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Impact of cognitive impairment on the upper limb function recovery after lacunar stroke

2021· article· en· W3158940661 on OpenAlexaboutno aff
T. N. Semenova, V. N. Grigoryeva, E. V. Guzanova

Bibliographic record

VenuePractical medicine · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineUpper limbCognitionStroke (engine)Montreal Cognitive AssessmentRehabilitationPhysical medicine and rehabilitationAcute strokeExecutive dysfunctionPhysical therapyCognitive impairmentInternal medicineNeuropsychologyPsychiatry

Abstract

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The purpose of this study was to evaluate impact of cognitive impairments on the upper limb function recovery after acute lacunar stroke (LS). Material and methods. 139 patients (aged from 35 to 80 y. o.) with acute LS were examined. Along with the clinical and neurological examination, an upper limb function was evaluated by Action Research Arm Test and 9-Hole Peg Test, a study of cognitive status was made using the Montreal Cognitive Assessment (МоСа) and Frontal Assessment Battery (FAB). Results. Impaired upper limb function was revealed in 79% of patients with LS. After 2 weeks of acute period of LS, a significant improvement or the complete recovery of the upper limb function was observed in 81%. Moderate/severe executive dysfunction (FAB < 15 points) was defined in 65% of patients with LS and upper limb dysfunction. Moderate/severe cognitive impairments (МоСа < 26 points) were revealed in almost 55% of patients. In acute period of LS, the negative prognostic factor for complete recovery or significant improvement of the arm function was the presence of moderate/severe executive dysfunction (OR 3.89; 95% CI 1.07-14.19; p = 0.04) and general cognitive deficit (OR 3.27; 95% CI 1.10-9.70; p = 0.03). Conclusions. Cognitive impairments including executive disorders may affect the upper limb function recovery in acute period of LS. The data obtained can be used for the development of personalized rehabilitation programs for these patients.

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 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)0.000
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.052
GPT teacher head0.345
Teacher spread0.293 · 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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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