The Role of Patient Education in Total Knee Arthroplasty: a new methodology for developing countries: a randomized controlled trial
Bibliographic record
Abstract
Abstract Background: The illiteracy index is high in public hospitals of developing countries,. We established a method in which patients are instructed before total knee arthroplasty (TKA) in a differentiated way without the necessity of reading any self-orientation. Methods: We developed a multidisciplinary approach to improve patient education in TKA comprising of a differentiated orientation conducted by an orthopedic surgeon, a nurse and a physiotherapist. It consists of standardized lectures regarding on pre, intra and post-operative issues in a randomized controlled trial of 79 consecutive patients undergoing primary TKA. Thirty-four patients received the standard education (control group) and 45 patients received the differentiated education (intervention group). The patients were evaluated during at least six months. Results: After a 6-month follow-up period, the Short Form Health Survey (SF-36), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), the visual analogue pain scale (VAS) and knee range-of-motion (ROM) improved significantly in both groups. Range-of-motion was better in the intervention group (mean and SD - 106.9 ± 5.7 versus 92.5 ± 12.1 degrees, p = 0.02). Moreover, walk ability (more than 400 meters) was better in the intervention group compared with the control group (97.4% versus 72.4%, p = 0.003). In the intervention and control groups, respectively, 10.5% and 31% of patients reported the need for some walking devices (p = 0.03). Conclusions: A differentiated educational program with a multidisciplinary team had a positive impact on functional outcomes, improving ROM and walk ability of patients undergoing TKA in a short-term evaluation.
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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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".