Novel Predictors of Stroke-Associated Pneumonia: A Single Center Analysis

Stroke-associated pneumonia (SAP) is a common cause of disability or death. Although the researches on SAP have been relatively mature, the method that can predict SAP with great accuracy has not yet been determined. It is necessary to discover new predictors to construct a more accurate predictive...

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Main Authors: Ya-ming Li, Li Zhao, Yue-guang Liu, Yang Lu, Jing-zhu Yao, Chun-ju Li, Wei Lu, Jian-hua Xu
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-03-01
Series:Frontiers in Neurology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2022.857420/full
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author Ya-ming Li
Li Zhao
Yue-guang Liu
Yang Lu
Jing-zhu Yao
Chun-ju Li
Wei Lu
Jian-hua Xu
author_facet Ya-ming Li
Li Zhao
Yue-guang Liu
Yang Lu
Jing-zhu Yao
Chun-ju Li
Wei Lu
Jian-hua Xu
author_sort Ya-ming Li
collection DOAJ
description Stroke-associated pneumonia (SAP) is a common cause of disability or death. Although the researches on SAP have been relatively mature, the method that can predict SAP with great accuracy has not yet been determined. It is necessary to discover new predictors to construct a more accurate predictive model for SAP. We continuously collected 2,366 patients with acute ischemic stroke, and then divided them into the SAP group and non-SAP group. Data were recorded at admission. Through univariate analyses and multivariate regression analyses of the data, the new predictive factors and the predictive model of SAP were determined. The receiver operating characteristic (ROC) curve and the corresponding area under the curve (AUC) were used to measure their predictive accuracy. Of the 2,366 patients, 459 were diagnosed with SAP. International normalized ratio (INR) (odds ratio = 37.981; 95% confidence interval, 7.487–192.665; P < 0.001), age and dysphagia were independent risk factors of SAP. However, walking ability within 48 h of admission (WA) (odds ratio = 0.395; 95% confidence interval, 0.287–0.543; P < 0.001) was a protective factor of SAP. Different predictors and the predictive model all could predict SAP (P < 0.001). The predictive power of the model (AUC: 0.851) which included age, homocysteine, INR, history of chronic obstructive pulmonary disease (COPD), dysphagia, and WA was greater than that of age (AUC: 0.738) and INR (AUC: 0.685). Finally, we found that a higher INR and no WA could predict SAP in patients with acute ischemic stroke. In addition, we designed a simple and practical predictive model for SAP, which showed relatively good accuracy. These findings might help identify high-risk patients with SAP and provide a reference for the timely use of preventive antibiotics.
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spelling doaj.art-f6528980461f42a3be5ca1a3a075853d2022-12-22T01:43:56ZengFrontiers Media S.A.Frontiers in Neurology1664-22952022-03-011310.3389/fneur.2022.857420857420Novel Predictors of Stroke-Associated Pneumonia: A Single Center AnalysisYa-ming LiLi ZhaoYue-guang LiuYang LuJing-zhu YaoChun-ju LiWei LuJian-hua XuStroke-associated pneumonia (SAP) is a common cause of disability or death. Although the researches on SAP have been relatively mature, the method that can predict SAP with great accuracy has not yet been determined. It is necessary to discover new predictors to construct a more accurate predictive model for SAP. We continuously collected 2,366 patients with acute ischemic stroke, and then divided them into the SAP group and non-SAP group. Data were recorded at admission. Through univariate analyses and multivariate regression analyses of the data, the new predictive factors and the predictive model of SAP were determined. The receiver operating characteristic (ROC) curve and the corresponding area under the curve (AUC) were used to measure their predictive accuracy. Of the 2,366 patients, 459 were diagnosed with SAP. International normalized ratio (INR) (odds ratio = 37.981; 95% confidence interval, 7.487–192.665; P < 0.001), age and dysphagia were independent risk factors of SAP. However, walking ability within 48 h of admission (WA) (odds ratio = 0.395; 95% confidence interval, 0.287–0.543; P < 0.001) was a protective factor of SAP. Different predictors and the predictive model all could predict SAP (P < 0.001). The predictive power of the model (AUC: 0.851) which included age, homocysteine, INR, history of chronic obstructive pulmonary disease (COPD), dysphagia, and WA was greater than that of age (AUC: 0.738) and INR (AUC: 0.685). Finally, we found that a higher INR and no WA could predict SAP in patients with acute ischemic stroke. In addition, we designed a simple and practical predictive model for SAP, which showed relatively good accuracy. These findings might help identify high-risk patients with SAP and provide a reference for the timely use of preventive antibiotics.https://www.frontiersin.org/articles/10.3389/fneur.2022.857420/fullstrokeinfectionpneumoniainternational normalized ratiowalking ability
spellingShingle Ya-ming Li
Li Zhao
Yue-guang Liu
Yang Lu
Jing-zhu Yao
Chun-ju Li
Wei Lu
Jian-hua Xu
Novel Predictors of Stroke-Associated Pneumonia: A Single Center Analysis
Frontiers in Neurology
stroke
infection
pneumonia
international normalized ratio
walking ability
title Novel Predictors of Stroke-Associated Pneumonia: A Single Center Analysis
title_full Novel Predictors of Stroke-Associated Pneumonia: A Single Center Analysis
title_fullStr Novel Predictors of Stroke-Associated Pneumonia: A Single Center Analysis
title_full_unstemmed Novel Predictors of Stroke-Associated Pneumonia: A Single Center Analysis
title_short Novel Predictors of Stroke-Associated Pneumonia: A Single Center Analysis
title_sort novel predictors of stroke associated pneumonia a single center analysis
topic stroke
infection
pneumonia
international normalized ratio
walking ability
url https://www.frontiersin.org/articles/10.3389/fneur.2022.857420/full
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AT yanglu novelpredictorsofstrokeassociatedpneumoniaasinglecenteranalysis
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