Abstract WP329: A Functional Recovery Analysis of Inpatient Rehabilitation for Mild Stroke Patients
Bibliographic record
Abstract
Background / Purpose: Organized stroke care within the rehabilitation setting has improved functional outcomes and enable stroke patients to re-integrate within the communities. The Evidence Based Systematic Review for stroke recommends that mild stroke patients with a FIM ® > 80 could receive therapy within the community. However, in Ontario, approximately 20% of mild stroke patients continue to be admitted to inpatient rehabilitation. The purpose of this study is to identify the differences between the mild stroke patients being admitted to inpatient rehabilitation and being discharged home directly from acute care and propose a triage system for the mild stroke population. Methods: A retrospective chart audit was conducted for acute stroke discharges from two regional stroke centres in Ontario. The cohort included patients with a most responsible diagnosis of stroke and a completed AlphaFIM ® Instrument assessment. Stroke cases that had a Projected Full FIM ® score derived from the AlphaFIM ® Instrument with a score > 80, we’re stratified into two groups:discharged home and discharged to inpatient rehabilitation. Data was analyzed using a full and step wise regression model to determine which indicators impacted the discharge disposition. Results: There were 813 patients were eligible for inclusion. The mean age of participants was 72 years, and 54% were males. Overall, 33% of mild stroke patients were admitted to inpatient rehabilitation. The results of the analysis did not explain why so many mild stroke patients are admitted to inpatient rehabilitation. There was a trend toward mild stroke patients with aphasia, inattention and cognitive impairments being admitted to inpatient rehabilitation; however, this was not statistically significant. These two groups did not differ in rates of recurrent stroke or re-admission to hospital at follow-up. Conclusion: The results of this research indicates that milder stroke patients with a Projected Full FIM ® > 80 may effectively be managed in the community if appropriate rehabilitation services are available. Further research is warranted to evaluate functional outcomes of stroke patients within the community rehabilitation setting in order to determine its efficiencies.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".