Comparison of Unicompartmental Knee Arthroplasty Versus High Tibial Osteotomy for Medial Knee Osteoarthritis: An Updated Meta‐Analysis of 56,000 Patients
Bibliographic record
Abstract
ABSTRACT Osteoarthritis (OA) is a prevalent degenerative joint disease primarily affecting hip and knee joints, with an estimated 300 million cases globally. This study is crucial as it provides an updated, comprehensive comparison of unicompartmental knee arthroplasty (UKA) and high tibial osteotomy (HTO) for treating medial knee osteoarthritis, offering valuable insights into their relative effectiveness. The findings aim to inform clinical decision‐making and improve patient outcomes by identifying the superior treatment option. A comprehensive search was conducted across PubMed, Cochrane Library, and Google Scholar until August 1, 2024. Statistical analysis used Review Manager 5.4 with a random‐effects model, risk ratio (RR), and mean differences (MD) with 95% confidence intervals (CI) for the dichotomous and continuous outcomes, respectively. The Newcastle‐Ottawa Scale was used for quality assessment, and funnel plots were used to analyze publication bias. GRADE assessment was done to gauge the certainty of the evidence. Thirty‐nine studies, involving a total of 56,686 patients, were evaluated for comparison. UKA significantly reduced the complications (RR = 0.37; 95% CI: [0.25, 0.54]; p < 0.0001; I2 = 30%), revision rates to total knee arthroplasty (TKA) (RR = 0.64; 95% CI: [0.41, 0.99]; p = 0.05; I2 = 72%) and postoperative pain (MD = −0.33; 95% CI: [−0.64, −0.03]; p = 0.03; I2 = 89%) compared to HTO, while range of motion (ROM) (RR = −3.55; 95% CI: [−7.16, 0.52]; p = 0.09; I2 = 98%) and walking speed (MD = 0.02; 95% CI: [−0.04, 0.07]; p = 0.56; I2 = 0%) and surgical site infections(RR = 1.40; 95% CI: [0.30, 6.53]; p = 0.67; I2 = 86%) were comparable. All the functional knee scores are comparable except the Hospital for Special Surgery (HSS) score, which is increased in UKA (MD = 2.63; 95% CI: [0.52, 4.74]; p = 0.01; I2 = 76%). UKA is superior to HTO, offering lower revision rates, reduced postoperative pain, fewer complications, and better functional scores.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.045 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".