Subjective Sleep Disruption and Mood Disorders are Associated with the Risk of Chronic Pain in Patients with Obstructive Sleep Apnea
Bibliographic record
Abstract
Objective: This study aimed to determine the prevalence of chronic pain and its risk factors in patients with obstructive sleep apnea (OSA). Methods: A total of 145 patients diagnosed with OSA were consecutively recruited from the Sleep Medicine Center in West China Hospital. All patients were divided into two groups including OSA with and without chronic pain. They were assessed the subjective sleep (Pittsburgh Sleep Quality Index, Insomnia Severity Index), objective sleep (polysomnography), mood symptoms (Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale), and pain characteristics (Short-Form McGill Pain Questionnaire). Demographic, clinical, subjective and objective sleep parameters were compared between OSA patients with and without chronic pain. Binary logistic regression models and linear regression models were used to examine the risk factors of chronic pain in OSA. Results: Fifty-five (37.9%) patients with OSA were diagnosed with chronic pain. There were more severe subjective sleep disruption and symptoms of anxiety and depression in patients with chronic pain compared to those without chronic pain. After controlling for potential confounders, poor subjective sleep quality and severe insomnia and mood disorders (all p s < 0.05), but not objective sleep fragmentation or nocturnal hypoxemia (all ps > 0.05) were associated with the increased risk of pain and pain intensity, respectively. Conclusion: More than one-third of patients with OSA had chronic pain. Subjective sleep disruption and mood disorders are the risk factors of chronic pain in OSA. Our findings suggest that subjective sleep quality should be valued highly in the relationship between OSA and pain. Keywords: obstructive sleep apnea, subjective sleep disruption, insomnia, anxiety, depression, chronic pain
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".