High tibial osteotomy compared with unicompartmental arthroplasty for the treatment of medial compartment osteoarthritis: a meta-analysis
Bibliographic record
Abstract
Background The objective of our meta-analysis was to compare the clinical outcomes of high tibial osteotomy (HTO) and unicompartmental knee arthroplasty (UKA) for the treatment of isolated medial compartment osteoarthritis (OA). Methods We searched the major medical databases for randomized trials and observational studies comparing HTO and UKA. After testing for publication bias and heterogeneity, the data were aggregated by fixed-effects modeling. Our primary outcome was the percentage of good or excellent outcomes in each group. Our secondary outcomes were implant survivorship and change in gait velocity. Results Six studies met our inclusion criteria for review. We found no evidence of publication bias or heterogeneity between studies for all outcome measures. The combined odds ratio for a good or excellent outcome in the UKA group was 2.03 (95% CI: 1.16 to 3.6) P = 0.01. The combined odds ratio for survival from aseptic loosening for the UKA group was 2.14 (95% CI: 0.93 to 4.93) P = 0.07. The pooled mean difference for gait velocity was 0.39 (95% CI: −0.12 to 0.90), P = 0.14. Conclusion UKA yields a greater percentage of good or excellent outcomes and a strong trend towards improved survivorship over HTO for medial compartment OA. Level of Evidence: Therapeutic Level II.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.041 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".