Incidence and burden of comorbid pain and depression in patients with chronic rhinosinusitis awaiting endoscopic sinus surgery in Canada
Bibliographic record
Abstract
BACKGROUND: This study sheds important light on the association between sino-nasal symptoms and global quality of life in patients with chronic rhinosinusitis waiting for endoscopic sinus surgery. Using patient-reported information collected pre-operatively, the primary objective was to report on patients' pre-surgical sino-nasal symptoms and their association with self-reported pain and depression. The secondary objective was to report on levels of depression and pain among patients in the sample reporting severe sleep problems. METHODS: This is a cross-sectional study of patient-reported outcomes collected prospectively from a cohort of 261 patients assigned to the wait list for elective endoscopic sinus surgery in a large urban region of Canada. RESULTS: Younger patients and patients with other medical comorbidities were most likely to report significant symptoms of chronic rhinosinusitis and substantial associated pain and depression. In the primary analyses, patients reporting significant symptoms of chronic rhinosinusitis were more likely to report moderate depression or high pain (p < 0.01). Subsequently, chronic rhinosinusitis patients with severe sleep problems were 82% likely to report moderate or severe depression and pain. CONCLUSION: Preoperative management of depression and pain may be considered in order to improve the health-related quality of life of patients waiting for ESS. As depression and pain were highly prevalent, patients with severe sleep problems may be candidates for prioritized access.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".