Sleep Quality and Fatigue Are Associated with Pain Exacerbations of Hip Osteoarthritis: An Internet-based Case-crossover Study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association of sleep quality, sleep duration, and fatigue with hip pain exacerbations in persons with symptomatic hip osteoarthritis (OA). METHODS: Participants (n = 252) were followed for 90 days and asked to complete online questionnaires at 10-day intervals (control periods). A hip pain exacerbation (case periods) was defined as an increase of 2 points in pain intensity compared with baseline on a numeric rating scale (0-10). Subjective sleep quality and sleep duration were assessed using the Pittsburgh Sleep Quality Index, and fatigue was measured by Multidimensional Assessment of Fatigue in both periods. Univariable and multivariable conditional logistic regressions were used to assess the association. RESULTS: Of the 252 participants, 130 (52%) were included in the final analysis. Univariate association analysis showed that both poor sleep quality and greater fatigue were associated with increased odds of pain exacerbations (OR 1.72, 95% CI 1.04-2.86; OR 1.92, 95% CI 1.21-3.05, respectively). Short sleep duration was not associated with pain exacerbations. Poor sleep quality and greater fatigue remained associated with pain exacerbations after adjustment for physical activity and night pain levels in multivariable analysis. There was no significant interaction between sleep quality and fatigue (p = 0.21). CONCLUSION: Poor sleep quality and greater fatigue were related to pain exacerbation in persons with symptomatic hip OA. Sleep disorders and fatigue should be considered when dealing with pain exacerbations.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".