Models to predict prognosis in older patients with heart failure complicated by pre-frailty and frailty: a pilot prospective cohort study.

Abstract

There are no clinical prediction models to predict the prognosis of pre-frailty or frailty in patients with heart failure. We aimed to develop prediction models for the prognosis of pre-frailty and frailty in older patients with heart failure using the classification and regression tree (CART) method; we then tested the predictive accuracies of the developed models. Patients with pre-frailty or frailty at admission were divided into improved and non-improved groups. The CART method was used to establish two models: A, which predicted the presence or absence of pre-frailty improvement during hospitalisation; and B, which predicted the presence or absence of frailty improvement during hospitalisation. Patients with heart failure complicated by pre-frailty (n=28) or frailty (n=156) were included. In model A, the accuracy of predicting pre-frailty improvement was high; the best predictor was single-leg standing time at admission, followed by left ventricular ejection fraction at admission. In model B, the accuracy of predicting frailty improvement was moderate; the best predictor was hand grip strength at admission, followed by estimated glomerular filtration rate at admission, haemoglobin level at admission, and change in single-leg standing time during hospitalisation. The areas under the receiver operating characteristic curves of the CART models were 0.96 and 0.84 in models A and B, respectively. Although conditions at admission may predict the improvement of pre-frailty and frailty during hospitalisation, cardiac rehabilitation that improves single-leg standing time may help to improve frailty, particularly when conditions at admission are poor.