Inferior outcome of revision of unicompartmental knee arthroplasty to total knee arthroplasty compared with primary total knee arthroplasty: systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to compare the revision of unicompartmental knee arthroplasty (UKA) to total knee arthroplasty (TKA) with primary TKA through a review of previously published studies. The hypothesis was that the revised UKA group would need additional operative procedures, including the use of stems and augments, resulting in poorer clinical outcomes than those of the primary TKA group. METHODS: A literature search of online register databases was performed to identify clinical trials that compared revised UKA to TKA with primary TKA. An electronic literature search was performed using the Medline, Embase, Cochrane Library, Web of Science, and Scopus databases. No language or date restrictions were applied. RESULTS: A total of 2034 articles were identified from a keyword search, of which 11 studies were determined as eligible. They were all retrospective comparative studies. The revised UKA to TKA group had longer operation times resulting from additional procedures such as bone grafting and use of stems and augments, higher reoperation rates, and worse postoperative clinical outcomes based on the Western Ontario and McMaster Universities Osteoarthritis Index and Oxford Knee Score than the primary TKA group, with the differences being statistically significant. CONCLUSION: UKA should not be considered an alternative procedure to TKA. LEVEL OF EVIDENCE: Therapeutic Level III.
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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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.017 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".