P.061 An outcome study of ischemic stroke patients admitted to a rehabilitation unit
Bibliographic record
Abstract
Background: Earlier studies suggest that age and stroke severity are the main determinants in stroke patient disposition after rehabilitation. We examined these and other variables to determine those that correlated with returning home vs. long-term care (LTC). Methods: Chart review of ischemic stroke patients with initial alpha-FIM scores between 40 and 80 admitted to our Rehabilitation Unit from January 1, 2005 to December 31, 2014. Univariate and multivariate analyses were performed. Results: There were 162 suitable patients. 130 went home and 32 went to LTC. The multivariable analysis showed the following variables favored LTC disposition: age (1.2x increased risk with increased age, P<0.01), residence (17.5x increased risk if not starting at home, P<0.01), right vs. left hemisphere (5.4x greater risk with right hemisphere, p=0.01), bowel continence (10.6x greater risk if not continent, p<0.01), and caregiver (0.05x decreased risk if a caregiver is present, p<0.01). No differences were found for sex, diabetes mellitus, atrial fibrillation, previous stroke, congestive heart failure, COPD, obesity, hemianopsia or financial status. Conclusions: Numerous variables probably affect patient disposition after rehabilitation for acute ischemic stroke.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".