A Modified Test for Patellar Instability
Bibliographic record
Abstract
OBJECTIVE: (1) Determine if displacement of the patella in a distal lateral direction results in a more sensitive method to show deficiency of the medial patellofemoral ligament (MPFL), the primary restraint to lateral patellar dislocation, than the traditional patellar apprehension test in a direct lateral direction. (2) Determine objective criteria for defining a positive patellar instability test rather than subjective evaluation of apprehension. DESIGN: In vitro biomechanical study. SPECIMENS: Ten above-the-knee amputation specimens. MAIN OUTCOME MEASURES: Force-displacement curves with direct lateral patellar displacement were compared with curves with distal lateral patellar displacement before and after sectioning the MPFL. RESULTS: After dividing the MPFL, average terminal restraining force to distal lateral patellar displacement declined by 53% (P=0.024), but force declined only by 30% (P=0.09) with lateral displacement. The greatest difference in terminal slope (eg, end point) was with the MPFL intact with lateral displacement compared with distal lateral displacement with the ligament divided (P=8.67x10(-5)). The terminal slope declined after ligament division with lateral (P=0.07) and distal lateral patellar displacement (P=0.09). CONCLUSION: Displacement of the patella in a distal lateral direction is a more sensitive maneuver to detect disruption of the MPFL, the primary soft tissue restraint, than with traditional lateral displacement. With the knee flexed 30 degrees and patella displaced 2 cm, objective criteria for a positive patellar instability test include greater ease of patellar translation and a softer end point compared with a normal, contralateral knee.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".