Evidence map›Paper›PMID 42699189›Full record

ArticleFrontiers in medicine2026

Predicting stroke-associated pneumonia for acute ischemic stroke patients post intravenous thrombolysis: the post-IVT-SAP risk score.

Daofeng Hu, Min Zhou, Lai Wei, Zhifeng Liu, Guoyong Zeng, Haoyi Ye, Jidong Peng, Yuping Zeng

Abstract read
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Article in Frontiers in medicine, 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

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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

8 authors.

Daofeng Hu *Department of Medical Imaging, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, China.
Min Zhou *Department of Neurology, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Ganzhou, China.
Lai WeiDepartment of Radiology, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Zhifeng LiuDepartment of Medical Imaging, The Fourth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Guoyong ZengDepartment of Neurology, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Ganzhou, China.
Haoyi YeDepartment of Medical Imaging, The Fourth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Jidong PengDepartment of Medical Imaging, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, China.
Yuping ZengDepartment of Medical Imaging, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Few prediction tools have been developed specifically for stroke-associated pneumonia (SAP) in patients with acute ischemic stroke (AIS) undergoing intravenous thrombolysis (IVT). This study aimed to develop and externally evaluate a simple risk score for SAP after IVT. Materials and methods: This multicenter retrospective study included 836 patients with AIS treated with IVT at three hospitals. Patients from two hospitals formed the training cohort, and those from the third hospital formed the external validation cohort. Univariable and multivariable logistic regression analyses were performed to identify independent predictors and develop a simple risk prediction score. Model discrimination was evaluated using receiver operating characteristic curve analysis. Results: Among 836 patients, 145 (17.3%) developed SAP. Age >75 years, atrial fibrillation, a higher pre-thrombolysis National Institutes of Health Stroke Scale score, and a lower pre-thrombolysis Alberta Stroke Program Early CT Score were independently associated with SAP and incorporated into the PISRS. The PISRS yielded an area under the curve of 0.718 in the training cohort and 0.801 (95% CI, 0.684-0.919) in the external validation cohort. Each 1-point increase in the PISRS was associated with increased odds of SAP within 7 days (OR = 2.623; 95% CI, 2.143-3.212). Conclusion: The PISRS is a simple admission-based score that may facilitate early risk stratification for SAP in patients with AIS undergoing IVT. Further prospective validation in larger and more diverse cohorts is required.

Indexed as

acute ischemic stroke (AIS)intravenous thrombolysis (IVT)post-IVT-SAP risk score (PISRS)predictive scorestroke-associated pneumonia (SAP)

Identifiers

PMID42699189
PMCPMC13542813

What Socratic holds

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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 Socratic graph.