Establishment and validation of a predictive model for mortality within 30 days in patients with sepsis-induced blood pressure drop: A retrospective analysis.

<h4>Objectives</h4>To establish and validate an individualized nomogram to predict the probability of death within 30 days in patients with sepsis-induced blood pressure drop would help clinical physicians to pay attention to those with higher risk of death after admission to wards.<h...

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Main Authors: Bin Wang, Jianping Chen
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0252009
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spelling doaj-fb14750e13064a85af2283e2620bc7652021-06-09T04:30:26ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01165e025200910.1371/journal.pone.0252009Establishment and validation of a predictive model for mortality within 30 days in patients with sepsis-induced blood pressure drop: A retrospective analysis.Bin WangJianping Chen<h4>Objectives</h4>To establish and validate an individualized nomogram to predict the probability of death within 30 days in patients with sepsis-induced blood pressure drop would help clinical physicians to pay attention to those with higher risk of death after admission to wards.<h4>Methods</h4>A total of 1023 patients who were admitted to the Dongyang People's Hospital, China, enrolled in this study. They were divided into model group (717 patients) and validation group (306 patients). The study included 13 variables. The independent risk factors leading to death within 30 days were screened by univariate analyses and multivariate logistic regression analyses and used for Nomogram. The discrimination and correction of the prediction model were assessed by the area under the Receiver Operating Characteristic (ROC) curve and the calibration chart. The clinical effectiveness of the prediction model was assessed by the Decision Curve Analysis (DCA).<h4>Results</h4>Seven variables were independent risk factors, included peritonitis, respiratory failure, cardiac insufficiency, consciousness disturbance, tumor history, albumin level, and creatinine level at the time of admission. The area under the ROC curve of the model group and validation group was 0.834 and 0.836. The P value of the two sets of calibration charts was 0.702 and 0.866. The DCA curves of the model group and validation group were above the two extreme (insignificant) curves.<h4>Conclusions</h4>The model described in this study could effectively predict the death of patients with sepsis-induced blood pressure drop.https://doi.org/10.1371/journal.pone.0252009
collection DOAJ
language English
format Article
sources DOAJ
author Bin Wang
Jianping Chen
spellingShingle Bin Wang
Jianping Chen
Establishment and validation of a predictive model for mortality within 30 days in patients with sepsis-induced blood pressure drop: A retrospective analysis.
PLoS ONE
author_facet Bin Wang
Jianping Chen
author_sort Bin Wang
title Establishment and validation of a predictive model for mortality within 30 days in patients with sepsis-induced blood pressure drop: A retrospective analysis.
title_short Establishment and validation of a predictive model for mortality within 30 days in patients with sepsis-induced blood pressure drop: A retrospective analysis.
title_full Establishment and validation of a predictive model for mortality within 30 days in patients with sepsis-induced blood pressure drop: A retrospective analysis.
title_fullStr Establishment and validation of a predictive model for mortality within 30 days in patients with sepsis-induced blood pressure drop: A retrospective analysis.
title_full_unstemmed Establishment and validation of a predictive model for mortality within 30 days in patients with sepsis-induced blood pressure drop: A retrospective analysis.
title_sort establishment and validation of a predictive model for mortality within 30 days in patients with sepsis-induced blood pressure drop: a retrospective analysis.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2021-01-01
description <h4>Objectives</h4>To establish and validate an individualized nomogram to predict the probability of death within 30 days in patients with sepsis-induced blood pressure drop would help clinical physicians to pay attention to those with higher risk of death after admission to wards.<h4>Methods</h4>A total of 1023 patients who were admitted to the Dongyang People's Hospital, China, enrolled in this study. They were divided into model group (717 patients) and validation group (306 patients). The study included 13 variables. The independent risk factors leading to death within 30 days were screened by univariate analyses and multivariate logistic regression analyses and used for Nomogram. The discrimination and correction of the prediction model were assessed by the area under the Receiver Operating Characteristic (ROC) curve and the calibration chart. The clinical effectiveness of the prediction model was assessed by the Decision Curve Analysis (DCA).<h4>Results</h4>Seven variables were independent risk factors, included peritonitis, respiratory failure, cardiac insufficiency, consciousness disturbance, tumor history, albumin level, and creatinine level at the time of admission. The area under the ROC curve of the model group and validation group was 0.834 and 0.836. The P value of the two sets of calibration charts was 0.702 and 0.866. The DCA curves of the model group and validation group were above the two extreme (insignificant) curves.<h4>Conclusions</h4>The model described in this study could effectively predict the death of patients with sepsis-induced blood pressure drop.
url https://doi.org/10.1371/journal.pone.0252009
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AT jianpingchen establishmentandvalidationofapredictivemodelformortalitywithin30daysinpatientswithsepsisinducedbloodpressuredroparetrospectiveanalysis
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