Combined Medial Patellofemoral Ligament and Medial Patellotibial Ligament Reconstruction for Recurrent Lateral Patellar Dislocation in Flexion
Bibliographic record
Abstract
Recurrent lateral patellar dislocation can be a challenging entity to manage. It results from an imbalance between the restraints to lateralization of the patella and the forces applied to the patella within the biomechanical environment of the knee. The medial patellofemoral ligament has been recognized as the most important static soft-tissue restraint. However, the medial patellotibial ligament and medial patellomeniscal ligament are important for patellar stability at higher degrees of knee flexion. Lateral patellar dislocation in flexion poses a particularly challenging clinical entity with a combination of unique characteristics that need to be addressed to achieve optimal patellar tracking and stability. In this technical note, we describe a combined medial patellofemoral ligament and medial patellotibial ligament reconstruction technique to address lateral patellar dislocation in flexion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".