Functional Status and Health-Related Quality of Life During Inpatient Stroke Rehabilitation
Bibliographic record
Abstract
OBJECTIVE: To examine changes in functional status and health-related quality of life (HRQOL) during inpatient stroke rehabilitation to examine the associations between changes in the two measures. DESIGN: Two independently collected databases were combined for a retrospective analysis. One contained the objectively assessed FIM score; the other contained the subjectively assessed Medical Outcomes Study 36-item short form (SF-36). Admission and discharge scores were compared using paired-samples t tests. Associations between the FIM outcomes and the SF-36 outcomes were assessed by means of Pearson's product-moment correlations. RESULTS: One hundred sixteen patients were represented in both databases. Mean age was 71.4 yrs; 59 (51.1%) were female. All FIM scores, four of eight SF-36 domains, and one summary component score showed statistically significant improvement during the course of rehabilitation. Changes in SF-36 were not strongly associated with changes in FIM score, with only 6 of 90 correlations attaining statistical significance. CONCLUSIONS: Functional status and HRQOL improved considerably over the course of rehabilitation. However, there was poor association between the two outcomes. Both instruments offer insights into outcomes of inpatient rehabilitation, but they are complementary rather than overlapping.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".