Derivation of an electronic frailty index for predicting short-term mortality in heart failure: a machine learning approach.

ABSTRACT:

Aims

Frailty may be found in heart failure patients especially in the elderly and is associated with a poor prognosis. However, assessment of frailty status is time-consuming, and the electronic frailty indices developed using health records have served as useful surrogates. We hypothesized that an electronic frailty index developed using machine learning can improve short-term mortality prediction in patients with heart failure.

Methods and results

This was a retrospective observational study that included patients admitted to nine public hospitals for heart failure from Hong Kong between 2013 and 2017. Age, sex, variables in the modified frailty index, Deyo's Charlson co-morbidity index (≥2), neutrophil-to-lymphocyte ratio (NLR), and prognostic nutritional index at baselin

SUBMITTER: Ju C 

PROVIDER: S-EPMC8318426 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature