Incidence Of Atrial Fibrillation Research Articles

Insulin mitigates acute ischemia induced atrial fibrillation and sinoatrial node dysfunction ex vivo.

Acute atrial ischemia is a well-known cause of postoperative atrial fibrillation (POAF). However, mechanisms through which ischemia contributes to the development of POAF are not well understood. In this study, ex vivo Langendorff perfusion was used to induce acute ischemia and reperfusion in the heart in order to mimic POAF. Inducibility of atrial fibrillation (AF) was evaluated using programmed electrical stimulation and confirmed with open-atrium optical mapping. Compared to the control group without ischemia, 25 minutes of ischemia substantially increased the incidence of AF. The right atrium was more susceptible to AF than the left atrium. Administering insulin for 30 minutes before ischemia and during reperfusion with 25 minutes of ischemia greatly reduced the vulnerability to AF. However, insulin treatment during reperfusion only did not show substantial benefits against AF. Optical mapping studies showed that insulin mitigates ischemia-induced abnormal electrophysiology, including shortened action potential duration and effective refractory period, slowed conduction velocity, increased conduction heterogeneity, and altered calcium transients. In conclusion, insulin reduced the risk of acute ischemia/reperfusion-induced AF via improving the electrophysiology and calcium handling of atrial cardiomyocytes, which provides a potential therapy for POAF.

Abstract 4138604: Impact of GLP-1 Agonist on the Incidence of Atrial Fibrillation in Obese Patients Following Heart Failure Hospitalization

Introduction: Atrial fibrillation (AF) in patients with heart failure (HF) is associated with increased morbidity and mortality. Glucagon-like peptide-1 (GLP-1) agonists have been shown to reduce cardiovascular risk in patients with obesity and diabetes, respectively. Meta-analysis of prospective trials looking at GLP-1 agonist use on the incidence of AF suggest benefit in patients with diabetes but is of unclear benefit in this regard for patients with obesity. Hypothesis: GLP-1 agonists reduce atrial fibrillation incidence in patients with diabetes and obesity. Aims: The goal of the study is to assess the effects of GLP-1 agonist on incidence of new AF in patients with obesity and diabetes following heart failure hospitalization. Methods: The study included consecutive patients who were admitted to an academic tertiary care center over three years with a primary diagnosis of heart failure exacerbation and no prior diagnosis of AF. The primary outcome was incidence of AF within 12 months after hospitalization. Demographic, comorbidity, echocardiography, and medications were obtained. Cox-regression analysis was performed to identify the predictors of new-onset AF following HF hospitalization. Results: Of the patients included in our study, 1668 (42.9%) have a BMI greater than or equal to 30, 574 (14.5%) have BMI greater than or equal to 40, and 2300 (58.2%) have diabetes mellitus. GLP-1 use is associated with a significantly lower incidence of AF at one year in obese patients (p=0.042; RR 0.73; 95% CI: 0.54-.99) (Figure), while in non-obese individuals, GLP-1 receptor agonist was not associated with a decreased incidence of AF (p=0.674; RR 1.08; 95% CI: 0.76-1.53). In patients with diabetes, GLP-1 receptor agonist use did not reach statistical significance for reduced AF incidence following heart failure hospitalization ( p=0.091; RR 0.80; 95% CI 0.62-1.04 ). Conclusion: GLP-1 receptor agonist use is associated with a statistically significant reduction of incidence of new atrial fibrillation at one year following hospitalization for heart failure in obese patients.

Abstract 4119300: Prevalence and Outcomes of Atrial Fibrillation during Pregnancy and Puerperium

Background: Atrial fibrillation (AF) during pregnancy and puerperium is devastating for the mother and her family, yet data regarding incidence and outcomes are very limited. Objective: We aimed to investigate the incidence and outcomes of AF during pregnancy and puerperium in a large database. The value of the CHA 2 DS 2 -VASc score in predicting adverse outcomes during pregnancy was also assessed. Study Design: The National Inpatient Sample (NIS) database was queried to identify pregnancy-related hospitalizations from 2008 to 2017. Temporal trends in the incidence and outcomes of AF were extracted. The CHA 2 DS 2 -VASc score was calculated for all patients, and the score was classified into three groups: low-risk group (1 point), moderate-risk group (2-3 points), and high-risk group (≥4 points). Results: Among 40,996,860 pregnancy-related hospitalizations, 15,162 (0.037%) were diagnosed with AF. The incidence increased from 2.18 per 10,000 hospitalizations in 2008 to 4.87 per 10,000 in 2017 ( P trend < .0001). The proportion of patients with AF increased with advanced maternal age ( P trend < .0001). Subgroup analysis showed that the incidence of AF was higher in black women, lowest-income households, and elderly parturients ( P trend < .0001). The following factors were significantly associated with AF during pregnancy: age ≥45 years, lipid metabolism disorders, hypertension, obstructive sleep apnea, hyperthyroidism, and valvular disease ( P < .0001). The in-hospital mortality rate of pregnant women with AF was significantly higher than those without AF (OR = 2.26, 95%CI = 1.75-2.93, P < .0001). The mortality rate of AF during pregnancy was positively associated with an increasing CHA 2 DS 2 -VASc score ( P trend < .0001), which was 0.35% (95% CI: 0.24%-0.47%) in the low-risk group, 1.30% (95% CI: 0.98%-1.62%) in the moderate-risk group, and 2.18% (95% CI: 0.86%-3.51%) in the high-risk group. The incidence of stroke, acute myocardial infarction, acute heart failure, and cardiac shock during pregnancy was also significantly correlated with the increasing CHA 2 DS 2 -VASc score in AF patients ( P trend < .0001), with the highest prevalence in the high-risk group. Conclusion: The incidence of AF during pregnancy and puerperium increased consistently, associated with high maternal mortality. The CHA 2 DS 2 -VASc score can be an essential risk stratification tool to predict severe cardio-cerebral vascular events and even death in AF patients during pregnancy and puerperium.

Abstract 4135617: Large Scale Proteomics Identifies Circulating Biomarkers Relating Atrial Fibrillation to Heart Failure: the Atherosclerosis Risk in Communities Study

Introduction: There is a bidirectional relationship between atrial fibrillation (AF) and heart failure (HF) risk. Data regarding shared and unique pathways underlying each are limited. Aims: Identify plasma proteins associated with both incident AF and HF and determine the extent to which associations with one outcome are conditional on interval occurrence of the other outcome. Methods: Among participants in the community-based Atherosclerosis Risk in Communities study free of HF and AF at study visit 5 (2011-2013), we measured 4,955 plasma proteins (SomaScan aptamer-affinity assay). We performed parallel analyses of individual protein associations with incident HF and AF using multivariable Cox regression adjusted for demographic and clinical covariates at Bonferroni significance. We then repeated the analysis for each outcome in models censoring participants with interval occurrence of the other outcome (i.e. incident AF censoring for interval HF, and vice versa). We tested associations of AF-related proteins with echocardiographic and Zio patch measures at Visit 5. Results: Among 4,118 participants included, mean age was 75±5 years, 60% were female, and 18% reported Black race. We identified 83 proteins associated with incident HF (n=355 incident events at 7 [IQR 6-8] year follow-up) and 24 with incident AF (n=517 incident events at 8 [7-9] years), of which 10 were associated with both. In models of incident HF censoring for interval AF, 63 (76%) proteins remained significantly associated with HF. In contrast, in the analysis of incident AF censoring for interval HF, only 4 (17%) proteins remained associated with AF, of which 3 were also associated with HF risk (Figure). These 4 AF-related proteins were associated with measures of LV diastolic function (LA volume, E/e’. average), LV mass index, LA function (LA reservoir, LA contraction), and supraventricular ectopy density (all p<0.05). Conclusion: Nearly half of proteins reflecting AF risk also associate with HF, greater than 80% of AF-associated proteins are HF-dependent, and even those that are not correlate with measures of LV remodeling and dysfunction. These findings suggest that AF-related mechanisms among older adults are part of a wider HF syndrome.

Abstract 4138611: Impact of SGLT-2 Inhibitor Use on Atrial Fibrillation Incidence Following Heart Failure Hospitalization

Introduction: The development of atrial fibrillation (AF) in patients with heart failure (HF) is associated with increased morbidity and mortality. Sodium-glucose cotransporter-2 (SGLT-2) inhibitors have demonstrated cardiovascular benefit in patients with both preserved and reduced ejection fractions. Meta analysis of prospective trials suggest reduced incidence and burden of atrial fibrillation in patients taking SGLT-2 inhibitors, though this has not been specifically addressed in prospective trials. Hypothesis: SGLT-2 inhibitors reduce the incidence of atrial fibrillation in patients with heart failure. Aim: The goal of the study is to assess the impact of SGLT-2 inhibitor on the incidence of atrial fibrillation following heart failure hospitalization. Methods: The study included consecutive patients who were admitted to an academic tertiary care center over a 3 year time period with a primary diagnosis of heart failure exacerbation and no prior diagnosis of AF. The primary outcome was development of AF within 12 months after hospitalization. Demographic, comorbidity, echocardiographic data, and medications were obtained. Cox-regression analysis was performed to identify the predictors of new-onset AF after HF hospitalization. Results: Among the 3,953 patients included in our study, 704 (17.8%) patients were prescribed SGLT-2 inhibitors. Of those taking SGLT-2 inhibitors, 559 (79.4%) patients had diabetes. SGLT-2 inhibitor use is associated with significant reduction of AF at one year ( p<0.001; RR 0.65; 95% CI: 0.51-.81 ). This finding was consistent across patients with reduced ejection fractions (EF<50%) ( p=0.001; RR 0.56; 95% CI: 0.40-.80 ) and preserved ejection fraction (EF>50%)( p=0.001; RR 0.58; 95% CI: 0.42-0.80 ). Conclusion: In patients with reduced ejection fraction and preserved ejection fraction heart failure, use of an SGLT-2 inhibitor is associated with a statistically significant lower risk of new-onset atrial fibrillation at one year following HF hospitalization.

Abstract 4135307: Integrating genomics and proteomics to identify causal proteins and biologic pathways for incident atrial fibrillation in chronic kidney disease

Introduction/ Background: Individuals with chronic kidney disease (CKD) are at an increased risk for developing atrial fibrillation (AF). Research Objective: By integrating genomics and proteomics, we sought to identify proteins and biologic pathways causally linked to the development of AF in the CKD population. Methods / Approach: We measured 4638 unique plasma proteins using SomaScan v.4.0 in participants (ppts) with CKD and no prior AF from 2 cohorts: Chronic Renal Insufficiency Cohort (CRIC, n=2654) and Atherosclerosis Risk in Communities Cohort (ARIC, n=1326). Associations of individual proteins with incident AF were analyzed using Cox regression after adjustment for demographics, comorbidities, and kidney function. Among proteins independently associated with incident AF in both cohorts, we tested for causality using two-sample Mendelian Randomization (MR). Previously published genome wide association studies (GWAS) were used to identify both protein quantitative loci (cis-pQTL) and summary statistics for incident AF. We then used Ingenuity Pathway Analysis to compare proteins and pathways associated with both incident AF and an increase in left atrial (LA) size across serial echocardiograms in CRIC. Results / Data: Over the 5-year analytic period, incident AF occurred in 150 ppts from CRIC and 140 ppts from ARIC. Eight proteins were independently associated with AF in both cohorts: NT-proBNP, SVEP1, TAGLN, TFF3, WAP4, MMP-12, CILP2 and NELL-1. Of these, 3 were significant in MR analysis (Figure 1): CILP2 and MMP-12 maintain structural integrity of the extracellular matrix in the heart and modulate the fibrotic response; NELL-1 is responsible for cell signaling in kidney disease and cardiovascular development. In addition, leading biologic pathways implicated in both development of AF and increase in LA size included systemic fibrosis (p=1.7x10 -4 for AF and 2.3 x10 -4 for LA); regulation of insulin-like growth factor (p=2.3 x10 -4 for AF and p=4.3 x10 -7 for LA) and extracellular matrix degradation (p=5.5 x10 -4 for AF and p=4.2 x10 -4 for LA). Conclusions: Trans-omics analyses identified 3 proteins causally associated with developing AF in the CKD population. Also, several pathways involved with cardiac remodeling and fibrosis are common to the development of AF and LA remodeling.

Abstract 4138564: Fitbit-Measured Physical Activity Is Inversely Associated With Incident Atrial Fibrillation Among All Of Us Participants

Background: Studies show that moderate to vigorous physical activity (MVPA) reduces atrial fibrillation (AF) risk. However, these studies used subjective questionnaires or short-term (<1 week) accelerometry assessments. Objective: This study investigated the link between MVPA levels and AF incidence using long-term (1-year) accelerometry data from the NIH All of Us Fitbit database. Methods: The study included All of Us participants who agreed to share electronic health record (EHR) and Fitbit data between January 1, 2016 to July 1, 2022. Among participants without an existing diagnosis of AF, the average weekly minutes of MVPA over the first year of Fitbit use was computed. Incident AF events were identified using validated ICD-10 codes in a five-year follow-up period. The risk of incident AF was evaluated using Cox proportional hazards regression models, for both MVPA as a continuous and a categorical variable (<30, 30-150,151-300, and >300 minutes MVPA per week; aligned with WHO guidelines). Covariates included age, sex, race/ethnicity, BMI, smoking status, and diagnoses of hypertension and diabetes. In a subset of participants with whole genome data, we evaluated if the association between MVPA and AF incidence varied by a participant’s AF genetic risk score (GRS) Results: 6086 participants (mean age 50 years, 71% female, 83% White) had EHR and at least 1 year of Fitbit data. Over the 1-year MVPA assessment period, participants had 41±12 weeks of complete data and a median 202 [241] minutes of MVPA per week. 55 participants (0.9%) experienced incident AF in the five-year follow-up period. In adjusted analysis, every additional hour of MVPA was associated with an 11% reduced risk of AF (HR = 0.89 [0.81,0.98], p = 0.02). There was a step-wise reduction in risk of AF by MVPA category with <30 min/week as the reference: 30-150 (HR = 0.62 [0.24,1.6], p = 0.31), 151-300 (HR = 0.40 [0.15,1.07], p = 0.07), and >300 (HR = 0.35 [0.13,0.95], p = 0.04) ( Figure 1 ). These associations also held after adjusting for GRS. Conclusion: Higher amounts of objectively measured MVPA were inversely associated with risk of incident AF, independent of clinical and genetic risk factors.

Abstract 4113263: Serum Metabolomics Adds Predictive Value to Clinical and Polygenic Risk Scores for Atrial Fibrillation: A UK Biobank study of >240,000 Patients

Background: Atrial fibrillation (AF) poses substantial morbidity and mortality burdens globally. It is critical to identify individuals at high-risk for AF to implement both lifestyle modifications and close monitoring for initiation of oral anticoagulants. Currently, risk prediction in AF relies on clinical scores such as CHARGE-AF. Small molecule metabolites are thought to play a role in AF pathogenesis, but the additional predictive value of metabolomics over clinical and genetic risk factors is unknown. Using the UK Biobank (UKBB), we sought to perform this evaluation. Methods: We included all UKBB participants with complete 1 H-NMR metabolite measurements. We excluded participants with prior history of AF or with incomplete AF Polygenic Risk Score (AF-PRS) or CHARGE-AF components. The final cohort included 240,628 patients. In-patient records, primary care notes, and death registries were queried to identify patients who had developed incident AF within 5 years of enrollment. The cohort was divided into a 80/20:Train/Test split. We compared the performance of an Elastic-Net regularized Cox Proportional Hazards (EN-CPH) model trained on CHARGE-AF, AF-PRS, and the full 170 metabolite panel to a CPH model trained only on CHARGE-AF and AF-PRS. Results: Within 5 years, 4,174 (1.7%) patients developed AF. Compared to the control population, the incident AF cases were more likely to be older (62 vs. 56, p<0.001), male (65% vs 45%, p<0.001), and have higher CHARGE-AF and AF-PRS scores (p<0.001). After training the EN-CPH model on CHARGE-AF, AF-PRS, and 170 metabolites, the final model included 8 metabolites on top of CHARGE-AF (HR: 1.28) and AF-PRS (HR: 1.11). After adjusting for CHARGE-AF and AF-PRS, creatinine level was associated with increased risk of AF (HR: 1.01) while linoleic acid level (HR: 0.985) was associated with decreased risk. Furthermore, total cholesterol, esterified cholesterol, free cholesterol, cholesteryl esters in IDL, omega-6 fatty acids, and cholesterol in large LDL were associated with HR 0.993-0.999. The EN-CPH model out-performed the CPH model without metabolomics on the test set (AUC 0.786 vs 0.753, p < 0.001). Conclusions: The addition of metabolomics to clinical and genomic risk scores improves prediction of 5-year incident AF within a general population. This study highlights the significance of the metabolome as an independent prognosticator of AF risk. Further study of the mechanisms by which selected metabolites alter AF risk is needed.

Abstract 4145802: Association between Glucagon-like peptide-1 receptor agonists and risk of Arrhythmias or Heart Failure among patients with Type 2 Diabetes: A Meta-Analysis of 29 Randomized Controlled Trials.

Background: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have shown a reduction in major adverse cardiovascular events (MACE) among patients with type 2 diabetes mellitus (T2DM). However, their effect on reducing the risk of incidence of arrhythmias and heart failure has not been established, and there is very limited literature to date. Objective: We evaluated the effect of GLP-1 RAs on the incidence of arrhythmias and heart failure among patients with T2DM. Methods: We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) that enrolled patients with type 2 diabetes and compared GLP-1 RAs and control groups. PubMed and ClinicalTrials.gov were systematically searched from inspection till May 2024 without any language restrictions. Odds ratios (OR) and 95% confidence intervals (CI) were pooled using a random-effect model. Results: A total of 29 RCTs with 72,868 patients (35,631 in the GLP-1 RA group and 37,237 in the control group) were included in the analysis. Pooled analysis showed that there is no significant association between GLP-1 RAs and incidence of atrial fibrillation (OR, 0.94(95%CI: 0.75-1.18), P=0.60), atrial flutter (OR, 0.87(95%CI: 0.60-1.26), P=0.46), cardiac arrest (OR, 0.79(95%CI: 0.51-1.23), P=0.30), ventricular tachycardia (OR, 1.37(95%CI: 0.90-2.07), P=0.14), and ventricular fibrillation (OR, 0.91 (95%CI: 0.45-1.84), P=0.80) when compared with control group. However, GLP-RAs reduced the incidence of atrioventricular block complete (OR, 0.58 (95%CI: 0.35-0.97), P=0.04), and heart failure (OR, 0.795 (95%CI: 0.634-0.997), P=0.047). Conclusion: This study shows that GLP-1 RAs reduced the incidence of atrioventricular block complete and incidence of heart failure. However, no significant association has been observed for arrhythmias.

Abstract 4138686: Impact of Ejection Fraction on Incidence of Atrial Fibrillation Following Admission for Heart Failure

Introduction: Though the prevalence of atrial fibrillation (AF) is similar amongst heart failure (HF) with reduced, mildly reduced, and preserved ejection fractions, population-level data suggests a modestly increased prevalence in patients with HFpEF compared to those HFrEF. The development of atrial fibrillation is associated with increased risk of stroke, hospitalization, and cardiovascular death in all types of heart failure, though some data suggests morbidity and mortality is worse amongst those with HFpEF. Whether ejection fraction plays a role in development of AF following a HF hospitalization is unclear. Hypothesis: We hypothesized incidence of AF following heart failure hospitalization is increased in patients with preserved ejection fractions. Aim: The goal of this study is to assess the impact of ejection fraction on development of new atrial fibrillation following heart failure exacerbation. Methods: Patients admitted to an academic tertiary care hospital with a primary diagnosis of HF without a previous diagnosis of AF were identified and followed for up to one year for this retrospective study. Demographic, comorbidity, medications, and echocardiography of these patients were obtained from the medical record and analyzed. Consistent with the American Heart Association heart failure guidelines, we defined HFrEF as an EF less than 40%, HFmrEF as an EF between 40-50%, and HFpEF as an EF greater than 50%. This data was analyzed on SPSS using cox-regression and Kaplan-Meier survival analysis. Results: Of the 3,953 patients included in our study, 22.2% had HFrEF, 13.5% had HFmrEF, and 64.3% had HFpEF. At the end of one year 23.5% of those with HFrEF, 20.1% of those with HFmrEF, and 15.9% of those with HFpEF, developed atrial fibrillation. The difference in AF incidence was noted to be statistically significantly lower in HFpEF compared to HFrEF (p<0.001) and HFmrEF (p=0.019). The difference between HFmrEF and HFrEF did not reach statistical significance (p=0.144). Conclusion: In patients without atrial fibrillation, a reduced ejection fraction is associated with an increased incidence of atrial fibrillation one year following a hospitalization for heart failure compared to a preserved ejection fraction.

Abstract 4124709: Accelerometer-Measured Sedentary Behavior and Future Cardiovascular Disease

Background: Current consensus guidelines emphasize the importance of achieving 150 minutes or more of moderate to vigorous physical activity (MVPA) per week to promote cardiovascular health but give little guidance about sedentary behavior. Research Question: Is sedentary behavior associated with cardiovascular (CV) disease in a manner distinct from insufficient physical activity? Aims: Examine associations between accelerometer-measured sedentary behavior with risk of specific CV outcomes, including potential interactions with MVPA. Methods: Using 89,530 individuals providing one week of accelerometer-based physical activity data from the UK Biobank, we fit Cox models adjusted for demographic and lifestyle factors to assess associations between sedentary time (as a spline term) and incident atrial fibrillation (AF), myocardial infarction (MI), heart failure (HF), and CV mortality. We assessed the potential effect of MVPA on these associations by including MVPA as an adjustment variable, as well as performing subgroup analyses stratified at the guideline-recommended MVPA threshold. Results: Among 89,530 individuals (age 62±8 years, 56.4% women) undergoing accelerometry, median sedentary time was 9.4 hours/day (quartile-1: 8.2, quartile-3: 10.6). In multivariable models, using the second quartile (8.2-9.4 hours/day) as a referent, sedentary time in the top quartile (>10.6 hours/day) was associated with greater risk of HF (hazard ratio [HR] 1.45, 95% CI 1.28-1.65), and CV mortality (HR 1.62, 95% CI 1.34-1.96), with evidence of a threshold effect at 10.6 hours/day. Higher sedentary time was also associated with greater risk of incident AF (HR 1.11, 95% CI 1.01-1.21) and MI (HR 1.15, 95% CI 1.00-1.32), with an approximately linear relation. Associations with HF and CV mortality persisted after adjustment for MVPA, as well as among individuals both above and below the guideline-based activity threshold of ≥150 minutes MVPA/week. Conclusions and Relevance: Sedentary behavior is broadly associated with future adverse CV outcomes. For HF and CV mortality, associations appear distinct from insufficient MVPA, and sedentary time in excess of 10.6 hours/day conferred an increased risk.

Abstract 4137717: Atrial Fibrillation in Valvular Heart Disease: Assessing the Impact of Genetics in the UK Biobank

Background: Atrial fibrillation (AF) in valvular heart disease (VHD) is typically linked to pressure or volume overload resulting in atrial remodeling. However, the independent contribution of genetics to AF in VHD beyond abnormal hemodynamics and other risk factors remains unclear. Objective: To study the role of a previously developed Polygenic Risk Score (PRS) for AF in predicting AF across different VHDs in the UK Biobank cohort. Methods: We analyzed UK Biobank data between 2000 and 2022. ICD codes were used to define incident AF and VHD status, including mitral valve (MV) disease [prolapse (MVP), regurgitation (MR) and stenosis (MS)] and aortic (AV) disease [stenosis (AS) and regurgitation (AR)]. Prior AF was excluded. Participants were divided into quintiles based on the PRS: the top quintile was defined as high genetic AF risk, second through fourth as intermediate genetic risk, and bottom quintile as low genetic risk. Results: Among 452841 participants with available PRS, 2238 had at least one VHD (385 MVP, 1058 MR, 81 MS, 421 AR, and 509 AS). AF incidence was 9.9%, 13.6%, and 19% in the low, intermediate and high genetic risk groups respectively, compared to 1.4%, 2.8%, and 5.7% in the general population (all p<0.05) - Figure 1A . Cox regression models adjusted for cardiovascular risk factors showed different genetic effects on AF across VHD types. Censoring patients at death, including valve intervention as a time-dependent variable, and excluding AF within 30 days post-intervention, PRS independently predicted AF in MV disease (hazard ratio [HR] 1.7, p=0.03 for the intermediate risk/mid PRS; HR 2.3, p=0.002 for the high risk PRS), particularly in those with MVP (HR 3.1, p=0.03 for the high PRS). However, in those with AV disease, PRS was not significantly associated with AF (p=0.93 and p=0.07) - Figure 1B. Conclusion: In patients with VHD, AF PRS is significantly associated with an increased risk of developing AF. However, the genetic impact varies across different VHD. In AV disease, there is a minimal genetic contribution, and the elevated AF risk may be predominantly due to pressure or volume overload. In contrast, in MV disease, particularly in MVP, there is a substantial genetic influence on AF risk.

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 4147617: Depression and the Development of Cardiovascular Disease: Insights from All of Us Research Program

Introduction/Background: Depression is recognized as a risk factor for worse outcomes in patients with cardiovascular disease, but there is limited research on whether individuals with depression have an increased incidence of future cardiovascular disease. Research questions/Hypothesis: Do individuals with depression have an increased incidence of cardiovascular disease? Goals/Aims: This study was conducted to evaluate the association between a diagnosis of depression and the risk of developing future cardiovascular events, to determine whether the treatment of depression should be considered as a primary form of cardiovascular disease prevention. Methods/Approach: We conducted a prospective analysis using the “All Of Us” Research Program dataset. Participants who responded to the historical depression status in the “Personal/Family History Survey” and with linked electronic health records data were considered eligible for this study. We used Cox regression models to calculate the incidence of myocardial infarction (MI), stroke, heart failure (HF), and atrial fibrillation (AF) and the hazard ratio (HR) of a diagnosis of depression. Models were adjusted for sex, race, age, and prevalent hypertension, diabetes mellitus, hyperlipidemia, and smoking. The survival analysis of the four outcomes was conducted in parallel. We conducted sensitivity analysis by excluding participants with documentation of prior MI, stroke, HF, and/or AF. Results/Data: 100,030 participants were included in this study, with a mean age of 53.2 (standard deviation of 16.5). 68.4% of participants were female, 10% were Hispanic, 9.6% were Black, and 37.1% had a diagnosis of depression. The median follow up time was 3 years. Compared to participants without depression, participants with depression were at risk of developing MI (aHR 1.22, 95% CI 1.05–1.41), stroke (aHR 1.68, 95% CI 1.06–2.68), HF (aHR 1.28, 95% CI 1.15–1.43), and AF (aHR 1.14, 95% CI 1.02–1.27). In the sensitivity analysis, participants with depression were at risk of developing MI (aHR 1.22, 95% CI 1.03–1.44), stroke (aHR 1.68, 95% CI 1.06–2.68), and HF (aHR 1.31, 95% CI 1.15–1.48) but not AF (aHR 1.12, 95% CI 0.99–1.27). Conclusions: This study indicates that patients with a diagnosis of depression were more likely to develop cardiovascular disease, even if they had no known history of cardiovascular disease. Providers should include the treatment of depression as a part of a holistic approach to cardiovascular disease prevention.

Abstract 4138220: Traditional and HIV-specific Risk Factors Are Associated with Incident Non-valvular Atrial Fibrillation and Atrial Flutter among Underrepresented Racial and Ethnic Minority Groups Living with HIV

Introduction: With effective antiretroviral therapy (ART), HIV can now be managed as a chronic disease. Chronic disease and cardiovascular risk factor management is especially important for underrepresented racial and ethnic minority groups (UREG). Non-valvular atrial fibrillation and atrial flutter (NVAF) have not been adequately studied in UREG with HIV. Research Questions: Among UREG with HIV, what is the incidence of NVAF? What factors are associated with incident NVAF? Aims: To narrow an evidence gap among UREG with HIV by 1) describing the incidence of NVAF and 2) identifying factors associated with incident NVAF. Methods: This is an ancillary study of the Pathways to Cardiovascular Disease Prevention and Impact of Specialty Referral in Underrepresented Racial and Ethnic Minorities with HIV (PATHWAYS) study, a retrospective population-based study of HIV care patterns among UREG with HIV. Patients without a known history of NVAF entered our study cohort at the date of their first documented HIV diagnosis. We computed the cumulative incidence of NVAF over five years of follow-up (mean 3.4, SD 1.6), handling death as a competing risk. Cox regression analysis was used to examine the univariate associations between characteristics at HIV diagnosis and incident NVAF, adjusting for site and date of HIV diagnosis. Results: From 2015-2019, 10,945 UREG meeting entry criteria were identified. On average, patients were 67.1% male, 94.4% Black, and 8.5% Hispanic. Average CHA2DS2VASc score was 0.92 (SD 1.1) and 63.4% were on ART. Cumulative incidence of NVAF at one and five years after HIV diagnosis were 0.48% (95% CI 0.36-0.63) and 2.16% (95% CI 1.85-2.51), respectively. HIV-related factors associated with incident NVAF included baseline CD4 count <200 (HR 1.84, 95% CI 1.20-2.80) and initial ART including protease inhibitors (HR 1.56, 95% CI 1.14-2.13) and/or integrase strand transfer inhibitors (HR 1.47, 95% CI 1.08-1.99). Additional associated factors included older age, Medicare, cardiology visit(s) in prior year, and co-morbid diseases including hypertension, hyperlipidemia, coronary and peripheral artery disease, prior stroke/transient ischemic attack, heart failure, and chronic kidney disease. Conclusions: In a large cohort of UREG living with HIV, both traditional and HIV-specific risk factors are associated with increased risk of incident NVAF. Interventions to mitigate NVAF risk in this population will require interdisciplinary, team-based approaches.

Abstract 4132212: Trends in Atrial Fibrillation or Flutter Related Mortality Among Adults in the United States: Insights from CDC WONDER Database from 1999-2020

Background: Atrial fibrillation or flutter (Afib/AFL) incidence rates continue to rise and are linked to significant mortality, particularly in older populations. Our analysis examines Afib/AFL mortality trends across different demographics and regions in the U.S. from 1999 to 2020, highlighting the importance of understanding these patterns. Aim: To guide preventive measures that alleviate the impact of Afib/AFL and identify high-risk populations and regions, we sought to quantify trends associated with Afib/AFL related mortality in the U.S. Methods: We conducted a comprehensive search of death certificates from 1999-2020 using Centers for Disease Control and Prevention Wide-Ranging OnLine Data for Epidemiologic Research (CDC WONDER) database focusing on Afib/AFL mortality in adults with ICD-10 codes I48. Gender, race, geographical and urban-rural parameters were investigated by calculating annual percent change (APC) and age-adjusted mortality rates (AAMRs) per 100,000 persons using the Joinpoint Regression Program (Joinpoint V 4.9.0.0, National Cancer Institute). Results: A total of 2,581,488 deaths occurred in patients with Afib/AFL from 1999 to 2020. The AAMR displayed an abrupt rise from 2018 to 2020 (APC: 8.51; 95% CI: 4.84-10.47). Men consistently exhibited a higher AAMR (overall AAMR male: 79.4, 95% CI 79.3-79.6; female: 60.8, 95% CI 60.7-60.9). Non-metropolitan areas showed higher AAMRs than metropolitan areas (overall AAMR non-metropolitan areas: 74.9, 95% CI 74.7-75.1; metropolitan: 67.2, 95% CI 67.1-67.2). Disparities were also observed in AAMRs by region with the West region showing the highest mortality rate with a notable rise between 2010 and 2020 (APC: 3.70, 95% CI 3.30-5.37). Non-hispanic (NH) White population showed the highest mortality (overall AAMR: 74.2, 95% CI 74.1-74.3), followed by NH American Indian (AAMR: 50.3), NH Black (AAMR: 45.8), NH Asian (AAMR: 35.0) and Hispanic (AAMR: 37.9) populations. Conclusion: Mortality from Afib/AFL has risen from 1999 to 2020. Men, NH white populations, and residents in non-metropolitan areas and Western U.S. are at higher risk. Targeted interventions and strategic healthcare resource allocation are needed to address these disparities and improve outcomes.

Abstract 4115541: Association of Glucagon-like Peptide 1 Receptor Agonist Use with Incident Atrial Fibrillation

Background: Glucagon-like peptide 1 receptor agonists (GLP-1RAs) have shown efficacy for reducing cardiovascular morbidity and mortality in patients with diabetes mellitus (DM), but conflicting evidence exists regarding their impact on cardiac arrhythmias. Whereas some studies suggested a possible association between GLP-1RA use and arrhythmogenesis, other studies suggested decreased association with atrial fibrillation (AF). Overall, large-scale real-world data evaluating risk of AF in association with GLP-1RAs are lacking. Objective: To compare risk of incident AF after initiation of GLP1-RA vs Dipeptidyl peptidase-4 inhibitors (DPP4i), as active comparators, in patients with DM. Methods: This retrospective propensity score-matched cohort study was conducted within the Veterans Health Administration from fiscal years 2006 to 2021. The study included U.S. veterans aged 35 years or older who initiated either GLP1-RA or DPP4i prescriptions. The primary outcome assessed was a composite outcome of atrial fibrillation (AF), defined as a diagnosis of AF/flutter based on administrative codes or undergoing an AF procedure. Results: Out of 116,235 GLP1-RA users and 217,668 DPP4i users, we propensity score-matched 80,948 pairs, on 88 characteristics, including demographics, comorbidities, vital signs, cardiovascular risk score, healthcare utilization, DM control, laboratory investigation, and medications. Composite outcome of AF was similar in GLP-1RA group (4.1%) and DPP4i group (4.3%); odds ratio (OR) 0.96, 95% confidence interval (CI) 0.92-1.01. Secondary analyses stratified by medication use duration showed no significant differences in composite AF risk (P>0.05). Notably, individuals achieving weight loss of 2%, 5%, or 10% of baseline body weight had significantly lower AF incidence, whereas no significant differences were observed in those with no weight loss or weight gain (OR 0.99, 95% CI 0.91-1.07). Conclusions: Use of GLP1-RA in patients with DM was not associated with a decreased risk of AF when compared with the use of DPP4i. In the subgroup analysis, significantly lower AF risk was seen in the GLP-1 RA group who achieved weight loss vs. DPP4i and this highlights weight loss as a potential modifier of cardiovascular outcomes in DM.

Abstract 4121589: Sex differences in Social Determinants of Health and Adverse Outcomes in Atrial Fibrillation: A UK Biobank Study

Background: Beyond the risk of thromboembolic stroke, people with atrial fibrillation (AF) are substantially burdened with a higher incidence of cardiovascular mortality, even among patients treated with anticoagulants. The reasons behind these outcomes are only partially understood. Social determinants of health (SDOH), strong independent predictors of major adverse cardiovascular events (MACE) in several cardiac diseases, may play a role; however, their impact on AF prognosis and the differences in SDOH by sex have been insufficiently explored. Objective: We investigated the sex differences in the association between SDOH and MACE in patients with AF. Methods: Data from the UK Biobank included participants enrolled from 2006 to 2010. An incident AF patient cohort, free of stroke and MI was created. Seventeen SDOH derived from three domains:: socio-economic status, psychosocial factors, and neighborhood/living environment were identified Cox proportional hazards models were used to evaluate the associations of individual SDOH components with the risk of MACE stratified by sex. Covariates including all variables of the CHA 2 DS 2 -VASc Score (Congestive heart failure, Hypertension, Age, Diabetes, prior stroke or transient ischemic attack, Vascular disease and Sex), current use of antiplatelet therapy or anticoagulation, smoking and body mass index. The primary outcome was a composite of MACE (including stroke, transient ischemic attack and arterial thromboembolic event, MI and cardiovascular mortality) and all-cause mortality. Results: A total of 23,113 participants with AF (mean age, 62.44 ± 5.88 years; female sex 39.7%) were included. The composite outcome occurred in 5,151 (22%) of participants over 10-year follow up. In the multivariate adjusted model, several SDOH were independently associated with an increased risk of adverse outcomes. Males showed a broader range of SDOH that were significantly associated with outcomes, including unfavourable economic factors and low social support. Despite females had fewer significant SDOH, education-related factors and local crime rates were significant predictors of adverse outcomes (Figure 1). Conclusions: Adverse SDOHs are associated with a higher risk of MACE and all-cause mortality in AF, with sex-specific variations. These findings underscore the need of incorporating routinely SDOH assessment into clinical practice to more accurately stratify risk and tailor preventive strategies based on sex-specific data.

ECG-based machine learning model for AF identification in patients with first ischemic stroke.

The recurrence rate of strokes associated with atrial fibrillation (AF) can be substantially reduced through the administration of oral anticoagulants. However, previous studies have not demonstrated a clear benefit from the universal application of oral anticoagulants in patients with embolic stroke of undetermined source. Timely detection of AF remains a challenge in patients with stroke. This study aims to develop a convolutional neural network (CNN) model to accurately identify patients with AF using a 12-lead sinus-rhythm electrocardiogram (ECG) recorded around the time of the first ischemic stroke. Additionally, this study also evaluates the model's ability to predict future occurrence of AF. A CNN model was trained with ECG data from patients at Taipei Veterans General Hospital. External validation was performed on ischemic stroke patients from National Taiwan University Hospital. The model's performance was assessed for detecting AF at the stroke event and predicting future AF occurrences. The model demonstrated an area under curve (AUC) of 0.91 for internal validation and 0.69 for external validation in identifying AF at the stroke event, with sensitivity and negative predictive value both achieving 97%. Kaplan-Meier survival analysis of patients without a prior diagnosis of AF revealed a significant increase in future AF incidence among the high-risk group identified by the model (adjusted hazard ratio: 4.06; 95% confidence interval: 2.74-6.00). The CNN model effectively identifies AF in stroke patients using 12-lead ECGs and predicts future AF events, facilitating early anticoagulation therapy and potentially reducing recurrent stroke risk. Further prospective studies are warranted to confirm these findings.

Accelerometer-Measured Sedentary Behavior and Risk of Future Cardiovascular Disease.

Beyond serving as a marker for insufficient physical activity, sedentary behavior may directly affect future cardiovascular (CV) disease risk. This study sought to examine associations between accelerometer-measured sedentary behavior with risk of specific CV outcomes, including potential relations with moderate to vigorous physical activity (MVPA). Among participants of the UK Biobank prospective cohort study, we fit Cox models adjusted for demographic and lifestyle factors to assess associations between accelerometer-measured daily sedentary time with incident atrial fibrillation (AF), myocardial infarction (MI), heart failure (HF), and CV mortality. We assessed the potential effect of MVPA on associations between sedentary time and CV disease by including MVPA as an adjustment variable, as well as performing subgroup analyses stratified at the guideline-recommended MVPA threshold (ie,≥150min/wk). We then performed compositional analyses to estimate the effects of reallocating sedentary time to other activities. Among 89,530 individuals (age 62 ± 8 years, 56.4% women) undergoing 1week of accelerometry, median sedentary time was 9.4 h/d (Q1-Q3: 8.2-10.6). In multivariable models, using the second quartile (8.2-9.4 h/d) as a referent, sedentary time in the top quartile (>10.6 h/d) was associated with greater risks of HF (HR: 1.45; 95%CI: 1.28-1.65) and CV mortality (HR: 1.62; 95%CI: 1.34-1.96), with an inflection of risk at 10.6 h/d. Higher sedentary time was also associated with greater risks of incident AF (HR: 1.11; 95%CI: 1.01-1.21) and MI (HR: 1.15; 95%CI: 1.00-1.32), with an approximately linear relation. Associations with HF and CV mortality persisted among individuals meeting guideline-recommended MVPA levels. Among individuals with >10.6 h/d of sedentary time, reallocating sedentary behavior to other activities substantially reduced the excess CV risk conferred by sedentary behavior (eg, 30-minute decrease in sedentary time for HF: HR: 0.93; 95%CI: 0.90-0.96), even among individuals meeting guideline-recommended MVPA (HR: 0.93; 95%CI: 0.87-0.99). Sedentary behavior is broadly associated with future adverse CV outcomes, with particularly prominent effects on HF and CV mortality, where risk inflected at approximately 10.6 h/d. Although guideline-adherent MVPA partially mitigates excess risk, optimizing sedentary behavior appears to be important even among physically active individuals.