Bicompartmental knee arthroplasty vs total knee arthroplasty for the treatment of medial compartment and patellofemoral osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Interest in bicompartmental knee arthroplasty (BKA) for the treatment of medial patellofemoral osteoarthritis (MPFOA) has grown in recent years because BKA offers a bone and ligament-preserving alternative to total knee arthroplasty (TKA). BKA only resurfaces the diseased compartments, while preserving proprioception and native knee kinematics. Therefore, the objective of this study is to assess knee function, perioperative morbidity, and implant survivability in patients undergoing BKA vs TKA for MPFOA. METHODS: The databases MEDLINE, PUBMED, and EMBASE were systematically searched. Randomized controlled trials and nonrandomized comparative studies comparing BKA with TKA for the treatment of MPFOA were included for further analysis. The primary outcome of interest was knee function. Secondary outcomes included range of movement, operation length, intraoperative blood loss, hospital length of stay, postoperative complications, and rate of revision length. The quality of evidence was evaluated using the GRADE approach. Meta-analysis was performed by pooling the results of the selected studies when possible. RESULTS: Six studies were selected for inclusion (4 prospective studies and 2 retrospective cohort studies). In total, 274 patients and 277 knees were included for analysis. There were no significant differences between the 2 groups at any time points in terms of knee function, length of stay, complication rate, or revision rate, when monolithic BKA designs were controlled for. BKA did result in significantly decreased intraoperative blood loss, at the expense of increased operative length compared with TKA. CONCLUSIONS: The use of modular BKA for MPFOA is comparable with TKA in terms of short-term function, complication rate, and revision rate. BKA reduces intraoperative blood losses, but it is also more technically demanding, resulting in increased operation length. The use of modular BKA has acceptable short-term outcomes, but more long-term data are needed before it can be recommended for routine use in the treatment of MPFOA. The selection of modular BKA should be determined on a patient-specific basis. Currently, there is no evidence to suggest the use of monolithic BKA designs because of their high revision and failure rate.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".