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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.
Wang, Zhongjian; Huang, Jian; Zhang, Yang; Liu, Xiaozhu; Shu, Tingting; Duan, Minjie; Wang, Haolin; Yin, Chengliang; Cao, Junyi.
Afiliação
  • Wang Z; Artificial Intelligence Laboratory, Pharnexcloud Digital Technology (Chengdu) Co. Ltd., Chengdu, China.
  • Huang J; Graduate School, Guangxi University of Chinese Medicine, Nanning, China.
  • Zhang Y; College of Medical Informatics, Chongqing Medical University, Chongqing, China.
  • Liu X; Medical Data Science Academy, Chongqing Medical University, Chongqing, China.
  • Shu T; College of Medical Informatics, Chongqing Medical University, Chongqing, China.
  • Duan M; Department of Cardiology, Daping Hospital, The Third Military Medical University (Army Medical University), Chongqing, China.
  • Wang H; College of Medical Informatics, Chongqing Medical University, Chongqing, China.
  • Yin C; Medical Data Science Academy, Chongqing Medical University, Chongqing, China.
  • Cao J; College of Medical Informatics, Chongqing Medical University, Chongqing, China.
Front Med (Lausanne) ; 10: 1237229, 2023.
Article em En | MEDLINE | ID: mdl-37780569
ABSTRACT
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, SpO2, 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, SpO2 of 93%, SBP of 137 mmHg, and a temperature of 36.4°C.

Conclusion:

Decreased temperature, decreased SpO2, 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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article