EVALUATING THE EFFECTIVENESS OF POST-SURGICAL REHABILITATION PROGRAMS ON FUNCTIONAL RECOVERY AFTER KNEE AND HIP JOINT SURGERIES IN PAKISTAN
Bibliographic record
Abstract
Background: Postoperative rehabilitation is a vital component in the recovery process after total knee and hip joint replacement surgeries. In Pakistan, limited data exists regarding the effectiveness of rehabilitation programs on functional outcomes following such procedures. Objective: To assess rehabilitation outcomes and functional recovery among patients undergoing knee and hip joint surgeries in the Lahore region of Pakistan. Methods: A descriptive study was conducted over eight months in tertiary care hospitals and rehabilitation centers in Lahore. A total of 422 patients who underwent either total knee or hip replacement and completed at least four weeks of structured rehabilitation were enrolled. Functional outcomes were measured using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and the Timed Up and Go (TUG) test. Statistical analyses included one-way ANOVA, t-tests, and Pearson correlation. Results: The mean age of participants was 62.3 ± 8.4 years, with 61.1% undergoing knee and 38.9% undergoing hip replacement. The average WOMAC total score was 40.9 ± 9.1, indicating moderate functional improvement. TUG test times averaged 13.2 ± 2.8 seconds for knee and 12.6 ± 2.4 seconds for hip replacement groups, within normal functional limits. Longer rehabilitation duration was significantly associated with better WOMAC scores (p < 0.001), and a moderate negative correlation was observed between weeks of rehabilitation and total WOMAC scores (r = –0.48, p < 0.001). Conclusion: Structured and prolonged rehabilitation programs significantly improve functional recovery in post-surgical knee and hip joint patients. These findings emphasize the need to integrate accessible rehabilitation into routine postoperative care across Pakistan.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".