Post-stroke fatigue: A factor associated with inability to return to work in patients <60 years—A 1-year follow-up
Bibliographic record
Abstract
This study investigated the association between post-stroke fatigue and inability to return to work/drive in young patients aged <60 years with first stroke who were employed prior to infarct while controlling for stroke severity, age, extent of disability, cognitive function, and depression. The Fatigue Severity Scale (FSS) was used to evaluate post-stroke fatigue in this 1-year prospective cohort study. Follow-ups were completed at 3, 6, and 12 months post rehabilitation discharge. A total of 112 patients were recruited, 7 were excluded, due to loss to follow-up (n = 6) and being palliative (n = 1), resulting in 105 participants (71% male, average age 49 ±10.63 years). Stroke patients receiving both inpatient and outpatient rehabilitation were consecutively recruited. Persistent fatigue remained associated with inability to return to work when controlling for other factors at 3 months (adjusted OR = 18, 95% CI: 2.9, 110.3, p = 0.002), 6 months (adjusted OR = 29.81, 95% CI: 1.7, 532.8, p = 0.021), and 12 months (adjusted OR = 31.6, 95% CI: 1.8, 545.0, p = 0.018). No association was found between persistent fatigue and return to driving. Fatigue at admission was associated with inability to return to work at 3 months but not return to drive. Persistent fatigue was found to be associated with inability to resume work but not driving. It may be beneficial to routinely screen post-stroke fatigue in rehabilitation and educate stroke survivors and employers on the impacts of post-stroke fatigue on return to work.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".