Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine learning cluster analysis
| Autor: | Simrat Gill, Jinming Duan, Victor Roth Cardoso, Emma Jane Bruce, Andrey D. Barsky, Karina V Bunting, Otilia Tica, Georgios V. Gkoutos, Marcus Flather, Luke T. Slater, Alastair R. Mobley, Saisakul Chernbumroong, Dipak Kotecha, Xiaoxia Wang, John A. Williams, Andrew J.S. Coats, Furqan Aziz, Samantha C. Pendleton, Andreas Karwath |
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| Přispěvatelé: | cardAIc group, The Beta-blockers in Heart Failure Collaborative |
| Rok vydání: | 2021 |
| Předmět: |
Heart Failure
medicine.medical_specialty Ejection fraction Intention-to-treat analysis business.industry Adrenergic beta-Antagonists Atrial fibrillation Articles General Medicine Odds ratio medicine.disease Placebo Machine Learning Text mining Double-Blind Method Internal medicine Heart failure Atrial Fibrillation Cardiology Humans Medicine Sinus rhythm business RC |
| Zdroj: | Lancet Lancet (London, England) |
| ISSN: | 0140-6736 |
| Popis: | Background:\ud Mortality remains unacceptably high in patients with heart failure and reduced left ventricular ejection fraction (LVEF) despite advances in therapeutics. We hypothesised that a novel artificial intelligence approach could better assess multiple and higher-dimension interactions of comorbidities, and define clusters of β-blocker efficacy in patients with sinus rhythm and atrial fibrillation.\ud Methods:\ud Neural network-based variational autoencoders and hierarchical clustering were applied to pooled individual patient data from nine double-blind, randomised, placebo-controlled trials of β blockers. All-cause mortality during median 1·3 years of follow-up was assessed by intention to treat, stratified by electrocardiographic heart rhythm. The number of clusters and dimensions was determined objectively, with results validated using a leave-one-trial-out approach. This study was prospectively registered with ClinicalTrials.gov (NCT00832442) and the PROSPERO database of systematic reviews (CRD42014010012).\ud Findings:\ud 15 659 patients with heart failure and LVEF of less than 50% were included, with median age 65 years (IQR 56–72) and LVEF 27% (IQR 21–33). 3708 (24%) patients were women. In sinus rhythm (n=12 822), most clusters demonstrated a consistent overall mortality benefit from β blockers, with odds ratios (ORs) ranging from 0·54 to 0·74. One cluster in sinus rhythm of older patients with less severe symptoms showed no significant efficacy (OR 0·86, 95% CI 0·67–1·10; p=0·22). In atrial fibrillation (n=2837), four of five clusters were consistent with the overall neutral effect of β blockers versus placebo (OR 0·92, 0·77–1·10; p=0·37). One cluster of younger atrial fibrillation patients at lower mortality risk but similar LVEF to average had a statistically significant reduction in mortality with β blockers (OR 0·57, 0·35–0·93; p=0·023). The robustness and consistency of clustering was confirmed for all models (p |
| Databáze: | OpenAIRE |
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