Relationship Between Hip Morphology and Hip‐Related Patient‐Reported Outcomes in Young and Middle‐Aged Individuals: A Population‐Based Study
Bibliographic record
Abstract
OBJECTIVE: Radiographic measurements of the alpha angle and the lateral center edge (LCE) angle in the hip joint are important for the diagnosis of femoroacetabular syndrome, a potential risk factor for hip osteoarthritis. Our objective was to determine whether these measurements are associated with hip-related patient-reported outcomes in young and middle-aged individuals. METHODS: A stratified random sample of white men and women ages 20-49 years, with and without hip pain, was selected using random digit dialing from the population of metro Vancouver, Canada. The alpha and LCE angles were measured bilaterally on radiographs using Dunn and anteroposterior views, respectively. Patient-reported outcomes were measured by the Copenhagen Hip And Groin Outcome Score (HAGOS), which has scales for symptoms, pain, daily activities, sports, physical activity, and quality of life (QoL). We performed descriptive analyses and a regression analysis with restricted cubic splines, adjusted for age and sex and weighted for the sampling design. RESULTS: Data were obtained for 500 subjects. The alpha angle distribution was strongly skewed, with a mean of 54°. The LCE angle distribution was symmetric, with a mean of 34°. In the restricted cubic splines analysis, the relationship between the alpha angle and HAGOS scores was nonlinear, with higher alpha angles generally associated with worse HAGOS scores for alpha >60°. The associations were statistically significant for symptoms, sports, and QoL. No association was found between the LCE angle and HAGOS scales. CONCLUSION: In a general population sample ages 20-49 years, we have found an association between the alpha angle and hip-related patient-reported 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".