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A nomogram for predicting the risk of sepsis in patients with acute cholangitis

OBJECTIVE: Sepsis is a serious complication of acute cholangitis. We aimed to establish a nomogram for predicting the probability of sepsis in patients with acute cholangitis. METHODS: Subjects were patients with acute cholangitis in the Medical Information Mart for Intensive Care database. Extraneo...

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Autores principales: Liu, Qingqing, Zhou, Quan, Song, Meina, Zhao, Fanfan, Yang, Jin, Feng, Xiaojie, Wang, Xue, Li, Yuanjie, Lyu, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7140205/
https://www.ncbi.nlm.nih.gov/pubmed/31429338
http://dx.doi.org/10.1177/0300060519866100
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author Liu, Qingqing
Zhou, Quan
Song, Meina
Zhao, Fanfan
Yang, Jin
Feng, Xiaojie
Wang, Xue
Li, Yuanjie
Lyu, Jun
author_facet Liu, Qingqing
Zhou, Quan
Song, Meina
Zhao, Fanfan
Yang, Jin
Feng, Xiaojie
Wang, Xue
Li, Yuanjie
Lyu, Jun
author_sort Liu, Qingqing
collection PubMed
description OBJECTIVE: Sepsis is a serious complication of acute cholangitis. We aimed to establish a nomogram for predicting the probability of sepsis in patients with acute cholangitis. METHODS: Subjects were patients with acute cholangitis in the Medical Information Mart for Intensive Care database. Extraneous variables were excluded based on stepwise regression. The nomogram was established using logistic regression. RESULTS: The predictive model comprised five variables: age (odds ratio [OR]: 1.03, 95% confidence interval [CI]: 1.01–1.04), ventilator-support time (OR: 1.004, 95% CI: 1.001–1.008), diabetes (OR: 10.74, 95% CI: 2.80–70.57), coagulopathy (OR: 2.92, 95% CI: 1.83–4.73) and systolic blood pressure (OR: 0.62, 95% CI: 0.41–0.93). The areas under the receiver operating characteristic curve of the nomogram for the training and validation sets were 0.700 and 0.647, respectively. The Hosmer–Lemeshow goodness-of-fit test revealed high concordance between the predicted and observed probabilities for both the training and validation sets. The calibration plot also demonstrated good agreement between the predicted and observed outcomes for both the training and validation sets. CONCLUSIONS: We developed and validated a risk-prediction model for sepsis in patients with acute cholangitis. Our results will be helpful for preventing sepsis in patients with acute cholangitis.
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spelling pubmed-71402052020-04-13 A nomogram for predicting the risk of sepsis in patients with acute cholangitis Liu, Qingqing Zhou, Quan Song, Meina Zhao, Fanfan Yang, Jin Feng, Xiaojie Wang, Xue Li, Yuanjie Lyu, Jun J Int Med Res Special Issue: Infectious Disease and Mathematical Modelling New process OBJECTIVE: Sepsis is a serious complication of acute cholangitis. We aimed to establish a nomogram for predicting the probability of sepsis in patients with acute cholangitis. METHODS: Subjects were patients with acute cholangitis in the Medical Information Mart for Intensive Care database. Extraneous variables were excluded based on stepwise regression. The nomogram was established using logistic regression. RESULTS: The predictive model comprised five variables: age (odds ratio [OR]: 1.03, 95% confidence interval [CI]: 1.01–1.04), ventilator-support time (OR: 1.004, 95% CI: 1.001–1.008), diabetes (OR: 10.74, 95% CI: 2.80–70.57), coagulopathy (OR: 2.92, 95% CI: 1.83–4.73) and systolic blood pressure (OR: 0.62, 95% CI: 0.41–0.93). The areas under the receiver operating characteristic curve of the nomogram for the training and validation sets were 0.700 and 0.647, respectively. The Hosmer–Lemeshow goodness-of-fit test revealed high concordance between the predicted and observed probabilities for both the training and validation sets. The calibration plot also demonstrated good agreement between the predicted and observed outcomes for both the training and validation sets. CONCLUSIONS: We developed and validated a risk-prediction model for sepsis in patients with acute cholangitis. Our results will be helpful for preventing sepsis in patients with acute cholangitis. SAGE Publications 2019-08-20 /pmc/articles/PMC7140205/ /pubmed/31429338 http://dx.doi.org/10.1177/0300060519866100 Text en © The Author(s) 2019 http://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Special Issue: Infectious Disease and Mathematical Modelling New process
Liu, Qingqing
Zhou, Quan
Song, Meina
Zhao, Fanfan
Yang, Jin
Feng, Xiaojie
Wang, Xue
Li, Yuanjie
Lyu, Jun
A nomogram for predicting the risk of sepsis in patients with acute cholangitis
title A nomogram for predicting the risk of sepsis in patients with acute cholangitis
title_full A nomogram for predicting the risk of sepsis in patients with acute cholangitis
title_fullStr A nomogram for predicting the risk of sepsis in patients with acute cholangitis
title_full_unstemmed A nomogram for predicting the risk of sepsis in patients with acute cholangitis
title_short A nomogram for predicting the risk of sepsis in patients with acute cholangitis
title_sort nomogram for predicting the risk of sepsis in patients with acute cholangitis
topic Special Issue: Infectious Disease and Mathematical Modelling New process
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7140205/
https://www.ncbi.nlm.nih.gov/pubmed/31429338
http://dx.doi.org/10.1177/0300060519866100
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