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Record W2603598218 · doi:10.4102/sajp.v69i4.378

Factors which are predictive of return work after stroke

2013· article· en· W2603598218 on OpenAlexaboutno aff
Veronica Ntsiea, Heleen van Aswegen, Steve Olorunju

Bibliographic record

VenueSouth African Journal of Physiotherapy · 2013
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsRivermead post-concussion symptoms questionnaireMontreal Cognitive AssessmentStroke (engine)Functional Independence MeasureActivities of daily livingPhysical therapyCognitionPopulationMedicineBarthel indexRehabilitationPhysical medicine and rehabilitationPsychologyGerontologyCognitive impairmentPsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

Stroke impacts on a survivor’s ability to participate in community activities such as return to work (RTW) and affects people who are within the working age. There is a dearth of literature on RTW after stroke in developing countries. This study aimed to bridge this gap in South Africa, and was conducted within the Gauteng province as it comprises the largest share of the South African population. Seventy-two stroke survivors participated in this cross-sectional study. A demographic questionnaire; Barthel index; Modified Rivermead mobility index and Montreal cognitive assessment were used to determine the characteristics of study participants. The mean (standard deviation) scores for the Barthel Index (BI), Modified Rivermead mobility index (MRMI) and Montreal cognitive assessment (MoCA) were 19.6 (±0.2), 39.5 (±0.9) and 25.1 (±4.8) respectively. Thirty-one (43%) of the stroke survivors returned to work at six months after stroke. Stroke survivors with left hemiplegia had a greater chance of RTW than those with right hemiplegia (odds ratio 7.7). For every unit increase in the BI and MoCA score, the likelihood of RTW increased by 1.6 and 1.3 respectively. Conclusion: Side of hemiplegia, independence in activities of daily living and cognitive ability were found to be predictors of RTW at six months after stroke. It is important to identify people with cognitive impairments after stroke so that efforts can be made to increase awareness of the potential role that cognitive impairments may play in RTW.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.016
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.011
GPT teacher head0.259
Teacher spread0.247 · 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.

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".

Quick stats

Citations10
Published2013
Admission routes1
Has abstractyes

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