Relationship Between Lateral Patellar Stability and Tibial Tubercle Location for Varying Patellofemoral Geometries
Bibliographic record
Abstract
The geometry of the patellofemoral joint affects function and pathology. However, the impact of trochlear groove depth on treatments for patellar instability and pain is not clear. Tibial tubercle osteotomy is a common surgical intervention for patellar instability where the tibial insertion of the patellar tendon (PT) is translated to align the extensor mechanism and stabilize the joint. The aim of this work was to investigate the interaction between trochlear groove depth and PT insertion and their effect on patellar stability. Patellofemoral geometry was modified based on a statistical shape model to create knees with a range of trochlear groove depths. A Monte Carlo approach was used and 750 instances of a musculoskeletal model were generated with varying geometry and anterior and medial transfer of the PT. Stability was assessed by applying a lateral perturbation force to the patella during simulation of overground walking. In knees with deep trochlear grooves, a medialized PT increased stability. However, in knees with shallow trochlear grooves, stability was maximized for tendon insertion ∼1 mm medial to its neutral location. This PT insertion also corresponded to the best alignment of the patella in the trochlear groove in these knees, indicating that good alignment may be important to maximizing stability. Anterior PT transfer had minimal effect on stability for all geometries. A better understanding of the effects of articular geometry and tubercle location on stability may aid clinicians in patient-specific surgical planning.
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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 | 0.001 | 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".