Beta blockers may reduce mortality in cluster of young patients with AF and HF: Lancet
A statistically significant reduction in mortality is associated with beta blockers in a cluster of younger atrial fibrillation patients at lower mortality risk but similar LVEF to average, according to a study published in The Lancet.
Mortality remains unacceptably high in patients with heart failure and reduced left ventricular ejection fraction (LVEF) despite advances in therapeutics.
A group of researchers from the U.K 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.
The researchers applied neural network-based variational autoencoders and hierarchical clustering 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 were determined objectively, with results validated using a leave-one-trial-out approach.
The results of the study are as follows:
- 15 659 patients with heart failure and LVEF of less than 50% were included, with median age 65 years and LVEF 27%, 3708 (24%) patients were women. In sinus rhythm, most clusters demonstrated a consistent overall mortality benefit from β blockers.
- One cluster in sinus rhythm of older patients with less severe symptoms showed no significant efficacy.
- In atrial fibrillation, four of five clusters were consistent with the overall neutral effect of β blockers versus placebo.
- 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.
- The robustness and consistency of clustering was confirmed for all models and cluster membership was externally validated across the nine independent trials.
Thus, the researchers concluded that an artificial intelligence-based clustering approach was able to distinguish the 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.
Reference:
Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine-learning cluster analysis by Karwath A et. al published in The Lancet.
DOI: https://doi.org/10.1016/S0140-6736(21)01638-X
