Medial patellofemoral ligament reconstruction appears to be a better treatment than repair, proximal realignment, or conservative management for primary patellar dislocation: A network meta-analysis
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to compare the functional outcomes and re-dislocation rates of medial patellofemoral ligament (MPFL) reconstruction, MPFL repair, combined proximal realignment (CPR), and conservative management for primary patellar dislocation by conducting a systematic literature search of the available studies. The hypothesis was that MPFL repair and MPFL reconstruction would be better options for treating primary patellar dislocation. METHODS: Randomized controlled trials or prospective studies of primary patellar dislocation treated with MPFL reconstruction, MPFL repair, CPR, or conservative management were identified from the MEDLINE, EMBASE, and the Cochrane Library databases through December 31, 2021. A total of 626 patients met the prespecified inclusion criteria. The methodological quality of each study was assessed using a risk of bias table, Detsky quality index, and Newcastle-Ottawa Scale. The end-point data collected included comparisons of the mean in functional scores on knee outcomes scales and the number of patients who experienced re-dislocation. A network meta-analysis of the relevant literature was performed to investigate which treatment showed better outcomes. RESULTS: In total, 10 trials were included in this study. There was no statistically significant difference in the subgroup analysis in terms of the functional outcomes among MPFL reconstruction, MPFL repair, CPR, and conservative management. However, MPFL reconstruction showed statistically significantly better outcomes than MPFL repair, CPR, or conservative management in terms of the re-dislocation rate. Additionally, surface under the cumulative ranking curve percentage showed that MPFL reconstruction had a lower probability of re-dislocation than MPFL repair even though there was no significant difference (0.24, 95% confidence interval: 0.02-2.91). CONCLUSION: Using a network meta-analysis, this meta-analysis showed that there was no significant difference in functional outcomes in a subgroup analysis. In re-dislocation subgroup analysis, MPFL repair and MPFL reconstruction produced significantly better results than other treatments. Also, surface under the cumulative ranking curve percentage showed that MPFL reconstruction had a lower probability of re-dislocation than MPFL repair.
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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 | 0.028 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.049 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".