ECG AI Predicts AF Recurrence Risk 03/21/26

Welcome to Cardiology Today – Recorded March 21, 2026. This episode summarizes 5 key cardiology studies on topics like premature menopause and sodium-glucose cotransporter two inhibitors. Key takeaway: ECG AI Predicts AF Recurrence Risk. Article Links: Article 1: Premature Menopause and Lifetime Risk of Coronary Heart Disease. (JAMA cardiology) Article 2: Life expectancy and determinants of relative survival following surgical aortic valve replacement for aortic stenosis. (Heart (British Cardiac Society)) Article 3: Real-world evidence with dapagliflozin in heart failure with reduced ejection fraction in Central Eastern Europe and the Baltic region (EVOLUTION-HF CEE-BA Study). (ESC heart failure) Article 4: Comparative diagnostic performance of machine learning models and traditional scores for HFpEF in older adults. (European journal of heart failure) Article 5: Predicting Recurrence and Outcomes After Stressor-Associated Atrial Fibrillation Using ECG-Based Deep Learning. (Journal of the American Heart Association) Full episode page: https://podcast.explainheart.com/podcast/ecg-ai-predicts-af-recurrence-risk-03-21-26/ Featured Articles Article 1: Premature Menopause and Lifetime Risk of Coronary Heart Disease. Journal: JAMA cardiology PubMed Link: https://pubmed.ncbi.nlm.nih.gov/41848694 Summary: The study found that premature onset of menopause is associated with an increased short-term risk of coronary heart disease. Researchers calculated lifetime risk estimates of incident coronary heart disease and estimated years lived free of and with coronary heart disease. These estimates were stratified by premature menopause status and self-identified race across 163600 person-years of follow-up. The findings highlight the critical long-term cardiovascular implications of premature menopause across diverse populations. Article 2: Life expectancy and determinants of relative survival following surgical aortic valve replacement for aortic stenosis. Journal: Heart (British Cardiac Society) PubMed Link: https://pubmed.ncbi.nlm.nih.gov/41850785 Summary: Surgical aortic valve replacement improves survival in patients with severe, symptomatic aortic stenosis. This study evaluated the long-term relative survival of patients after surgical aortic valve replacement compared with the general population. Researchers identified specific predictors of any residual survival discrepancies among 1287 patients who received surgical aortic valve replacement for moderate or greater aortic stenosis. These findings provide clarity on life expectancy post-surgical aortic valve replacement and factors influencing it. Article 3: Real-world evidence with dapagliflozin in heart failure with reduced ejection fraction in Central Eastern Europe and the Baltic region (EVOLUTION-HF CEE-BA Study). Journal: ESC heart failure PubMed Link: https://pubmed.ncbi.nlm.nih.gov/41858299 Summary: F. C.E.E.-B.A. Study). Sodium-glucose cotransporter two inhibitors are currently recommended as one of the four pillars of treatment in Heart Failure with Reduced Ejection Fraction. This study characterized the real-world patient population initiated on dapagliflozin for Heart Failure with Reduced Ejection Fraction in clinical practice. The data came from nine countries across Central Eastern Europe and the Baltic Area, providing crucial real-world insights following dapagliflozin’s 2020 approval. The findings offer valuable information on therapeutic adoption and patient profiles in diverse European regions. Article 4: Comparative diagnostic performance of machine learning models and traditional scores for HFpEF in older adults. Journal: European journal of heart failure PubMed Link: https://pubmed.ncbi.nlm.nih.gov/41859834 Summary: F. pEF in older adults. This study evaluated the diagnostic performance of four supervised machine learning algorithms for identifying Heart Failure with Preserved Ejection Fraction in individuals aged 60 to 80 years. The study found that machine learning approaches improved diagnostic accuracy when compared to traditional Heart Failure with Preserved Ejection Fraction scores. This demonstrates the superior utility of advanced computational methods in diagnosing this challenging condition in older adult populations. Article 5: Predicting Recurrence and Outcomes After Stressor-Associated Atrial Fibrillation Using ECG-Based Deep Learning. Journal: Journal of the American Heart Association PubMed Link: https://pubmed.ncbi.nlm.nih.gov/41859908 Summary: The study retrospectively analyzed patients with stressor-associated atrial fibrillation to predict recurrence and outcomes. It found that artificial intelligence-enabled models using the 12-lead electrocardiogram could accurately estimate the risk of recurrence. These models proved valuable in identifying individuals at highest risk for atrial fibrillation recurrence, which traditional clinical factors have shown limited utility in achieving. This represents a significant advancement in guiding management for patients with stressor-associated atrial fibrillation. Transcript Today’s date is March 21, 2026. Welcome to Cardiology Today. Here are the latest research findings. Article number one. Premature Menopause and Lifetime Risk of Coronary Heart Disease. The study found that premature onset of menopause is associated with an increased short-term risk of coronary heart disease. Researchers calculated lifetime risk estimates of incident coronary heart disease and estimated years lived free of and with coronary heart disease. These estimates were stratified by premature menopause status and self-identified race across 163600 person-years of follow-up. The findings highlight the critical long-term cardiovascular implications of premature menopause across diverse populations. Article number two. Life expectancy and determinants of relative survival following surgical aortic valve replacement for aortic stenosis. Surgical aortic valve replacement improves survival in patients with severe, symptomatic aortic stenosis. This study evaluated the long-term relative survival of patients after surgical aortic valve replacement compared with the general population. Researchers identified specific predictors of any residual survival discrepancies among 1287 patients who received surgical aortic valve replacement for moderate or greater aortic stenosis. These findings provide clarity on life expectancy post-surgical aortic valve replacement and factors influencing it. Article number three. Real-world evidence with dapagliflozin in heart failure with reduced ejection fraction in Central Eastern Europe and the Baltic region (EVOLUTION-H. F. C.E.E.-B.A. Study). Sodium-glucose cotransporter two inhibitors are currently recommended as one of the four pillars of treatment in Heart Failure with Reduced Ejection Fraction. This study characterized the real-world patient population initiated on dapagliflozin for Heart Failure with Reduced Ejection Fraction in clinical practice. The data came from nine countries across Central Eastern Europe and the Baltic Area, providing crucial real-world insights following dapagliflozin’s 2020 approval. The findings offer valuable information on therapeutic adoption and patient profiles in diverse European regions. Article number four. Comparative diagnostic performance of machine learning models and traditional scores for H. F. pEF in older adults. This study evaluated the diagnostic performance of four supervised machine learning algorithms for identifying Heart Failure with Preserved Ejection Fraction in individuals aged 60 to 80 years. The study found that machine learning approaches improved diagnostic accuracy when compared to traditional Heart Failure with Preserved Ejection Fraction scores. This demonstrates the superior utility of advanced computational methods in diagnosing this challenging condition in older adult populations. Article number five. Predicting Recurrence and Outcomes After Stressor-Associated Atrial Fibrillation Using E.C.G.-Based Deep Learning. The study retrospectively analyzed patients with stressor-associated atrial fibrillation to predict recurrence and outcomes. It found that artificial intelligence-enabled models using the 12-lead electrocardiogram could accurately estimate the risk of recurrence. These models proved valuable in identifying individuals at highest risk for atrial fibrillation recurrence, which traditional clinical factors have shown limited utility in achieving. This represents a significant advancement in guiding management for patients with stressor-associated atrial fibrillation. Thank you for listening. Don’t forget to subscribe. Keywords premature menopause, sodium-glucose cotransporter two inhibitors, older adults, women’s health, survival predictors, deep learning, population cohort, real-world evidence, heart failure with preserved ejection fraction, treatment patterns, stressor-associated atrial fibrillation, lifetime risk, aortic stenosis, diagnostic scores, electrocardiogram, heart failure with reduced ejection fraction, diagnostic accuracy, life expectancy, coronary heart disease, relative survival, artificial intelligence, machine learning, atrial fibrillation recurrence, dapagliflozin, surgical aortic valve replacement. About Concise summaries of cardiovascular research for professionals. Subscribe • Share • FollowThe post ECG AI Predicts AF Recurrence Risk 03/21/26 first appeared on Cardiology Today.