A novel web-based calculator to predict 30-day all-cause in-hospital mortality for 7,202 elderly patients with heart failure in ICUs: a multicenter retrospective cohort study in the United States

• Published in: Frontiers in medicine Vol. 10; p. 1237229
• Main Authors: Wang, Zhongjian, Huang, Jian, Zhang, Yang, Liu, Xiaozhu, Shu, Tingting, Duan, Minjie, Wang, Haolin, Yin, Chengliang, Cao, Junyi
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 15.09.2023
• Subjects: big data; calculator; death; elderly; heart failure; Medicine; web-based
• ISSN: 2296-858X; 2296-858X
• DOI: 10.3389/fmed.2023.1237229

Background and aims Heart failure (HF) is a significant cause of in-hospital mortality, especially for the elderly admitted to intensive care units (ICUs). This study aimed to develop a web-based calculator to predict 30-day in-hospital mortality for elderly patients with HF in the ICU and found a relationship between risk factors and the predicted probability of death. Methods and results Data ( N = 4450) from the MIMIC-III/IV database were used for model training and internal testing. Data ( N = 2,752) from the eICU-CRD database were used for external validation. The Brier score and area under the curve (AUC) were employed for the assessment of the proposed nomogram. Restrictive cubic splines (RCSs) found the cutoff values of variables. The smooth curve showed the relationship between the variables and the predicted probability of death. A total of 7,202 elderly patients with HF were included in the study, of which 1,212 died. Multivariate logistic regression analysis showed that 30-day mortality of HF patients in ICU was significantly associated with heart rate (HR), 24-h urine output (24h UOP), serum calcium, blood urea nitrogen (BUN), NT-proBNP, SpO 2 , systolic blood pressure (SBP), and temperature ( P < 0.01). The AUC and Brier score of the nomogram were 0.71 (0.67, 0.75) and 0.12 (0.11, 0.15) in the testing set and 0.73 (0.70, 0.75), 0.13 (0.12, 0.15), 0.65 (0.62, 0.68), and 0.13 (0.12, 0.13) in the external validation set, respectively. The RCS plot showed that the cutoff values of variables were HR of 96 bmp, 24h UOP of 1.2 L, serum calcium of 8.7 mg/dL, BUN of 30 mg/dL, NT-pro-BNP of 5121 pg/mL, SpO 2 of 93%, SBP of 137 mmHg, and a temperature of 36.4°C. Conclusion Decreased temperature, decreased SpO 2 , decreased 24h UOP, increased NT-proBNP, increased serum BUN, increased or decreased SBP, fast HR, and increased or decreased serum calcium increase the predicted probability of death. The web-based nomogram developed in this study showed good performance in predicting 30-day in-hospital mortality for elderly HF patients in the ICU.