The effect of endoscopic sinus surgery on quality of life and absenteeism in patients with chronic rhinosinuitis - a multi-centre study
Bibliographic record
Abstract
BACKGROUND: Chronic rhinosinusitis with and without nasal polyps (CRSw/sNP) are common conditions decreasing health-related quality of life (HRQOL). Individual symptoms capable of predicting outcome after endoscopic sinus surgery (ESS) are poorly defined, and the indirect costs of CRS is rarely reported in Europe. METHODOLOGY: Patients with CRSw/sNP admitted for ESS were prospectively enrolled. Patients completed the 22 Sinonasal Outcome Test (SNOT-22), the short-form 36-item questionnaire (SF-36), a Visual Analogue Scale (VAS) and reported CRS-related absenteeism pre- and post-operatively. RESULTS: 181 patients were included. The SNOT-22 score diminished from 51.8 (48.7-55.0) pre-operatively to 33.0 (29.2-36.8) at 6 months. 64% achieved a clinically important improvement in the SNOT-22. SF-36 scores improved statistically significantly in all domains except Role Emotional. The VAS score halved from 68 (65-71) to 34 (29-39) at 6 months post-operatively. A pre-operative SNOT-22 score over 20 implied a greater chance of score improvement after 6 months. A multivariate model identified individual items associated with SNOT-22. Further, patients that had lees than 12 months of sinus disease derived greatest benefit. CRS-related absenteeism dropped from 8-14 days to 1-7 days 12 months after ESS. CONCLUSIONS: This prospective study showed that ESS significantly improved the HRQOL and decreased absenteeism of patients with CRSw/sNP. Shorter duration of disease and Need to blow nose and Blockage/congestion of nose of SNOT-22 were identified as predictive factors for good surgical outcome.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".