Factors associated with hip joint rotation in former elite athletes
Bibliographic record
Abstract
OBJECTIVES: To study factors associated with passive hip rotation range of motion (ROM) in former elite male athletes. METHODS: Athletes were interviewed about hip pain, disability, lifetime occupational loading, and athletic training. The passive hip rotation was measured with a Myrin inclinometer in 117 former elite male long distance runners, soccer players, weight lifters, and shooters aged 45-68 years. Magnetic resonance imaging was used to detect hip osteoarthritis. RESULTS: There were no differences in passive hip rotation ROM between the four athlete groups nor between diverging lifetime loading patterns associated with occupational or athletic activities. Among the subjects without hip osteoarthritis, hip pain, and hip disability according to a stepwise linear regression analysis, the only factor that was associated with the passive hip rotation ROM was body mass index (BMI), explaining about 21% of its variation. Subjects with high BMI had lower passive hip rotation ROM than those with low BMI. There was no right-left difference in the mean passive hip rotation ROM in subjects either with or without hip osteoarthritis as determined by magnetic resonance imaging. Nevertheless, hip rotation ROM was clearly reduced in a few hips with severe caput deformity. CONCLUSIONS: Long term loading appears to have no association with passive hip rotation ROM. On the other hand, the hip rotation value was lower in subjects with high BMI than in those with low BMI. A clear right-left difference in hip rotation was found only in those subjects who, according to our magnetic resonance imaging criteria, had severe hip osteoarthritis. These findings should be taken into account when hip rotation ROM is used in the clinical assessment of hip joints.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".