Meta-analysis of the efficacy of proximal fibular osteotomy versus unicompartmental knee arthroplasty in the treatment of medial compartment knee osteoarthritis in Chinese patients
Bibliographic record
Abstract
BACKGROUND: This study comprehensively and methodically assessed the effectiveness of proximal fibular osteotomy (PFO) compared to unicompartmental knee arthroplasty (UKA) as treatment for medial compartment knee osteoarthritis (KOA) to offer direction and evidence to support clinical surgical decision-making. METHODS: Literature screening was strictly conducted according to the inclusion criteria, and reasonable outcome indicators were selected from the included studies. The PubMed, Web of Science, Wanfang Data, CQVIP, and CNKI databases were searched using a predefined search strategy. Quality assessment was stratified by study design: the Cochrane Risk of Bias 2.0 tool for randomized controlled trials (RCTs) and the Newcastle-Ottawa Scale (NOS) for non-RCTs. After extracting relevant data from the included studies, a meta-analysis was performed using RevMan 5.4 software. RESULTS: Thirteen studies involving 698 patients were included, with 355 and 343 patients in the PFO and UKA groups, respectively. The meta-analysis revealed that the PFO group had a shorter surgical duration, less intraoperative blood loss, shorter hospital stay, and lower hospitalization costs than the UKA group. Nevertheless, no statistically significant differences in the postoperative visual analog scale scores (VAS), Hospital for Special Surgery (HSS) scores, knee range of motion (ROM), Knee Society Score (KSS), femorotibial angle, and incidence of postoperative complications were observed between the PFO and UKA groups. CONCLUSIONS: PFO and UKA provide comparable short-term functional outcomes for medial compartment KOA, with PFO offering advantages in surgical efficiency and cost. However, given the high heterogeneity and limited long-term data, these findings should be interpreted cautiously, and further high-quality studies are needed to confirm the durability and broader applicability of PFO.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.047 |
| Bibliometrics | 0.005 | 0.005 |
| 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) | 0.002 | 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".