Association of olfactory dysfunction in chronic rhinosinusitis with economic productivity and medication usage
Bibliographic record
Abstract
BACKGROUND: Chronic rhinosinusitis (CRS) has significant impacts upon productivity, economic metrics, and medication usage; however, factors that are associated with these economic outcomes are unknown. METHODS: We evaluated olfactory dysfunction in 221 patients with CRS using the Questionnaire of Olfactory Disorders-Negative Statements (QOD-NS) and the 40-item Smell Identification Test (SIT) and assessed whether an association existed between these olfactory metrics and healthcare utilization, productivity, and medication usage over the preceding 90 days. RESULTS: After adjusting for CRS-associated comorbidities, objective measures of disease, demographics, and CRS-specific quality of life (QOL), patients with lower QOD-NS scores (worse patient-reported olfaction) had more missed days of normal productivity and employment, worse productivity levels, more hours of missed employment due to physician visits, more time caring for sinuses, greater distance traveled to medical appointment, more days of oral steroid use, and higher odds of being on disability insurance. Clinical olfaction, as measured by SIT, was associated with greater distance traveled to medical appointment and higher odds of being on disability insurance, but did not correlate with other productivity measures. CONCLUSION: Impaired olfactory-specific QOL is associated with significantly worse economic and productivity metrics and increased medication usage even after adjusting for CRS-specific comorbidities, objective measures of disease, demographics, and severity of CRS-specific QOL. Future studies are warranted to determine if targeting the impaired olfactory-specific QOL noted in patients with CRS results in improved productivity and economic outcomes.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".