Evidence map›Paper›PMID 40999620›Full record

ArticleBrain and behavior2025

Cluster Analysis of Patients With Acute Ischemic Stroke: Identifying Characteristics of Long Hospital Stays in a Comprehensive Hospital.

HeJiao Mao, Guangsong Han, Yuhui Sha, Juanjuan Wu, Mingyu Tang, Ziang Pan, Lixin Zhou, Yicheng Zhu, Jun Ni

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Article in Brain and behavior, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers 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

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

HeJiao MaoState Key Laboratory of Complex Severe and Rare Diseases, Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Guangsong HanState Key Laboratory of Complex Severe and Rare Diseases, Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yuhui ShaState Key Laboratory of Complex Severe and Rare Diseases, Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Juanjuan WuState Key Laboratory of Complex Severe and Rare Diseases, Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Mingyu TangState Key Laboratory of Complex Severe and Rare Diseases, Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Ziang PanState Key Laboratory of Complex Severe and Rare Diseases, Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Lixin ZhouState Key Laboratory of Complex Severe and Rare Diseases, Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yicheng ZhuState Key Laboratory of Complex Severe and Rare Diseases, Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jun NiState Key Laboratory of Complex Severe and Rare Diseases, Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Funding

the National High-Level Hospital Clinical Research Funding
6 · The paper itself

Abstract

backgroundAcute ischemic stroke (AIS) is a leading cause of mortality and disability worldwide, imposing a significant burden on patients and healthcare systems. Length of stay (LOS) is a critical metric for assessing hospital resource utilization and patient prognosis. Identifying characteristics of AIS patients with prolonged LOS is essential for optimizing resource allocation and improving patient management. This study aimed to use cluster analysis to profile AIS patients with long LOS in a comprehensive hospital and explore differences in characteristics across gender and age subgroups.

methodsThis single-center, retrospective cohort study included 664 patients admitted with AIS to Peking Union Medical College Hospital from June 2012 to September 2021. Data collected included demographics, admission NIHSS scores, stroke risk factors, etiologies, and diagnostic workups. Patients were clustered using the K-prototype method, a machine learning technique for subclassifying complex data, to differentiate between patients with long and short LOS. Statistical tests were used to identify significant differences between the clusters.

resultsCluster analysis revealed that patients with longer LOS had a higher proportion of females (42.9% vs. 24.7%, p < 0.001) and were generally younger (52.3 vs. 65.4 years, p < 0.001). This group exhibited lower proportions of TOAST type 1 strokes (17.7% vs. 70.4%, p < 0.001), higher levels of hsCRP and D-dimer, and no significant difference in acute phase NIHSS scores. Notably, in-hospital strokes and admissions to non-neurological departments were more frequent in the long LOS group. Subgroup analysis by gender and age revealed that younger males and females shared similar characteristics with the overall long LOS group, including a higher incidence of non-neurological department admissions and higher D-dimer levels.

conclusionsThis study highlights the heterogeneity of AIS and the importance of etiological identification, particularly in younger and female patients. Our findings suggest that traditional factors like NIHSS scores may not fully capture the complexity of factors influencing LOS in these groups. Improved cross-departmental collaboration is crucial for better management of AIS patients.

Indexed as

Ischemic StrokeLength of StayAdultAgedAged, 80 and overAge FactorsCluster AnalysisFemaleHospitalizationHumansMaleMiddle AgedRetrospective StudiesRisk FactorsSex Factorsacute ischemic strokeage differencescluster analysisgender differenceshospital resource utilizationin‐hospital strokelength of stayNIHSSTOAST classification

Identifiers

PMID40999620
PMCPMC12463685

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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.