Evidence map›Paper›PMID 42021904›Full record

ArticleSichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition2026

[Pathogen Profile and Risk Factors for Hospital-Acquired Infection in Stroke Patients].

Ting Xu, Bingqing Han, Hanyu Zhang, Chunqing Shao, Yufei Wang, Yang Jiao, Guojun Zhang

Abstract readEnglish Abstract
In one paragraph

Article in Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ting Xu( 100070)Department of Laboratory Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.ORCID 0000-0002-8366-0463
Bingqing Han( 100070)Department of Laboratory Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
Hanyu Zhang( 100070)Department of Laboratory Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
Chunqing Shao( 100070)Department of Laboratory Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
Yufei Wang( 100070)Department of Laboratory Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
Yang Jiao( 100070)Department of Laboratory Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
Guojun Zhang( 100070)Department of Laboratory Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.ORCID 0000-0002-8366-0463

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the risk factors for hospital-acquired infection in patients with stroke and to analyze the distribution of pathogens and characteristics of infection sites. Methods: A retrospective cohort study was conducted, enrolling 393 patients with stroke hospitalized at Beijing Tiantan Hospital, Capital Medical University, from January 2024 to July 2025. Among them, 184 patients were assigned to the infection group and 209 to the non-infection group. Multivariable logistic regression analysis was used to identify risk factors for hospital-acquired infection, and a nomogram prediction model was constructed. Results: Multivariable logistic regression analysis identified cerebral infarction (odds ratio = 25.09, 95% confidence interval: 5.38-117.10), no history of alcohol consumption (odds ratio = 4.47, 95% confidence interval: 1.51-13.18), no history of cerebrovascular disease (odds ratio = 5.04, 95% confidence interval: 1.35-18.76), elevated neutrophil count (odds ratio = 1.29, 95% confidence interval: 1.08-1.55), and elevated C-reactive protein (odds ratio = 1.03, 95% confidence interval: 1.01-1.06) as independent risk factors for hospital-acquired infection in patients with stroke. Absence of nasogastric tube feeding (odds ratio = 0.09, 95% confidence interval: 0.03-0.31), no indwelling urinary catheterization (odds ratio = 0.21, 95% confidence interval: 0.06-0.77), and absence of postoperative coma (odds ratio = 0.07, 95% confidence interval: 0.01-0.36) were identified as protective factors. The nomogram model achieved an area under the curve of 0.96 (95% confidence interval: 0.94-0.98) in the training set and 0.94 (95% confidence interval: 0.90-0.99) in the validation set, with good calibration. Gram-negative bacteria were the predominant pathogens (70.2%), and the respiratory tract was the most common infection site (92.9%). Endotracheal intubation and impaired consciousness were identified as common risk factors for both pulmonary and Gram-negative bacterial infections. Conclusion: This study identified independent risk factors for hospital-acquired infection in patients with stroke, developed a nomogram model with good predictive performance, and preliminarily characterized the risk profiles associated with different infection types and sites. These findings provide a reference for early identification of high-risk patients and the formulation of targeted prevention and control strategies.

Indexed as

Cross InfectionStrokeAgedAged, 80 and overFemaleHumansLogistic ModelsMaleMiddle AgedNomogramsRetrospective StudiesRisk FactorsHospital-acquired infectionPredictive modelRisk factorsStroke

Identifiers

PMID42021904
PMCPMC13095767

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.