A meta-analysis of unicompartmental knee arthroplasty revised to total knee arthroplasty versus primary total knee arthroplasty
Bibliographic record
Abstract
BACKGROUND: This study was performed to compare the clinical outcomes of unicompartmental knee arthroplasty (UKA) revised to total knee arthroplasty (TKA) versus primary TKA. METHODS: Relevant trials were identified via a search of the Cochrane Central Register of Controlled Trials and PubMed from inception to 17 June 2017. A meta-analysis was performed to compare postoperative outcomes between revised UKA and primary TKA with respect to the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, Knee Society Score (KSS), mean polyethylene thickness, hospital stay, revision rate, range of motion (ROM), and complications. RESULTS: Five of 233 studies involving 536 adult patients (revised UKA group, n = 209; primary TKA group, n = 327) were eligible for inclusion in the meta-analysis. The primary TKA group had better WOMAC scores, KSS, and ROM than the revised UKA group (P < 0.05). Compared with primary TKA, revision of UKA to TKA required more augments, stems, and bone grafts and a thicker polyethylene component (P < 0.05). There were no significant differences between the two groups in the revision rate, hospital stay, or complications (P > 0.05). CONCLUSION: Conversion of UKA to TKA is associated with poorer clinical outcomes than primary TKA. Furthermore, we believe that conversion of UKA to TKA is more complicated than performing primary TKA. Revision UKA often requires more augments, stems, and bone grafts and thicker polyethylene components than primary TKA. However, patients who undergo conversion of UKA to TKA have similar hospital stay, complications, and revision rate as patients who undergo primary TKA.
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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 | 0.018 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.056 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".