Evidence map›Paper›PMID 39560985›Full record

ArticleJMIR formative research2024

Factors Influencing Poststroke Cognitive Dysfunction: Cross-Sectional Analysis.

Wu Zhou, HaiXia Feng, Hua Tao, Hui Sun, TianTian Zhang, QingXia Wang, Li Zhang

Abstract read
In one paragraph

Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

9 citing papers in PubMed.

  1. Psychometric properties comparison of EQ-5D-Y-3L and CHU-9D in children with adenoid hypertrophy.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Wu ZhouSchool of Medicine, Southeast University, Nanjing, China.ORCID 0009-0006-6872-4680
HaiXia FengSchool of Medicine, Southeast University, Nanjing, China.ORCID 0000-0002-1718-0971
Hua TaoHuai 'an Second People's Hospital, Huaian, China.ORCID 0009-0007-2349-4532
Hui SunSchool of Medicine, Southeast University, Nanjing, China.ORCID 0009-0000-1350-5647
TianTian ZhangThe First People's Hospital of Hefei, HeFei, China.ORCID 0009-0003-5738-2548
QingXia WangSchool of Medicine, Southeast University, Nanjing, China.ORCID 0009-0006-9275-0651
Li ZhangZhongda Hospital, Southeast University, Nanjing, China.ORCID 0009-0004-1398-5184

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPoststroke cognitive impairment (PSCI) is a common and debilitating complication that affects stroke survivors, impacting memory, attention, and executive function. Despite its prevalence, the factors contributing to PSCI remain unclear, with limited insights into how demographic and clinical variables influence cognitive outcomes.

objectiveThis study investigates the incidence of cognitive impairment in patients with stroke and examines key demographic and clinical factors, such as age, gender, and education level, which contribute to cognitive decline. The aim is to provide a deeper understanding of PSCI to inform early intervention strategies for improving patient outcomes.

methodsA cross-sectional study was conducted on 305 patients with ischemic stroke admitted to Zhongda Hospital, Southeast University, from January 2019 to September 2022. Cognitive function was assessed using the Mini-Mental State Examination (MMSE) within 72 hours of hospital admission. Demographic information, including age, gender, and education level, were collected. Statistical analyses were performed using chi-square tests, independent t tests, and multivariate regression to assess the relationship between cognitive function and key variables. Pearson correlation analysis explored associations among age, education, and MMSE scores.

resultsAmong the 305 patients with stroke, 16.7% (n=51) were diagnosed with cognitive impairment based on MMSE scores. The prevalence of cognitive impairment was slightly higher in males (17.6%, n=159) than females (15.8%, n=146), but this difference was not statistically significant. A strong negative correlation was found between MMSE scores and age (r=-0.32; P<.01), indicating that older patients had lower cognitive function. Education level showed a positive correlation with MMSE scores (r=0.41; P<.01), with patients with higher educational attainment demonstrating better cognitive outcomes. Cognitive function showed a marked decline in patients older than 60 years, particularly in domains such as memory, attention, and language skills.

conclusionsThis study confirms that age and education are significant factors in determining cognitive outcomes after stroke. The results align with existing literature showing that cognitive function declines with age, while higher educational attainment serves as a protective factor. The findings suggest that individuals with greater cognitive reserve, often linked to higher education, are better equipped to cope with the impact of brain injury. However, the study's reliance on MMSE may have limited its ability to detect domain-specific impairments. Future studies should consider using more sensitive cognitive tools, such as the Montreal Cognitive Assessment (MoCA), to provide a more comprehensive evaluation of PSCI. Cognitive impairment is prevalent among stroke survivors, with age and education level being key factors influencing outcomes. These findings underscore the importance of early detection and targeted interventions to mitigate cognitive decline. Further research with larger samples and more sensitive cognitive assessments is needed to fully understand PSCI and improve rehabilitation strategies for patients with stroke.

Indexed as

Cognitive DysfunctionStrokeAdultAgedAged, 80 and overAge FactorsChinaCross-Sectional StudiesEducational StatusFemaleHumansMaleMental Status and Dementia TestsMiddle AgedPrevalenceRisk Factorsanalysis of associated factorscognitioncognitivecognitive dysfunctioncognitive impairmentcross sectionalcross-sectional studyeducationMini-Mental State ExaminationMMSEstatus surveystrokestroke patientssurvey

Identifiers

PMID39560985
PMCPMC11615546

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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.