Total Knee Arthroplasty Versus Education and Exercise for Knee Osteoarthritis: A Propensity‐Matched Analysis
Bibliographic record
Abstract
OBJECTIVE: We estimate the treatment effect of total knee arthroplasty (TKA) versus an education and exercise (Edu+Ex) program on pain, function, and quality of life outcomes 3 and 12 months after treatment initiation for knee osteoarthritis (OA). METHODS: Patients with knee OA who had undergone TKA were matched on a 1:1 ratio with participants in an Edu+Ex program based on a propensity score fitted to a range of pretreatment covariates. After matching, between-group differences in improvement (the treatment effect) in Knee Injury and Osteoarthritis Outcome Score 12-item version (0, worst to 100, best) pain, function, and quality of life from baseline to 3 and 12 months were estimated using linear mixed models, adjusting for unbalanced covariates, if any, after matching. RESULTS: The matched sample consisted of 522 patients (Edu+Ex, n = 261; TKA, n = 261) who were balanced on all pretreatment characteristics. At 12-month follow-up, TKA resulted in significantly greater improvements in pain (mean difference [MD] 22.8; 95% confidence interval [95% CI] 19.7-25.8), function (MD 21.2; 95% CI 17.7-24.4), and quality of life (MD 18.3; 15.0-21.6). Even so, at least one-third of patients receiving Edu+Ex had a clinically meaningful improvement in outcomes at 12 months compared with 75% of patients with TKA. CONCLUSION: TKA is associated with greater improvements in pain, function, and quality of life, but these findings also suggest that Edu+Ex may be a viable alternative to TKA in a meaningful proportion of patients, which may reduce overall TKA need. Confirmatory trials are needed.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".