Prediction model of in-hospital mortality in elderly patients with acute heart failure based on retrospective study

OBJECTIVES: The aim of this study was to develop a clinical risk model that is predictive of in-hospital mortality in elderly patients hospitalized with acute heart failure (AHF). METHODS: 2486 patients who were 60 years and older from intensive care units of Cardiology Department in the hospital were analyzed. Independent risk factors for in-hospital mortality were obtained by binary logistic regression and then used to establish the risk prediction score system (RPSS). The area under the curve (AUC) of receiver operator characteristic and C-statistic test were adopted to assess the performance of RPSS and to compare with previous get with the guidelines–heart failure (GWTG-HF). RESULTS: By binary logistic regression analysis, heart rate (OR: 1.043, 95% CI: 1.030–1.057, P < 0.001), left ventricular ejection fraction (OR: 0.918, 95% CI: 0.833–0.966, P < 0.001), pH value (OR: 0.001, 95% CI: 0.000–0.002, P < 0.001), renal dysfunction (OR: 0.120, 95% CI: 0.066–0.220, P < 0.001) and NT-pro BNP (OR: 3.463, 95% CI: 1.870–6.413, P < 0.001) were independent risk factors of in-hospital mortality for elderly AHF patients. Additionally, RPSS, which was composed of all the above-mentioned parameters, provided a better risk prediction than GWTG-THF (AUC: 0.873 vs. 0.818, P = 0.016). CONCLUSIONS: Our risk prediction model, RPSS, provided a good prediction for in-hospital mortality in elderly patients with AHF.