Very early cognitive screening and return to work after stroke
Bibliographic record
Abstract
Background: Stroke is a common cause of long-term disability worldwide, and an increasing number of persons affected by stroke are of working age. In addition to physical impairments, a majority of patients reportedly suffer cognitive impairments after stroke. Reduced cognitive function may hinder poststroke return to work (RTW); however, most studies of this relationship have assessed cognitive function months after the stroke.Objectives: The current study aims to investigate the degree of post-stroke RTW, and whether very early cognitive function screening can predict RTW after a stroke.Methods: This study included 145 persons treated for stroke at 18–63 years of age at a large university hospital in Sweden between 2011 and 2016. Data were retrieved from the GOTVED database. Within 36–48 h after hospital admission, cognitive function was screened using the Montreal Cognitive Assessment (MoCA). Full and partial RTW were assessed based on the Swedish Social Insurance Agency’s register. Logistic regression was performed to analyze the potential predictors of RTW at 6 months and 18 months.Results: Neither global cognitive function nor executive function at 36–48 h after stroke predicted any degree of RTW at 6 or 18 months. Male sex, lower stroke severity, and not being on sick leave prior to stroke were significant predictors of RTW.Conclusions: Screening for cognitive impairments at 36–48-h post stroke is apparently too early for predicting RTW, and thus cannot be the sole basis for discharge planning after stroke. Additional research is needed to further analyze cognitive function early after stroke and RTW.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".