Development and Validation of a Nomogram for the Prediction of Hospital Mortality of Patients With Encephalopathy Caused by Microbial Infection: A Retrospective Cohort Study

BackgroundHospital mortality is high for patients with encephalopathy caused by microbial infection. Microbial infections often induce sepsis. The damage to the central nervous system (CNS) is defined as sepsis-associated encephalopathy (SAE). However, the relationship between pathogenic microorgani...

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Autores principales:	Lina Zhao, Yun Li, Yunying Wang, Qian Gao, Zengzheng Ge, Xibo Sun, Yi Li
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	sepsis associated encephalopathy prognosis hospital mortality nomogram microbial infection Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/d8b54dcdce20403e86853cf154c8655a
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spelling	oai:doaj.org-article:d8b54dcdce20403e86853cf154c8655a2021-11-04T13:37:00ZDevelopment and Validation of a Nomogram for the Prediction of Hospital Mortality of Patients With Encephalopathy Caused by Microbial Infection: A Retrospective Cohort Study1664-302X10.3389/fmicb.2021.737066https://doaj.org/article/d8b54dcdce20403e86853cf154c8655a2021-08-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fmicb.2021.737066/fullhttps://doaj.org/toc/1664-302XBackgroundHospital mortality is high for patients with encephalopathy caused by microbial infection. Microbial infections often induce sepsis. The damage to the central nervous system (CNS) is defined as sepsis-associated encephalopathy (SAE). However, the relationship between pathogenic microorganisms and the prognosis of SAE patients is still unclear, especially gut microbiota, and there is no clinical tool to predict hospital mortality for SAE patients. The study aimed to explore the relationship between pathogenic microorganisms and the hospital mortality of SAE patients and develop a nomogram for the prediction of hospital mortality in SAE patients.MethodsThe study is a retrospective cohort study. The lasso regression model was used for data dimension reduction and feature selection. Model of hospital mortality of SAE patients was developed by multivariable Cox regression analysis. Calibration and discrimination were used to assess the performance of the nomogram. Decision curve analysis (DCA) to evaluate the clinical utility of the model.ResultsUnfortunately, the results of our study did not find intestinal infection and microorganisms of the gastrointestinal (such as: Escherichia coli) that are related to the prognosis of SAE. Lasso regression and multivariate Cox regression indicated that factors including respiratory failure, lactate, international normalized ratio (INR), albumin, SpO2, temperature, and renal replacement therapy were significantly correlated with hospital mortality. The AUC of 0.812 under the nomogram was more than that of the Simplified Acute Physiology Score (0.745), indicating excellent discrimination. DCA demonstrated that using the nomogram or including the prognostic signature score status was better than without the nomogram or using the SAPS II at predicting hospital mortality.ConclusionThe prognosis of SAE patients has nothing to do with intestinal and microbial infections. We developed a nomogram that predicts hospital mortality in patients with SAE according to clinical data. The nomogram exhibited excellent discrimination and calibration capacity, favoring its clinical utility.Lina ZhaoLina ZhaoYun LiYunying WangQian GaoZengzheng GeXibo SunYi LiFrontiers Media S.A.articlesepsis associated encephalopathyprognosishospital mortalitynomogrammicrobial infectionMicrobiologyQR1-502ENFrontiers in Microbiology, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	sepsis associated encephalopathy prognosis hospital mortality nomogram microbial infection Microbiology QR1-502
spellingShingle	sepsis associated encephalopathy prognosis hospital mortality nomogram microbial infection Microbiology QR1-502 Lina Zhao Lina Zhao Yun Li Yunying Wang Qian Gao Zengzheng Ge Xibo Sun Yi Li Development and Validation of a Nomogram for the Prediction of Hospital Mortality of Patients With Encephalopathy Caused by Microbial Infection: A Retrospective Cohort Study
description	BackgroundHospital mortality is high for patients with encephalopathy caused by microbial infection. Microbial infections often induce sepsis. The damage to the central nervous system (CNS) is defined as sepsis-associated encephalopathy (SAE). However, the relationship between pathogenic microorganisms and the prognosis of SAE patients is still unclear, especially gut microbiota, and there is no clinical tool to predict hospital mortality for SAE patients. The study aimed to explore the relationship between pathogenic microorganisms and the hospital mortality of SAE patients and develop a nomogram for the prediction of hospital mortality in SAE patients.MethodsThe study is a retrospective cohort study. The lasso regression model was used for data dimension reduction and feature selection. Model of hospital mortality of SAE patients was developed by multivariable Cox regression analysis. Calibration and discrimination were used to assess the performance of the nomogram. Decision curve analysis (DCA) to evaluate the clinical utility of the model.ResultsUnfortunately, the results of our study did not find intestinal infection and microorganisms of the gastrointestinal (such as: Escherichia coli) that are related to the prognosis of SAE. Lasso regression and multivariate Cox regression indicated that factors including respiratory failure, lactate, international normalized ratio (INR), albumin, SpO2, temperature, and renal replacement therapy were significantly correlated with hospital mortality. The AUC of 0.812 under the nomogram was more than that of the Simplified Acute Physiology Score (0.745), indicating excellent discrimination. DCA demonstrated that using the nomogram or including the prognostic signature score status was better than without the nomogram or using the SAPS II at predicting hospital mortality.ConclusionThe prognosis of SAE patients has nothing to do with intestinal and microbial infections. We developed a nomogram that predicts hospital mortality in patients with SAE according to clinical data. The nomogram exhibited excellent discrimination and calibration capacity, favoring its clinical utility.
format	article
author	Lina Zhao Lina Zhao Yun Li Yunying Wang Qian Gao Zengzheng Ge Xibo Sun Yi Li
author_facet	Lina Zhao Lina Zhao Yun Li Yunying Wang Qian Gao Zengzheng Ge Xibo Sun Yi Li
author_sort	Lina Zhao
title	Development and Validation of a Nomogram for the Prediction of Hospital Mortality of Patients With Encephalopathy Caused by Microbial Infection: A Retrospective Cohort Study
title_short	Development and Validation of a Nomogram for the Prediction of Hospital Mortality of Patients With Encephalopathy Caused by Microbial Infection: A Retrospective Cohort Study
title_full	Development and Validation of a Nomogram for the Prediction of Hospital Mortality of Patients With Encephalopathy Caused by Microbial Infection: A Retrospective Cohort Study
title_fullStr	Development and Validation of a Nomogram for the Prediction of Hospital Mortality of Patients With Encephalopathy Caused by Microbial Infection: A Retrospective Cohort Study
title_full_unstemmed	Development and Validation of a Nomogram for the Prediction of Hospital Mortality of Patients With Encephalopathy Caused by Microbial Infection: A Retrospective Cohort Study
title_sort	development and validation of a nomogram for the prediction of hospital mortality of patients with encephalopathy caused by microbial infection: a retrospective cohort study
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/d8b54dcdce20403e86853cf154c8655a
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Development and Validation of a Nomogram for the Prediction of Hospital Mortality of Patients With Encephalopathy Caused by Microbial Infection: A Retrospective Cohort Study

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