Sleep quality and disease severity in patients with chronic rhinosinusitis
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To evaluate sleep quality in patients with chronic rhinosinusitis (CRS) using a validated outcome measure and to compare measures of CRS disease severity with sleep dysfunction. STUDY DESIGN: Cross-sectional evaluation of a multi-center cohort. METHODS: According to the 2007 Adult Sinusitis Guidelines, patients with CRS were prospectively enrolled from four academic, tertiary care centers across North America. Each subject completed the Pittsburgh Sleep Quality Index (PSQI) instrument, in addition to CRS-specific measures of quality-of-life (QOL), endoscopy, computed tomography (CT), and olfaction. Patient demographics, comorbid conditions, and clinical measures of disease severity were compared between patients with "good" (PSQI; ≤5) and "poor" (PSQI; > 5) sleep quality. RESULTS: Patients (n = 268) reported a mean PSQI score of 9.4 (range: 0-21). Seventy-five percent of patients reported PSQI scores above the traditional cutoff, indicating poor sleep quality. Patients with poor sleep quality were found to have significantly worse QOL scores on both the Rhinosinusitis Disability Index (P < 0.001) and 22-item Sinonasal Outcome Test (P < 0.001). No significant differences in average endoscopy, CT, or olfactory function scores were found between patients with good or poor sleep quality. Tobacco smokers reported worse average PSQI total scores compared to nonsmokers (P = 0.030). Patients reporting poor sleep were more likely to have a history of depression, even after controlling for gender (P = 0.020). CONCLUSION: The majority of patients with CRS have a poor quality of sleep, as measured by the PSQI survey. Poor sleep quality is significantly associated with CRS-specific QOL, gender, comorbid depression, and tobacco use, but not CT score or endoscopy grade. LEVEL OF EVIDENCE: 2b.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".