Dataset Information

Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine learning cluster analysis.

ABSTRACT:

Background

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.

Methods

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).

Findings

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<0·0001 vs random), and cluster membership was externally validated across the nine independent trials.

Interpretation

An artificial intelligence-based clustering approach was able to distinguish prognostic response from β blockers in patients with heart failure and reduced LVEF. This included patients in sinus rhythm with suboptimal efficacy, as well as a cluster of patients with atrial fibrillation where β blockers did reduce mortality.

Funding

Medical Research Council, UK, and EU/EFPIA Innovative Medicines Initiative BigData@Heart.

SUBMITTER: Karwath A

PROVIDER: S-EPMC8542730 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundEven on optimal therapy, many patients with heart failure and atrial fibrillation experience cardiovascular complications. Additional treatments are needed to reduce these events, especially in patients with heart failure and preserved left ventricular ejection fraction.MethodsThis prespecified subanalysis of the randomized EAST-AFNET4 trial (Early Treatment of Atrial Fibrillation for Stroke Prevention Trial) assessed the effect of systematic, early rhythm control therapy (ERC; using antiarrhythmic drugs or catheter ablation) compared with usual care (allowing rhythm control therapy to improve symptoms) on the 2 primary outcomes of the trial and on selected secondary outcomes in patients with heart failure, defined as heart failure symptoms New York Heart Association II to III or left ventricular ejection fraction [LVEF] <50%.ResultsThis analysis included 798 patients (300 [37.6%] female, median age 71.0 [64.0, 76.0] years, 785 with known LVEF). The majority of patients (n=442) had heart failure and preserved LVEF (LVEF≥50%; mean LVEF 61±6.3%), the others had heart failure with midrange ejection fraction (n=211; LVEF 40%-49%; mean LVEF 44 ± 2.9%) or heart failure with reduced ejection fraction (n=132; LVEF<40%; mean LVEF 31±5.5%). Over the 5.1-year median follow-up, the composite primary outcome of cardiovascular death, stroke, or hospitalization for worsening of heart failure or for acute coronary syndrome occurred less often in patients randomly assigned to ERC (94/396; 5.7 per 100 patient-years) compared with patients randomly assigned to usual care (130/402; 7.9 per 100 patient-years; hazard ratio, 0.74 [0.56-0.97]; P=0.03), not altered by heart failure status (interaction P value=0.63). The primary safety outcome (death, stroke, or serious adverse events related to rhythm control therapy) occurred in 71 of 396 (17.9%) patients with heart failure randomly assigned to ERC and in 87 of 402 (21.6%) patients with heart failure randomly assigned to usual care (hazard ratio, 0.85 [0.62-1.17]; P=0.33). LVEF improved in both groups (LVEF change at 2 years: ERC 5.3±11.6%, usual care 4.9±11.6%, P=0.43). ERC also improved the composite outcome of death or hospitalization for worsening of heart failure.ConclusionsRhythm control therapy conveys clinical benefit when initiated within 1 year of diagnosing atrial fibrillation in patients with signs or symptoms of heart failure. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01288352. URL: http://www.controlled-trials.com; Unique identifier: ISRCTN04708680. URL: https://www.clinicaltrialsregister.eu; Unique identifier: 2010-021258-20.

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