Machine learning-based gait analysis to predict clinical frailty scale in elderly patients with heart failure.

Although frailty assessment is recommended for guiding treatment strategies and outcome prediction in elderly patients with heart failure (HF), most frailty scales are subjective, and the scores vary among raters. We sought to develop a machine learning-based automatic rating method/system/model of the clinical frailty scale (CFS) for patients with HF. We prospectively examined 417 elderly (≥75 years) with symptomatic chronic HF patients from 7 centres between January 2019 and October 2023. The patients were divided into derivation ( Machine learning-based algorithms of automatically CFS rating are feasible, and the predicted CFS is associated with the risk of all-cause death in elderly patients with HF.

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© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.

Déclaration de conflit d'intérêts

Conflict of interest: none declared.