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September 5, 2025ESC Heart FailureOpen Access

Predicting acute decompensated heart failure using circadian markers from heart rate time series

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Circadian metrics showed significant changes in the 21 days leading to acute decompensated heart failure events.
The predictive algorithm achieved 74% sensitivity and 73% specificity in detecting worsening heart failure.
Mesor, amplitude, and acrophase were crucial metrics extracted for prediction, with amplitude being the most important predictor.
These findings indicate the potential for timely intervention using wearable technology for heart failure patients.

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Analysis of heart rate rhythms provides insights for early detection in acute decompensated heart failure, suggesting better outcomes.

Es et al. (2025) studied this question.

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