A novel nomogram to predict all-cause readmission or death risk in Chinese elderly patients with heart failure

Abstract

Aims: Elderly patients with heart failure (HF) are associated with frequent all-cause readmission or death. The present study sought to develop an accurate and easy-to-use model to predict all-cause readmission or death risk in Chinese elderly patients with HF. Methods and results: This was a prospective cohort study in patients with HF aged 65 or older. Demographic, co-morbidity, laboratory, and medication data were collected. A Cox regression model was used to identify factors for the prediction of readmission or death at 30 days and 1 year. A nomogram was developed with bootstrap validation. Of the included 854 patients, the cumulative all-cause readmission and mortality rates were 10.5% and 11.6% at 30 days and 34.9% and 19.7% at 1 year, respectively. The independent risk factors associated with both 30 day and 1 year readmission or death were older age, stroke, diastolic blood pressure < 60 mmHg, body mass index ≤ 18.5 kg/m2, lower estimated glomerular filtration rate, and BNP > 400 pg/mL (all P < 0.05). Anaemia, abnormal neutrophils, and admission without angiotensin-converting enzyme inhibitors/angiotensin receptor blockers were the specific independent risk factors of 30 day all-cause readmission or death (all P < 0.05), whereas serum sodium ≤ 140 mmol/L and admission without beta-blockers were the specific independent risk factors of 1 year all-cause readmission or death (all P < 0.05). The C-index of the 30 day and 1 year diagnosis prediction model was 0.778 [95% confidence interval (CI) 0.693–0.862] and 0.738 (95% CI 0.640–0.836), respectively. Conclusions: We developed accurate and easy-to-use nomograms to predict all-cause readmission or death in Chinese elderly patients with HF. The nomograms will assist in reducing the all-cause readmission and mortality rates.