hypertension.

Differences in Metabolomic Profiles Between Black and White Women and Risk of Coronary Heart Disease: an Observational Study of Women From Four US Cohorts.

BACKGROUND: Racial differences in metabolomic profiles may reflect underlying differences in social determinants of health by self-reported race and may be related to racial disparities in coronary heart disease (CHD) among women in the United States. However, the magnitude of differences in metabolomic profiles between Black and White women in the United States has not been well-described. It also remains unknown whether such differences are related to differences in CHD risk. METHODS: Plasma metabolomic profiles were analyzed using liquid chromatography-tandem mass spectrometry in the WHI-OS (Women's Health Initiative-Observational Study; 138 Black and 696 White women), WHI-HT trials (WHI-Hormone Therapy; 156 Black and 1138 White women), MESA (Multi-Ethnic Study of Atherosclerosis; 114 Black and 219 White women), JHS (Jackson Heart Study; 1465 Black women with 107 incident CHD cases), and NHS (Nurses' Health Study; 2506 White women with 136 incident CHD cases). First, linear regression models were used to estimate associations between self-reported race and 472 metabolites in WHI-OS (discovery); findings were replicated in WHI-HT and validated in MESA. Second, we used elastic net regression to construct a racial difference metabolomic pattern (RDMP) representing differences in the metabolomic patterns between Black and White women in the WHI-OS; the RDMP was validated in the WHI-HT and MESA. Third, using conditional logistic regressions in the WHI (717 CHD cases and 719 matched controls), we examined associations of metabolites with large differences in levels by race and the RDMP with risk of CHD, and the results were replicated in Black women from the JHS and White women from the NHS. RESULTS: Of the 472 tested metabolites, levels of 259 (54.9%) metabolites, mostly lipid metabolites and amino acids, significantly differed between Black and White women in both WHI-OS and WHI-HT after adjusting for baseline characteristics, socioeconomic status, lifestyle factors, baseline health conditions, and medication use (false discovery rate <0.05); similar trends were observed in MESA. The RDMP, composed of 152 metabolites, was identified in the WHI-OS and showed significantly different distributions between Black and White women in the WHI-HT and MESA. Higher RDMP quartiles were associated with an increased risk of incident CHD (odds ratio=1.51 [0.97-2.37] for the highest quartile comparing to the lowest; Ptrend=0.02), independent of self-reported race and known CHD risk factors. In race-stratified analyses, the RDMP-CHD associations were more pronounced in White women. Similar patterns were observed in Black women from the JHS and White women from the NHS. CONCLUSIONS: Metabolomic profiles significantly and substantially differ between Black and White women and may be associated with CHD risk and racial disparities in US women.

Polygenic Risk Score Predicts Sudden Death in Patients With Coronary Disease and Preserved Systolic Function.

BACKGROUND: A familial predisposition to sudden and/or arrhythmic death (SAD) in the setting of coronary artery disease (CAD) exists; however, the genetic basis is poorly understood. OBJECTIVES: The purpose of this study was to determine whether a genome-wide polygenic score for coronary artery disease (GPSCAD) might have utility in SAD risk stratification in CAD patients without severe systolic dysfunction. METHODS: A previously validated GPSCAD was generated utilizing genome-wide genotyping in 4,698 PRE-DETERMINE participants of European ancestry with CAD and left ventricular ejection fraction >30%-35%. The population was dichotomized according to top GPSCAD decile as defined by the general population, and absolute, proportional, and relative risks for SAD and non-SAD were estimated using competing risk analyses. RESULTS: Over a median follow-up of 8.0 years, participants in the top GPSCAD decile were at elevated absolute SAD risk (8.0%; 95% CI: 5.1%-12.4% vs 4.8%; 95% CI: 3.3%-7.0%; P = 0.005) and proportional SAD risk (29% vs 16%; P = 0.0003) compared with the remainder. After controlling for left ventricular ejection fraction, clinical factors, and electrocardiogram parameters, the top GPSCAD decile was associated with SAD (subdistribution HR: 1.77; 95% CI: 1.23-2.54; P = 0.002) but not non-SAD (subdistribution HR: 1.00; 95% CI: 0.80-1.25; P = 0.98) (P for Δ = 0.003). The addition of the top GPSCAD decile to the multivariable model significantly improved net reclassification indexes (NRIs) (continuous NRI: 14.0%; P = 0.024; and categorical NRI: 6.6%; P = 0.005) but not the C-index (difference in C-index: 0.007; P = 0.143). CONCLUSIONS: Among CAD patients without severe systolic dysfunction, high GPSCAD specifically predicted SAD and enriched for both absolute and proportional SAD risk, identifying a population who might benefit from defibrillator therapy.

Sex Differences in Atrial Fibrillation Risk: The VITAL Rhythm Study.

Importance: Women have a lower incidence of atrial fibrillation (AF) compared with men in several studies, but it is unclear whether this sex difference is independent of sex differences in prevalent cardiovascular disease (CVD), body size, and other risk factors. Objective: To examine sex differences in AF incidence and whether AF risk factors differ by sex in a contemporary cohort of men and women without prevalent CVD. Design, Setting, and Participants: This was a prospective cohort analysis within the Vitamin D and Omega-3 Trial (VITAL) Rhythm Study, a randomized trial that examined the effect of vitamin D and ω-3 fatty acid supplementation on incident AF among men 50 years or older and women 55 years or older without a prior history of prevalent AF, CVD, or cancer at baseline. Data were analyzed from September 29, 2020, to June 29, 2021. Exposures: Sex, height, weight, body mass index (BMI), body surface area (BSA), and other AF risk factors at study enrollment. Main Outcomes and Measures: Incident AF confirmed by medical record review. Results: A total of 25 119 individuals (mean [SD] age, 67.0 [7.1] years; 12 757 women [51%]) were included in this study. Over a median (IQR) follow-up of 5.3 (5.1-5.7) years, 900 confirmed incident AF events occurred among 12 362 men (495 events, 4.0%) and 12 757 women (405 events, 3.2%). After adjustment for age and treatment assignment, women were at lower risk for incident AF than men (hazard ratio [HR], 0.68; 95% CI, 0.59-0.77; P < .001). The inverse association between female sex and AF persisted after adjustment for race and ethnicity, smoking, alcohol intake, hypertension, diabetes (type 1, type 2, gestational), thyroid disease, exercise, and BMI (HR, 0.73; 95% CI, 0.63-0.85; P <.001). However, female sex was positively associated with AF when height (HR, 1.39; 95% CI, 1.14-1.72; P = .001), height and weight (HR 1.49, 95% CI, 1.21-1.82; P <.001), or BSA (HR, 1.25; 95% CI, 1.06-1.49; P = .009) were substituted for BMI in the multivariate model. In stratified models, risk factor associations with incident AF were similar for women and men. Conclusions and Relevance: In this cohort study, findings suggest that after controlling for height and/or body size, women without CVD at baseline were at higher risk for AF than men, suggesting that sex differences in body size account for much of the protective association between female sex and AF. These data underscore the importance of AF prevention in women.