aceMultivariate Machine Learning Model for Long-Term Risk Prediction of Acute Coronary Syndrome in Patients With Heart Failure With Preserved Ejection Fraction and Obstructive Sleep Apnea
Background Heart failure with preserved ejection fraction is a heterogeneous syndrome, and comorbid obstructive sleep apnea further increases the risk of acute coronary syndrome. However, effective tools for long-term acute coronary syndrome risk stratification in this population remain limited. This study aimed to develop and externally validate a machine learning-based prognostic model for predicting acute coronary syndrome risk at multiple time points in patients with heart failure with preserved ejection fra…
Researchers developed and externally validated a machine learning model to predict acute coronary syndrome risk in patients with HFpEF and sleep apnea, filling a gap in risk tools.
Evidence
- Peer-reviewedJournal of the American Heart Association2026-09-18
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Truvace Impact Record TRV-2026-1139, v2: “Multivariate Machine Learning Model for Long-Term Risk Prediction of Acute Coronary Syndrome in Patients With Heart Failure With Preserved Ejection Fraction and Obstructive Sleep Apnea.” Truvace, 2026-10-26. /record/TRV-2026-1139 (accessed at citation time). sha256 2e2b3578b32bb398…
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