No difference between mobile and fixed bearing in primary total knee arthroplasty: a meta‐analysis
Bibliographic record
Abstract
PURPOSE: Both mobile (MB) and fixed (FB) bearing implants are routinely used for total knee arthroplasty (TKA). This meta-analysis compared MB versus FB for TKA in terms of implant positioning, joint function, patient reported outcome measures (PROMs), and complications. It was hypothesised that MB performs better than FB implants in primary TKA. METHODS: This meta-analysis was conducted according to the 2020 PRISMA statement. In February 2022, the following databases were accessed: Pubmed, Web of Science, Google Scholar, Embase. All the randomized clinical trials (RCTs) comparing mobile versus fixed bearing for primary TKA were considered. RESULTS: Data from 74 RCTs (11,116 procedures) were retrieved. The mean follow-up was 58.8 (7.5 to 315.6) months. The MB group demonstrated greater range of motion (ROM) (P = 0.02), Knee Society Score (KSS) score (P < 0.0001), and rate of deep infections (P = 0.02). No difference was found in implant positioning: tibial slope, delta angle, alpha femoral component angle, gamma femoral component angle, beta tibial component angle, tibiofemoral alignment angle, posterior condylar offset, radiolucent lines. No difference was found in duration of the surgical procedure. No difference was found in the following PROMs: Oxford Knee Score (OKS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), visual analogue scale (VAS), function and pain subscales of the KSS score. No difference was found in the rate of anterior knee pain, revision, aseptic loosening, fractures, and deep vein thrombosis. CONCLUSION: There is no evidence in support that MB implants promote greater outcomes compared to FB implants in primary TKA. LEVEL OF EVIDENCE: Level I.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.048 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".