Risk factors for the development of sepsis in patients with cirrhosis in intensive care units

Abstract Sepsis is a serious complication of liver cirrhosis. This study aimed to develop a risk prediction model for sepsis among patients with liver cirrhosis. A total of 3130 patients with liver cirrhosis were enrolled from the Medical Information Mart for Intensive Care IV database, and randomly...

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Main Authors: Yan‐qi Kou, Yu‐ping Yang, Shen‐shen Du, Xiongxiu Liu, Kun He, Wei‐nan Yuan, Biao Nie
Format: Article
Language:English
Published: Wiley 2023-10-01
Series:Clinical and Translational Science
Online Access:https://doi.org/10.1111/cts.13549
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author Yan‐qi Kou
Yu‐ping Yang
Shen‐shen Du
Xiongxiu Liu
Kun He
Wei‐nan Yuan
Biao Nie
author_facet Yan‐qi Kou
Yu‐ping Yang
Shen‐shen Du
Xiongxiu Liu
Kun He
Wei‐nan Yuan
Biao Nie
author_sort Yan‐qi Kou
collection DOAJ
description Abstract Sepsis is a serious complication of liver cirrhosis. This study aimed to develop a risk prediction model for sepsis among patients with liver cirrhosis. A total of 3130 patients with liver cirrhosis were enrolled from the Medical Information Mart for Intensive Care IV database, and randomly assigned into training and validation cohorts in a 7:3 ratio. The least absolute shrinkage and selection operator (LASSO) regression was used to filter variables and select predictor variables. Multivariate logistic regression was used to establish the prediction model. Based on LASSO and multivariate logistic regression, gender, base excess, bicarbonate, white blood cells, potassium, fibrinogen, systolic blood pressure, mechanical ventilation, and vasopressor use were identified as independent risk variables, and then a nomogram was constructed and validated. The consistency index (C‐index), receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA) were used to measure the predictive performance of the nomogram. As a result of the nomogram, good discrimination was achieved, with C‐indexes of 0.814 and 0.828 for the training and validation cohorts, respectively, and an area under the curve of 0.849 in the training cohort and 0.821 in the validation cohort. The calibration curves demonstrated good agreement between the predictions and observations. The DCA curves showed the nomogram had significant clinical value. We developed and validated a risk‐prediction model for sepsis in patients with liver cirrhosis. This model can assist clinicians in the early detection and prevention of sepsis in patients with liver cirrhosis.
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spelling doaj.art-bb0c0d6d74d54659a4ecb57d7696a1f22023-10-18T07:31:17ZengWileyClinical and Translational Science1752-80541752-80622023-10-0116101748175710.1111/cts.13549Risk factors for the development of sepsis in patients with cirrhosis in intensive care unitsYan‐qi Kou0Yu‐ping Yang1Shen‐shen Du2Xiongxiu Liu3Kun He4Wei‐nan Yuan5Biao Nie6Department of Gastroenterology The First Affiliated Hospital of Jinan University Jinan University Guangzhou ChinaDepartment of Gastroenterology The First Affiliated Hospital of Jinan University Jinan University Guangzhou ChinaDepartment of Gastroenterology The First Affiliated Hospital of Jinan University Jinan University Guangzhou ChinaDepartment of Gastroenterology The First Affiliated Hospital of Jinan University Jinan University Guangzhou ChinaDepartment of Gastroenterology The First Affiliated Hospital of Jinan University Jinan University Guangzhou ChinaDepartment of Gastroenterology The First Affiliated Hospital of Jinan University Jinan University Guangzhou ChinaDepartment of Gastroenterology The First Affiliated Hospital of Jinan University Jinan University Guangzhou ChinaAbstract Sepsis is a serious complication of liver cirrhosis. This study aimed to develop a risk prediction model for sepsis among patients with liver cirrhosis. A total of 3130 patients with liver cirrhosis were enrolled from the Medical Information Mart for Intensive Care IV database, and randomly assigned into training and validation cohorts in a 7:3 ratio. The least absolute shrinkage and selection operator (LASSO) regression was used to filter variables and select predictor variables. Multivariate logistic regression was used to establish the prediction model. Based on LASSO and multivariate logistic regression, gender, base excess, bicarbonate, white blood cells, potassium, fibrinogen, systolic blood pressure, mechanical ventilation, and vasopressor use were identified as independent risk variables, and then a nomogram was constructed and validated. The consistency index (C‐index), receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA) were used to measure the predictive performance of the nomogram. As a result of the nomogram, good discrimination was achieved, with C‐indexes of 0.814 and 0.828 for the training and validation cohorts, respectively, and an area under the curve of 0.849 in the training cohort and 0.821 in the validation cohort. The calibration curves demonstrated good agreement between the predictions and observations. The DCA curves showed the nomogram had significant clinical value. We developed and validated a risk‐prediction model for sepsis in patients with liver cirrhosis. This model can assist clinicians in the early detection and prevention of sepsis in patients with liver cirrhosis.https://doi.org/10.1111/cts.13549
spellingShingle Yan‐qi Kou
Yu‐ping Yang
Shen‐shen Du
Xiongxiu Liu
Kun He
Wei‐nan Yuan
Biao Nie
Risk factors for the development of sepsis in patients with cirrhosis in intensive care units
Clinical and Translational Science
title Risk factors for the development of sepsis in patients with cirrhosis in intensive care units
title_full Risk factors for the development of sepsis in patients with cirrhosis in intensive care units
title_fullStr Risk factors for the development of sepsis in patients with cirrhosis in intensive care units
title_full_unstemmed Risk factors for the development of sepsis in patients with cirrhosis in intensive care units
title_short Risk factors for the development of sepsis in patients with cirrhosis in intensive care units
title_sort risk factors for the development of sepsis in patients with cirrhosis in intensive care units
url https://doi.org/10.1111/cts.13549
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