Radiographic Measures in Subjects Who Are Asymptomatic and Subjects With Patellofemoral Pain Syndrome
Bibliographic record
Abstract
Lateral tilt and displacement of the patella are considered characteristic features of patellofemoral pain syndrome. It has been suggested that abnormal patellar tilt and displacement are detected best with the knee near full extension, which requires computed tomography or magnetic resonance imaging. The objective of the current study was to determine whether alignment abnormalities could be detected in subjects with patellofemoral pain syndrome from axial radiographs obtained at 35 degrees knee flexion using a new, standardized radiographic technique. Thirty-three subjects with patellofemoral pain syndrome and 33 matched control subjects were recruited from a military population. Lateral and axial (unloaded and with quadriceps contraction) radiographs were taken using the Patellofemoral QUESTOR Precision Radiograph system. Measures of patellar tilt and displacement, and anatomic measures (sulcus angle, patellar facet angle, patella alta) were obtained from the radiographs. No significant differences in patellar tilt or displacement were detected between the groups (paired t tests) in either the unloaded or loaded (quadriceps contracted) condition, suggesting that these measures, obtained at this knee angle are not useful diagnostic or outcome measures in patellofemoral pain syndrome. Patellar angle, sulcus angle, and patellar height also did not differ between groups suggesting that these are not etiologic factors in patellofemoral pain syndrome.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".