Patellofemoral Instability Part I: Evaluation and Nonsurgical Treatment
Bibliographic record
Abstract
Patellofemoral instability (PFI) is a prevalent cause of knee pain and disability. It affects mostly young females with an incidence reported as high as 1 in 1,000. Risk factors for instability include trochlear dysplasia, patella alta, increased tibial tubercle-to-trochlear groove distance, abnormal patella lateral tilt, and coronal and torsional malalignment. Nonsurgical and surgical options for PFI can treat the underlying causes with varied success rates. The goal of this review series was to synthesize the current best practices into a concise, algorithmic approach. This article is the first in a two-part review on PFI, which focuses on the clinical and radiological evaluation, followed by nonsurgical management. The orthopaedic surgeon should be aware of the latest diagnostic protocol for PFI and its nonsurgical treatment options, their indications, and outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".