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Incidence and Related Factors of Post-stroke Cognitive Impairment: a Multicenter Cross-sectional Study Based on Full-cycle Rehabilitation in Stroke

2024· article· en· W6922364568 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInnovations in Aquaponics and Hydroponics Systems
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationHospital Anxiety and Depression ScaleStroke (engine)CognitionAnxietyIncidence (geometry)Depression (economics)Berg Balance Scale

Abstract

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Background Post-stroke cognitive impairment (PSCI) can significantly limit the recovery of stroke patients at all stages and lead to a decline in activity participation and quality of life. Objective Based on the concept of full-cycle rehabilitation in stroke, by investigating the incidence of PSCI, to analyzed the differences of PSCI in different age and disease period and its potential influencing factors. Methods Stroke patients were hospitalized in the rehabilitation departments of 27 hospitals in different regions of China from October 2022 to July 2023 using simple random sampling method for cross-sectional analysis. A total of 402 patients were finally included according to the study criteria, and categorized into the young and middle-aged group (18-64 years old, n=234) and the elderly group (≥65 years old, n=168) according to the criteria of the National Bureau of Statistics of China, and the patients were also categorized into the acute-phase group (1-7 d, n=25), subacute-phase group (8-180 d, n=338), and the chronic-phase group (>180 d, n=39) according to the International Stroke Rehabilitation Alliance. Baseline information on patients was collected through interviews, assessments, and an electronic case system. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), and subscores and total scores were calculated for each cognitive domain. Using the National Institute of Health Stroke Scale (NIHSS), Fugl-Meyer Assessment-Upper Extremity (FMA-UE), Fugl-Meyer Assessment-Lower Extremity (FMA-LE), Berg Balance Scale (BBS), Modified Barthel Index (MBI), Hospital Anxiety Scale (HADS-A), and the Hospital Depression Scale (HADS-D) were used to assess the disease conditions and physical functioning of the patients. Spearman's rank correlation analysis was used to investigate the correlation between cognitive function levels and other clinical indicators at different ages and different stages of disease. Results The prevalence of PSCI in stroke patients was 76.4% (307/402), including 81.0% (136/168) in elderly patients and 73.1% (171/234) in young and middle-aged patients; the prevalence of PSCI in stroke patients was 56.0% (14/25) in the acute phase, 78.4% (265/338) in the subacute phase, and 71.8% (28/39) in the chronic phase. The results of grouping by age and disease period showed that the elderly group had lower visuospatial and executive function, attention, numeracy, delayed recall scores and total MoCA scores than those in the young and middle-aged group (P<0.05). Patients in the subacute-phase group had lower visuospatial and executive function, language, delayed recall scores and total MoCA scores than those in the acute-phase group (P<0.05). Correlation analysis showed that the total MoCA score was positively correlated (P<0.001) with educational level (rs=0.314), stroke type (rs=0.114), FMA-UE (rs=0.245), FMA-LE (rs=0.242), BBS (rs=0.265), MBI (rs=0.293), and was negatively correlated (P<0.05) with gender (rs=-0.107), age (rs=-0.103), history of hypertension (rs=-0.112), hemiplegic side (rs=-0.139), disease duration (rs=-0.135), NIHSS (rs=-0.107), HADS-A (rs=-0.239), HADS-D (rs=-0.280). Further stratified analyses showed that the young and middle-aged and elderly groups were correlated with the total MoCA score in terms of the educational level, NIHSS and physical function indicators such as FMA-UE, FMA-LE, BBS, MBI, HADS-A, and HADS-D (P<0.05). In the acute-phase group, disease duration, FMA-UE, and HADS-A were related to total MoCA score (P<0.05). In the subacute-phase group, age, education level, hypertension, history of alcohol consumption, type of stroke, hemiplegic side, disease duration, NIHSS, and physical function indicators such as FMA-UE, FMA-LE, BBS, MBI, HADS-A, HADS-D were correlated with the total MoCA score (P<0.05), and only educational level, hypertension, and HADS-D were correlated with the total MoCA score in the chronic-phase group (P<0.05) . Conclusion PSCI is closely related to age, disease development period, education level, physical function, balance, activities of daily living, anxiety and depression levels in stroke patients, and individualised preventive strategies and interventions should be developed for patients based on different stratified cognitive potential influencing factors, as well as increased screening and attention to cognition in the early stages of the disease to the later stages of rehabilitation.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.089
GPT teacher head0.471
Teacher spread0.383 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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