Assessment of demographic and pathoanatomic risk factors in recurrent patellofemoral instability
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: The WARPS/STAID classification employs clinical assessment of presenting features and anatomic characteristics to identify two distinct subsets of patients within the patellofemoral instability population. The purpose of this study was to further define the specific demographics and the prevalence of risky pathoanatomies in patients classified as either WARPS or STAID presenting with recurrent patellofemoral instability. A secondary purpose was to further validate the WARPS/STAID classification with the Banff Patella Instability Instrument (BPII), the Marx activity scale and the Patellar Instability Severity Score (ISS). METHODS: A convenience sample of 50 patients with recurrent patellofemoral instability, including 25 WARPS and 25 STAID subtype patients, were assessed. Clinical data were collected including assessment of demographic risk factors (sex, BMI, bilaterality of symptoms, affected limb side and age at first dislocation) and pathoanatomic risk factors (TT-TG distance, patella height, patellar tilt, grade of trochlear dysplasia, Beighton score and rotational abnormalities of the tibia or femur). Patients completed the BPII and the Marx activity scale. The ISS was calculated from the clinical assessment data. Patients were stratified into the WARPS or STAID subtypes for comparative analysis. An independent t test was used to compare demographics, the pathoanatomic risk factors and subjective measures between the groups. Convergent validity was tested with a Pearson r correlation coefficient between the WARPS/STAID and ISS scores. RESULTS: Demographic risk factors statistically associated with a WARPS subtype included female sex, age at first dislocation and bilaterality. Pathoanatomic risk factors statistically associated with a WARPS subtype included trochlear dysplasia, TT-TG distance, generalized ligamentous laxity, patellar tilt and rotational abnormalities. The independent t test revealed a significant difference between the ISS scores: WARPS subtype (M = 4.4, SD = 1.1) and STAID subtype (M = 2.5, SD = 1.5); t(48) = 5.2, p < 0.001. The relationship between the WARPS/STAID and the ISS scores, measured using a Pearson r correlation coefficient, demonstrated a strong relationship: r = -0.61, n = 50, p < 0.001. CONCLUSIONS: This study has demonstrated statistically significant evidence that certain demographics and pathoanatomies are more prevalent in each of the WARPS and STAID patellofemoral instability subtypes. There was no difference in quality-of-life or activity level between the subtypes. The WARPS/STAID score demonstrated convergent validity to the ISS and divergent validity to the BPII score and the Marx activity scale. This study has further validated both the WARPS/STAID classification and the ISS of patients that present with recurrent patellofemoral instability. LEVEL OF EVIDENCE: III.
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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) | 0.001 | 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 it