The impact of comorbid depression in chronic rhinosinusitis on post-operative sino-nasal quality of life and pain following endoscopic sinus surgery
Bibliographic record
Abstract
BACKGROUND: Depression and chronic pain are debilitating disorders that co-exist with many chronic diseases. Chronic rhinosinusitis (CRS) is no exception. Nonetheless, little is known about the association between these co-related conditions and the treatment of CRS. The objective of this study is to measure outcomes following endoscopic sinus surgery (ESS) in CRS patients reporting significant pre-operative depression and pain. METHODS: This is a prospective longitudinal cohort study examining patients with CRS who had failed maximal medical therapy and subsequently underwent ESS. Participants completed a several patient-reported outcome (PRO) instruments pre-operatively and 6 months post-operatively. The PROs included the Sinonasal Outcome Test-22 (SNOT-22), the Patient Health Questionnaire (PHQ-9) measuring symptoms of depression and an assessment of chronic pain using the pain intensity (P), interference with enjoyment of life (E) and general (G) activity instrument, the PEG instrument. RESULTS: The study had 142 participants complete their pre-operative and post-operative surveys. The participation rate was 40.1% among eligible patients. The prevalence of at least moderate depression was 22 patients (15.5%) among participants. Compared with non-depressed participants, the pre-operative sino-nasal disease burden and pain scores were higher among depressed participants (p < 0.001) and the gain in health following surgery was smaller (p < 0.001). CONCLUSIONS: Pre-operative disease burden is higher among depressed patients. Post-operative gains in sino-nasal quality of life attributable to endoscopic sinus surgery were significantly smaller among depressed participants. Pre-operative screening for depression could identify opportunities for medical intervention and improve outcomes among CRS patients.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".