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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

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...

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Autores principales: Wang, Zhongjian, Huang, Jian, Zhang, Yang, Liu, Xiaozhu, Shu, Tingting, Duan, Minjie, Wang, Haolin, Yin, Chengliang, Cao, Junyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10541310/
https://www.ncbi.nlm.nih.gov/pubmed/37780569
http://dx.doi.org/10.3389/fmed.2023.1237229
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author Wang, Zhongjian
Huang, Jian
Zhang, Yang
Liu, Xiaozhu
Shu, Tingting
Duan, Minjie
Wang, Haolin
Yin, Chengliang
Cao, Junyi
author_facet Wang, Zhongjian
Huang, Jian
Zhang, Yang
Liu, Xiaozhu
Shu, Tingting
Duan, Minjie
Wang, Haolin
Yin, Chengliang
Cao, Junyi
author_sort Wang, Zhongjian
collection PubMed
description 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.
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spelling pubmed-105413102023-10-01 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 Front Med (Lausanne) Medicine 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. Frontiers Media S.A. 2023-09-15 /pmc/articles/PMC10541310/ /pubmed/37780569 http://dx.doi.org/10.3389/fmed.2023.1237229 Text en Copyright © 2023 Wang, Huang, Zhang, Liu, Shu, Duan, Wang, Yin and Cao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Wang, Zhongjian
Huang, Jian
Zhang, Yang
Liu, Xiaozhu
Shu, Tingting
Duan, Minjie
Wang, Haolin
Yin, Chengliang
Cao, Junyi
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10541310/
https://www.ncbi.nlm.nih.gov/pubmed/37780569
http://dx.doi.org/10.3389/fmed.2023.1237229
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