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A Nomogram to Better Predict the In-Hospital Mortality of Trauma Patients with Sepsis in the Intensive Care Unit

BACKGROUND: Trauma has a high incidence and mortality worldwide, and sepsis is one of the main causes of mortality in trauma patients. Therefore, it is essential to identify the risk factors of in-hospital mortality for trauma patients with sepsis. METHODS: Data were extracted from the Medical Infor...

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Autores principales: Qi, Jing, Xie, Qin, Li, Zhenzhou, Sun, Chuanzheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481405/
https://www.ncbi.nlm.nih.gov/pubmed/36134327
http://dx.doi.org/10.1155/2022/4134138
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author Qi, Jing
Xie, Qin
Li, Zhenzhou
Sun, Chuanzheng
author_facet Qi, Jing
Xie, Qin
Li, Zhenzhou
Sun, Chuanzheng
author_sort Qi, Jing
collection PubMed
description BACKGROUND: Trauma has a high incidence and mortality worldwide, and sepsis is one of the main causes of mortality in trauma patients. Therefore, it is essential to identify the risk factors of in-hospital mortality for trauma patients with sepsis. METHODS: Data were extracted from the Medical Information Mart for Intensive Care III database and divided into a training set and internal validation set, and another Chinese dataset was used as external validation set. Then, risk factors were estimated using univariate and multivariate logistic regression analyses in the training set. Finally, a nomogram was created to predict the probability of in-hospital mortality for trauma patients with sepsis. RESULTS: A total of 503 patients were enrolled in our study (335 in the training set and 168 in the validation set). Multivariate logistic regression analysis revealed that age (1.047 [1.025–1.071]), respiratory rate (1.258 [1.135–1.394]), PTT (1.026 [1.008–1.044]), ventilation (6.703 [1.528–29.408]), and vasopressor use (3.682 [1.502–9.025]) were independent factors associated with in-hospital mortality. The nomogram for trauma-related sepsis predicted in-hospital mortality with AUC values of 0.8939 in the training set, 0.8200 in the internal validation set, and 0.7779 in the external validation set. CONCLUSIONS: The new nomogram has a well predicted value for in-hospital mortality for patients with trauma and sepsis in intensive care units.
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spelling pubmed-94814052022-09-20 A Nomogram to Better Predict the In-Hospital Mortality of Trauma Patients with Sepsis in the Intensive Care Unit Qi, Jing Xie, Qin Li, Zhenzhou Sun, Chuanzheng Int J Clin Pract Research Article BACKGROUND: Trauma has a high incidence and mortality worldwide, and sepsis is one of the main causes of mortality in trauma patients. Therefore, it is essential to identify the risk factors of in-hospital mortality for trauma patients with sepsis. METHODS: Data were extracted from the Medical Information Mart for Intensive Care III database and divided into a training set and internal validation set, and another Chinese dataset was used as external validation set. Then, risk factors were estimated using univariate and multivariate logistic regression analyses in the training set. Finally, a nomogram was created to predict the probability of in-hospital mortality for trauma patients with sepsis. RESULTS: A total of 503 patients were enrolled in our study (335 in the training set and 168 in the validation set). Multivariate logistic regression analysis revealed that age (1.047 [1.025–1.071]), respiratory rate (1.258 [1.135–1.394]), PTT (1.026 [1.008–1.044]), ventilation (6.703 [1.528–29.408]), and vasopressor use (3.682 [1.502–9.025]) were independent factors associated with in-hospital mortality. The nomogram for trauma-related sepsis predicted in-hospital mortality with AUC values of 0.8939 in the training set, 0.8200 in the internal validation set, and 0.7779 in the external validation set. CONCLUSIONS: The new nomogram has a well predicted value for in-hospital mortality for patients with trauma and sepsis in intensive care units. Hindawi 2022-09-09 /pmc/articles/PMC9481405/ /pubmed/36134327 http://dx.doi.org/10.1155/2022/4134138 Text en Copyright © 2022 Jing Qi et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Qi, Jing
Xie, Qin
Li, Zhenzhou
Sun, Chuanzheng
A Nomogram to Better Predict the In-Hospital Mortality of Trauma Patients with Sepsis in the Intensive Care Unit
title A Nomogram to Better Predict the In-Hospital Mortality of Trauma Patients with Sepsis in the Intensive Care Unit
title_full A Nomogram to Better Predict the In-Hospital Mortality of Trauma Patients with Sepsis in the Intensive Care Unit
title_fullStr A Nomogram to Better Predict the In-Hospital Mortality of Trauma Patients with Sepsis in the Intensive Care Unit
title_full_unstemmed A Nomogram to Better Predict the In-Hospital Mortality of Trauma Patients with Sepsis in the Intensive Care Unit
title_short A Nomogram to Better Predict the In-Hospital Mortality of Trauma Patients with Sepsis in the Intensive Care Unit
title_sort nomogram to better predict the in-hospital mortality of trauma patients with sepsis in the intensive care unit
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481405/
https://www.ncbi.nlm.nih.gov/pubmed/36134327
http://dx.doi.org/10.1155/2022/4134138
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