Better PROMs and higher return-to-sport rate after modular bicompartmental knee arthroplasty than after total knee arthroplasty for medial and patellofemoral compartment osteoarthritis
Bibliographic record
Abstract
Background Theoretical advantages of bicompartmental knee arthroplasty (BKA) over total knee arthroplasty (TKA) for bicompartmental (medial combined with patellofemoral) osteoarthritis (OA) are still unclear. This study aimed to compare patient-reported outcome measures (PROMs) and return-to-sport (RTS) rate between modular BKA and TKA in early follow-up. Methods Twenty-five consecutive modular BKA cases with a minimum 2-year follow-up were matched with 50 TKA cases at 1:2 ratio. Demographic data and preoperative functional scores, including the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Knee Society Scores (KSSs), were analyzed to ensure comparability. Postoperative WOMAC score, KSS, range of motion (ROM), Forgotten Joint Score-12 (FJS-12), and RTS rates were compared. Operative time and blood loss were also analyzed. Results Significant differences in the WOMAC-function (median 97.1 vs. 89.7, p < 0.001) and KSS-function (median 90.0 vs. 80.0, p = 0.003) scores were identified between the BKA and TKA groups. ROM was significantly greater in the BKA group than in the TKA group (median 125.0° vs. 120.0°, p = 0.004), in addition to the FJS-12 (median 89.6 vs. 53.1, p < 0.001). The overall RTS rate was significantly higher in the BKA group than in the TKA group (71.6% vs. 56.5%, p = 0.039). Operative time was significantly longer in the BKA group than in the TKA group (median 105.0 vs. 67.5 min, p < 0.001), but blood loss was similar (median 557.6 vs. 450.7 ml, p = 0.334). Conclusion Modular BKA demonstrated better functional recovery, better joint perception, and higher RTS rate than TKA; thus, modular BKA can be a good alternative for bicompartmental OA.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".