Functional Outcome of Ischemic and Hemorrhagic Stroke Patients After Inpatient Rehabilitation
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The goal of this study was to assess the specific influence of stroke etiology on rehabilitation results. METHODS: This was a case-control study of 270 inpatients with sequelae of first stroke who were enrolled in homogeneous subgroups and matched for stroke severity, basal disability, age (within 1 year), sex, and onset admission interval (within 3 days) who were different only in terms of stroke origin, infarction versus hemorrhage. We compared the groups' length of stay, efficiency and effectiveness of treatment, and percentage of low and high responder patients. Odds ratios of dropouts and of low and high therapeutic response were also quantified. RESULTS: Compared with ischemic patients, hemorrhagic patients had significantly higher Canadian Neurological Scale and Rivermead Mobility Index scores at discharge; higher effectiveness and efficiency on the Canadian Neurological Scale, Barthel Index, and Rivermead Mobility Index; and a higher percentage of high responders on the Barthel Index. Hemorrhagic patients showed a probability of a high therapeutic response on the Barthel Index that was approximately 2.5 times greater than that of ischemic patients (odds ratio, 2.48; 95% confidence interval, 1.19 to 5.20; accuracy on prediction, 87.06%). CONCLUSIONS: The results of this study provide further evidence of better functional prognosis in stroke survivors with hemorrhagic 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".