Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Ya-ming, Zhao, Li, Liu, Yue-guang, Lu, Yang, Yao, Jing-zhu, Li, Chun-ju, Lu, Wei, Xu, Jian-hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9007082/
https://www.ncbi.nlm.nih.gov/pubmed/35432153
http://dx.doi.org/10.3389/fneur.2022.857420
_version_ 1784686789117607936
author Li, Ya-ming
Zhao, Li
Liu, Yue-guang
Lu, Yang
Yao, Jing-zhu
Li, Chun-ju
Lu, Wei
Xu, Jian-hua
author_facet Li, Ya-ming
Zhao, Li
Liu, Yue-guang
Lu, Yang
Yao, Jing-zhu
Li, Chun-ju
Lu, Wei
Xu, Jian-hua
author_sort Li, Ya-ming
collection PubMed
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.
format Online
Article
Text
id pubmed-9007082
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-90070822022-04-14 Novel Predictors of Stroke-Associated Pneumonia: A Single Center Analysis Li, Ya-ming Zhao, Li Liu, Yue-guang Lu, Yang Yao, Jing-zhu Li, Chun-ju Lu, Wei Xu, Jian-hua Front Neurol Neurology 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. Frontiers Media S.A. 2022-03-30 /pmc/articles/PMC9007082/ /pubmed/35432153 http://dx.doi.org/10.3389/fneur.2022.857420 Text en Copyright © 2022 Li, Zhao, Liu, Lu, Yao, Li, Lu and Xu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neurology
Li, Ya-ming
Zhao, Li
Liu, Yue-guang
Lu, Yang
Yao, Jing-zhu
Li, Chun-ju
Lu, Wei
Xu, Jian-hua
Novel Predictors of Stroke-Associated Pneumonia: A Single Center Analysis
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 Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9007082/
https://www.ncbi.nlm.nih.gov/pubmed/35432153
http://dx.doi.org/10.3389/fneur.2022.857420
work_keys_str_mv AT liyaming novelpredictorsofstrokeassociatedpneumoniaasinglecenteranalysis
AT zhaoli novelpredictorsofstrokeassociatedpneumoniaasinglecenteranalysis
AT liuyueguang novelpredictorsofstrokeassociatedpneumoniaasinglecenteranalysis
AT luyang novelpredictorsofstrokeassociatedpneumoniaasinglecenteranalysis
AT yaojingzhu novelpredictorsofstrokeassociatedpneumoniaasinglecenteranalysis
AT lichunju novelpredictorsofstrokeassociatedpneumoniaasinglecenteranalysis
AT luwei novelpredictorsofstrokeassociatedpneumoniaasinglecenteranalysis
AT xujianhua novelpredictorsofstrokeassociatedpneumoniaasinglecenteranalysis