Productivity changes following medical and surgical treatment of chronic rhinosinusitis by symptom domain
Bibliographic record
Abstract
BACKGROUND: Chronic rhinosinusitis (CRS) is associated with substantial productivity losses. Prior cross-sectional study has identified risk factors and symptom subdomains contributing to baseline productivity loss. This study evaluates correlations between posttreatment changes in symptom subdomain and productivity loss. METHODS: A total of 202 adult patients with refractory CRS were prospectively enrolled into an observational, multi-institutional cohort study between August 2012 and June 2015. Respondents provided pretreatment and posttreatment 22-item Sino-Nasal Outcome Test (SNOT-22) scores. Productivity losses were monetized using measures of absenteeism, presenteeism, lost leisure time, and U.S. government-estimated wage and labor rates. RESULTS: A total of 39 (19%) participants elected continued appropriate medical therapy (CAMT) and 163 (81%) elected endoscopic sinus surgery (ESS). CAMT patients experienced improvement in SNOT-22 total and rhinologic subdomain scores (both p ≤ 0.039). ESS patients reported improvement in SNOT-22 total scores and all subdomains (all p < 0.001). Mean monetized productivity losses were nearly unchanged following CAMT (-$200, p = 0.887) but significantly reduced following ESS (-$5,015, p < 0.001). Mean productivity losses were reported in CAMT patients reporting worse mean posttreatment extra-rhinologic, psychological, and sleep symptom severity scores; however, no statistically significant linear correlations (r ≤ 0.249; p ≥ 0.126) were reported. CONCLUSION: Treatment modalities associate with different posttreatment productivity changes. Patients electing ESS experienced postoperative improvement in productivity distributed across all SNOT-22 symptom domains, suggesting productivity improvement correlates with multiple symptom domains. Patients electing CAMT had better baseline productivity compared to patients electing ESS, and this productivity level was maintained through treatment. Greater productivity loss occurred in patients with worse SNOT-22 scores in the extra-rhinologic, psychological, and sleep subdomains.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".