Effects Of Preoperative Rehabilitation In Individuals Who Have Undergone Total Knee Arthroplasty: A Systematic Review
Bibliographic record
Abstract
Clinical practice typically includes treatment to improve pain, function, motion, and patient independence prior to total knee arthroplasty (TKA). However, it is unknown if this treatment improves outcomes following TKA. PURPOSE: To systematically review and synthesize the scientific literature in regards to how preoperative rehabilitation affects subjective and objective outcomes after TKA. METHODS: A computerized search was performed in February 2010. Criteria for inclusion required that studies (1) were written in English, (2) included patients undergoing TKA, (3) were randomized clinical trials, (4) included preoperative rehabilitation, and (5) reported 2-3 month postoperative point measures and measures of variability for specified outcomes. Outcomes of interest were the Pain, Stiffness, and Function subsections of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), knee flexion range of motion (ROM), and hospital length of stay (LOS). Included studies were reviewed separately by two investigators using the Physiotherapy Evidence Database (PEDro) Scale and a consensus was established for each. Hedge's g effect sizes [95% confidence intervals] were calculated to assess the magnitude of the treatment effect for each outcome, with separate meta-analyses performed as a summary of the treatment response for each outcome. RESULTS: Thirty-four studies were identified and seven met inclusion criteria. The average PEDro score was 5.6 out of 10 (range: 2 to 8). Meta-analysis revealed a weak effect (-0.1 [-0.3 to 0.2]) for preoperative rehabilitation on the Pain section of the WOMAC, a weak effect (-0.1 [-0.3 to 0.2]) for Stiffness, and a weak effect (0.1 [-0.2 to 0.3]) for Function. There was a weak effect (0.2[0.0 to 0.4]) for ROM and a weak effect (-0.2 [-0.4 to 0.0]) for LOS. While all effects were in favor of preoperative treatment, all CIs, except LOS, encompassed zero. CONCLUSION: For all outcomes except LOS, none were consistently favorable toward preoperative rehabilitation over the alternative for patients undergoing TKA. The clinical benefit of preoperative rehabilitation on patient outcomes remains unclear. Effects trended in favor of preoperative treatment, however the limited number of studies that met inclusion criteria likely contributes to weakness of effects.
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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 | 0.010 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".