Prediction of Incident Atrial Fibrillation and Association With Outcomes Using Routine Electronic Health Records in a Western Pacific Population.

Risk-Guided Screening for Atrial Fibrillation Using Electronic Health Records

The EHR-based machine learning model, FIND-AF 2.0, identifies a high-risk subpopulation for AF diagnosis among patients at elevated risk of stroke and could enable scalable, EHR-driven, risk-guided AF screening.

Prediabetes and the risk of atrial fibrillation and heart failure: a propensity-matched analysis in a real-world cohort.

Investigating the Association Between Atrial Fibrillation and Out-of-Hospital Cardiac Arrest: A Danish Nationwide Matched Cohort Study.

BACKGROUND Atrial fibrillation (AF) is an impending global epidemic, and out-of-hospital cardiac arrest (OHCA) is associated with high mortality. Although emerging evidence links AF with OHCA, research has been challenged by shared risk factors, especially ischemic heart disease and heart failure. OBJECTIVES This study aimed to investigate the association between AF and OHCA in light of risk factors for ischemic heart disease and heart failure. METHODS This was a Danish, nationwide matched cohort study using the Danish Cardiac Arrest Registry (June 1, 2001, to December 31, 2022) in individuals aged 18 to 85 years. Exposure was an AF diagnosis, and outcomes were OHCA and all-cause mortality. A 1:4 matching of AF patients with non-AF patients upon sex, birth year, ischemic heart disease, heart failure, diabetes, cancer, hypertrophic cardiomyopathy, dilated cardiomyopathy, and statin usage was performed. Multivariable Cox regression models were used and results presented as cumulative incidences from time of AF diagnosis/matching and HRs of OHCA and all-cause mortality. RESULTS The study included 6.47 million individuals, of whom 368,639 had AF. A total of 309,010 patients with AF (only newly diagnosed in the time period) were matched to 1,236,040 non-AF patients. Adjusted HRs of OHCA and all-cause mortality were higher in AF patients vs non-AF patients (1.66 [95% CI: 1.62-1.70] and 1.79 [95% CI: 1.78-1.81], respectively). CONCLUSIONS Findings suggest that AF remains a risk factor for OHCA, even after adjustments for ischemic heart disease and heart failure. Future studies should explore subsets of patients with AF at highest risk of OHCA to tailor preventive efforts toward this patient group.

Atrial Fibrillation and Documented Heart Failure in Patients Hospitalized with COVID-19: A Secondary Analysis of a Single-Centre Cohort from Western Romania

Background/Objectives: Atrial fibrillation (AF) and heart failure (HF) frequently coexist, but later-pandemic data from Eastern Europe are limited. We evaluated their documented coexistence in patients hospitalized with COVID-19; the study was not designed to determine whether SARS-CoV-2 modifies the established AF–HF relationship. Methods: We retrospectively analysed 395 adults admitted with RT-PCR-confirmed SARS-CoV-2 infection between 1 September 2022 and 31 December 2024. AF was identified from the admission record, while HF was determined by an audited, rule-based review of cardiovascular free-text entries. A modified Poisson model with robust variance was the primary analysis and estimated adjusted prevalence ratios (aPRs) after adjustment for age, sex, body mass index, hypertension, ischaemic heart disease, pre-existing type 2 diabetes, chronic kidney disease, chronic obstructive pulmonary disease, smoking, and prior ischaemic stroke. Logistic regression and a restrictive NYHA-coded HF definition were sensitivity analyses. Results: AF was documented in 68 patients (17.2%), HF in 106 (26.8%), and both conditions in 26 (6.6%). HF prevalence was 38.2% among patients with AF and 24.5% among those without AF. AF was associated with documented HF in the primary model (aPR 1.51, 95% confidence interval 1.06–2.16; p = 0.022); age was also associated with HF (aPR 1.02 per year, 95% confidence interval 1.01–1.04; p = 0.010). Results were similar with the restrictive HF definition (aPR 1.54, 95% confidence interval 1.07–2.23) and logistic regression (adjusted odds ratio 1.89, 95% confidence interval 1.06–3.37). Exploratory mortality estimates were imprecise and were not used for prognostic inference. Conclusions: AF identified a subgroup with a higher prevalence of documented HF within this hospitalized COVID-19 cohort. The findings are best interpreted as evidence of cardiovascular and multimorbidity complexity, not as proof of a COVID-specific, temporal, or causal AF–HF effect.

Analysis of accuracy of risk assessment tools for predicting new-onset atrial fibrillation in ST-elevation myocardial nfarction with percutaneous coronaty intervention (a systematic review)

The occurrence of NOAF was associated with increased in-hospital mortality, which was 2–3 times higher in patients with arrhythmia, and most NOAF prediction models developed specifically in STEMI cohorts undergoing PCI demonstrated higher discriminative ability.

Predictive value of acute atrial fibrillation for short-term mortality after ischemic stroke

Background Atrial fibrillation (AF) is an important risk factor for ischemic stroke. However, the prognostic impact of acute atrial fibrillation (AAF) at the onset of acute ischemic stroke (AIS) remains unclear. Methods This retrospective study categorized 417 patients with AIS into the AAF (n = 72), other AF (n = 142), and non-AF (n = 203) groups. Multivariate logistic regression analysis of associations with 30-day all-cause mortality and severe early neurological deficit (7-day NIHSS ≥16). Results The AAF group demonstrated significantly worse outcomes than the other AF and non-AF groups. In the multivariable analysis, AAF was identified as an independent risk predictor for severe 7-day neurological deficit [odds ratio (OR): 10.09; 95% CI: 3.87−27.36; P < 0.001] and all-cause mortality within 30 days (OR: 4.11; 95% CI: 2.28−7.43; P < 0.001). Conclusions AAF at the onset of AIS is an independent risk predictor for early neurological deterioration and short-term mortality, establishing it as a crucial prognostic indicator that warrants vigilant management.