The effects of age and sex on active and passive hip range of motion in individuals with alkaptonuria
Bibliographic record
Abstract
Purpose To report active and passive hip range of motion (ROM) data for individuals with alkaptonuria (AKU), with consideration for age, sex, and non-AKU comparative data.Materials and Methods Using a cross-sectional study design, 123 patients who had baseline ROM assessed in a previous international, multi-centre clinical trial were included. Data was compared between age groups, sexes, and with existing data from individuals without AKU. Data was analysed using a one-way ANOVA, paired t-test, and one-sample t-test, with results interpreted using partial eta squared and standardised mean differences (SMD).Results Differences were observed across the age groups for active and passive flexion (F = 3.815, p = 0.006, ηp2 = 0.115) and active hip abduction (F = 1.941, p = 0.108, ηp2 = 0.062). Differences between sexes ranged from trivial-to-large (SMD = 0.03 to 1.90), with variability evident across the age groups. Individuals with AKU were within the lower range of scores observed for healthy adults in flexion (t = −8.545 to −3.166, p = 0.010 to <0.001) and abduction (t = −20.830 to −0.737, p = 0.478 to <0.001).Conclusions Our results provide insight into the clinical value of ROM with consideration for age, sex and normative data as a determinant of disease progression and functional ability within individuals with AKU.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".