Partial versus total knee arthroplasty for isolated antero-medial osteoarthritis – An analysis of PROMs and satisfaction
Bibliographic record
Abstract
AIM: This study aimed to compare the patient-reported functional outcomes and patient satisfaction after medial Unicompartmental Knee Arthroplasty (UKA) versus Total Knee Arthroplasty (TKA), performed for anteromedial osteoarthritis (AMOA) of the knee in patients from an Indian population, at a minimum 3-year follow-up. METHODS: This is a prospective matched cohort study (1:2 ratio). One hundred and one UKA cases were matched to 206 TKA cases by propensity score matching for age, body mass index (BMI), gender distribution, and the Charlson Comorbidity Index (CCI). The primary outcome (Oxford knee score, OKS) was assessed at a 3-year follow-up, along with secondary outcomes (Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC] Score, Forgotten Joint Score (FJS), Anterior Knee Pain (Kujala) score, patient satisfaction, and revision rate at the final follow-up). RESULTS: The UKA group was superior to the TKA group in patient-reported functional outcomes based on the OKS (p = 0.004). Using the FJS score, UKA was more likely to be a forgotten joint compared to TKA (p < 0.001). However, differences in the OKS and FJS did not meet the reported minimal clinically important difference (MCID) thresholds. Quality of life (EuroQol-5D VAS scale) was found to be significantly higher in the UKA group (p < 0.001). Patients in the UKA group were more likely to be very satisfied (75.2%) versus the TKA group (62.1%, p = 0.023). CONCLUSION: For AMOA, UKA was associated with improved patient satisfaction compared to TKA. Although patient-reported outcome measures were statistically in favour of UKA over TKA, the differences were not clinically significant. Multicenter and randomized studies comparing the two procedures are warranted. EVIDENCE: Level-II Therapeutic.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".