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

The Lancet Sep 02, 2021

Karwath A, Bunting KV, Gill SK, et al. - In patients with heart failure and reduced left ventricular ejection fraction (LVEF), prognostic response from β blockers can be distinguished using an artificial intelligence-based clustering approach. Patients in sinus rhythm with suboptimal efficacy as well as a cluster of patients with atrial fibrillation where β blockers did lower mortality were included in this.

  • On pooled individual patient data from nine double-blind, randomized, placebo-controlled trials of β blockers, researchers applied neural network-based variational autoencoders and hierarchical clustering.

  • Included were 15,659 patients with heart failure and LVEF of less than 50%.

  • In sinus rhythm (n = 12,822), β blockers were consistently linked with overall mortality benefit in most clusters; no significant efficacy was identified in one cluster of older patients with less severe symptoms.

  • In atrial fibrillation (n = 2,837), overall neutral effect of β blockers vs placebo was consistent in four of five clusters.

  • A statistically significant reduction in mortality was observed with β blockers in one cluster of younger atrial fibrillation patients at lower mortality risk but similar LVEF to average.

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