Abstract P209: Community-Based Outpatient Stroke Rehabilitation Program Achieves Excellent Return to Work Outcomes: Characteristics and Rehabilitation Outcomes of Stroke Survivors Who Return to Work
Bibliographic record
Abstract
Background: Return to employment and driving are goals for many stroke survivors. There are few reports of patient centered outcomes like return to work or the characteristics of those who achieve these goals. Methods: Prospective observational study of stroke patients treated between 12/2011-7/2019 in an interdisciplinary outpatient rehabilitation program addressing physical, cognitive/communicative, risk factors, psychosocial, driving and vocational issues. Results: Of 190 consecutive patients,104(55%) were working prior to their stroke. 50% (73% men, 27% women) of those working pre-stroke returned to work upon program completion with 90% returning to their prior job, and 65% at prior hours. 24% of returning workers owned their own business, and 76% had other occupations. Returning workers had average age of 54 years, average NIHSS score of 4(range 0-11), average{mRS} of 2.7 (6% with 1; 25% with 2; 58% with 3; 10% with 4), and 31% were aphasic. 39 suffered ischemic strokes and 13 had hemorrhages. Locations were: 18 Left, 15 Right,11 Bilateral hemisphere, 8 Brainstem). 93% of patients working pre-stroke were driving. 80% who returned to work also resumed driving. Returning workers had average percent improvement in 6” walk and Berg Balance scores of 97% and 50% respectively; this group also improved in all 9 Stroke Impact scale domains with SIS total score improving an average of 22%. In comparison, of those not returning to work 34 had ischemic strokes, 18 had hemorrhages. This group had average age 55.6, average NIHSS score 7.3(range2-16), average {mRS} of 3.3(11% with 2, 54% with 3, 33% with 4, 2% with 5), 42% were aphasic, and 20% resumed driving. Returning workers had average admit Montreal Cognitive Assessment score of 25/30 and Stroke Self Efficacy Score of 85%; with average scores of 21/30 and 71% for those not returning to work. Average length of stay was 4.6(range .5-24) and 7.4(range1.7-18) months for those returning and not returning to work. Other demographic and outcome measures are collected. Conclusions: Despite significant disability, stroke survivors can achieve successful recovery, including return to work and driving. Further study of patients returning to work can help direct rehabilitation efforts for patients with return to work goals.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".