O037 Improved sleep is associated with improved hip osteoarthritis symptoms
Bibliographic record
Abstract
Abstract Aim Sleep problems often co-exist with hip osteoarthritis (OA) can be improved with exercise. Our aim was to investigate whether improvements in sleep quality and duration were associated with improvements in pain and function in people with hip OA following exercise. Methods Data from 185 participants with hip OA, randomized to an exercise intervention were pooled and analyzed. The dependent variable was 3-month change in sleep quality and duration using the Pittsburgh Sleep Quality Index (PSQI; range 0–21, higher scores = poorer sleep). The independent variables were 3-month change in hip pain severity (11-point scale; range 0-10, with higher scores indicating worse pain; minimum clinical important difference 1.8) and function (Western Ontario and McMaster Universities Osteoarthritis Index; range 0-68, with higher scores indicating more dysfunction; minimum clinical important difference 6). Associations between change in PSQI scores and change in pain and function were examined using linear regression models, adjusted for baseline values and covariates. Results Each one-point improvement in the PSQI was associated with a 0.2-point reduction in pain (95% CI: 0.1 to 0.3; adjusted R2 = 0.14) and a 1.1-point improvement in function (95% CI: 0.6 to 1.6; R2 = 0.28). Each one hour increase in sleep duration was associated with a 0.33-point reduction in pain (95% 0.02 to 0.63; R2 = 0.09) and a 2.6-unit improvement in function (95% 1.1 to 4.1; R2 = 0.24). Conclusion Improvements in sleep quality and duration are associated with small improvements in pain and function post-exercise.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.004 | 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".