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Correlation between Upper Limb Motor Function and Attention after Stroke: a Multicenter Cross-sectional Study

2025· article· en· W6903454364 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsUpper limbCorrelationRehabilitationMotor functionLower limbStroke (engine)Finger tappingTask (project management)

Abstract

fetched live from OpenAlex

Background Upper limb motor dysfunction is a common functional disorder after stroke. Attention may have an impact on the recovery of upper limb motor function, but there is little evidence of correlation between upper limb motor function and attention. Objective To explore the correlation between upper limb motor function and attention after stroke, and to provide a new perspective for clinical rehabilitation of upper limb function. Methods A total of 480 stroke patients who were hospitalized in the Department of Rehabilitation Medicine of 26 units in China from March to October 2023 were selected as the study subjects. The Fugl-Meyer Assessment Upper Limb (FMA-UL) and Montreal Cognitive Assessment (MoCA) were used to evaluate the upper limb motor function and attention of the patients, respectively. Pearson correlation analysis was used to explore the correlation between the total score of FMA-UL and the scores of attention assessment items in MoCA. Results Among the 480 patients, 105 patients did not finish the complete evaluation, so finally, 375 patients with stroke were included. The average FMA-UL score was (31.26±22.49) points. The average MoCA-Attention score was (4.74±1.60) points. The average Attention-Forward Digit Span and Backward Digit Span task score was (1.62±0.63) points; the average Attention-Vigilance task score was (0.74±0.45) points; the average Attention-Serial 7s task score was (2.39±0.95) points. The total FMA-UL score of male patients was higher than that of female patients (P<0.05). The total score of FMA-UL in all patients was positively correlated with the total score of MoCA-Attention, the score of Forward Digit Span and Backward Digit Span task, the score of Vigilance task, and the score of Serial 7s task (r=0.226, 0.146, 0.195, 0.182, P<0.05). The total score of FMA-UL in male patients was positively correlated with the total score of MoCA-Attention, the score of Forward Digit Span and Backward Digit Span task, the score of Vigilance task, and the score of Serial 7s task (r=0.236, 0.128, 0.213, 0.197, P<0.05) . Conclusion There is a significant and positive correlation between upper limb motor function and attention after stroke. The correlation between sustained attention and upper limb motor function is higher, and the correlation between attention span and upper limb motor function is lower. After grouping according to gender, the correlation between upper limb motor function and attention in male patients is the same as the above, while the correlation between upper limb motor function and attention in female patients is not significant, and gender may have an impact on the correlation between upper limb motor function and attention.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.108
GPT teacher head0.514
Teacher spread0.406 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2025
Admission routes1
Has abstractyes

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