Mobile-bearing versus Medial-pivot Designs in Total Knee Arthroplasty: A Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Mobile-bearing (MB) and medial-pivot (MP) prostheses are the two popular designs used in total knee arthroplasty (TKA), yet their long-term outcomes remain controversial. This meta-analysis was conducted to determine whether there are any differences in outcomes between patients who receive these two prostheses in TKA. METHOD: We comprehensively searched electronic databases up to November 2024. Observational studies or randomized controlled trials reported postoperative outcomes, including radiographic results, functional score through the Knee Society Score (KSS), Western Ontario and McMaster Universities (WOMAC) score, and patient satisfaction. The results are presented in odd ratios (ORs) or mean differences with corresponding 95% confidence intervals (CIs). RESULTS: In total, four studies were included, with 1069 patients and 1251 operated knees (632 MB TKAs and 619 MP TKAs). The mean age was 68.21 years old and the mean follow-up duration was from 5 to 11 years. Regarding patient satisfaction, the MB prostheses brought greater comfort to patients in the last follow-up than the MP group (OR = 3.19; 95%CI 1.92-5.30; p < 0.001). Additionally, there were no differences in the outcomes of functional scores, including the KSS (p = 0.34), WOMAC score (p = 0.16), and range of motion (ROM) (p = 0.36) between patients receiving the MB and MP prostheses. CONCLUSIONS: Our meta-analysis of four studies highlighted the long-term outcomes of TKA between MB and MP designs. While KSS, WOMAC scores, and knee ROM showed no significant differences, patients with MB designs reported higher satisfaction levels compared with those with MP designs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.054 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".