Effectiveness of tele-rehabilitation in patients with knee osteoarthritis: A randomized controlled trial
Bibliographic record
Abstract
Objective The primary objective of this randomized controlled trial was to evaluate the effectiveness of tele-rehabilitation (TR) compared to conventional rehabilitation (CT) in reducing pain (as measured by the Numeric Pain Rating Scale [NPRS]) in patients with knee osteoarthritis (OA). Secondary objectives included assessing changes in physical function and quality of life, as measured by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and the Short Form-36 (SF-36) health survey, respectively. Methods Fifty-five patients diagnosed with knee OA were randomly allocated to either the TR group ( n = 29), receiving remote physiotherapy sessions three times a week for four weeks, or the CT group ( n = 26), undergoing traditional outpatient rehabilitation with the same exercise regimen. Outcomes were measured at baseline and after a three-month follow-up period. Results At baseline, there were no significant differences between groups in terms of NPRS and WOMAC scores. After three months, both the CT and the TR groups showed significant improvements in pain reduction (NPRS, p < 0.001), WOMAC score ( p < 0.001), and in some subscales of the SF-36 (i.e., physical functioning, role limitation attributable to physical problems, energy, and pain). Conclusion Tele-rehabilitation is an effective alternative to CT for reducing pain and improving quality of life in patients with knee OA. These findings suggest that TR can be incorporated alongside conventional approaches to provide a comprehensive treatment strategy for managing knee OA, enhancing patient outcomes in various dimensions of well-being. Trial registration NCT05719350; Telerehabilitation in Patients With Osteoarthritis (TABLET).
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".