Health utility values for patients with recurrent acute rhinosinusitis undergoing endoscopic sinus surgery: a nested case control study
Bibliographic record
Abstract
BACKGROUND: Health utility scores quantify an individual's valuation of particular health states and are vital components of health economic studies and cost-effectiveness research. We sought to characterize health utility values for patients with recurrent acute rhinosinusitis (RARS) both before and after endoscopic sinus surgery (ESS), as well as compare health utility to chronic rhinosinusitis without nasal polyposis (CRSsNP). METHODS: Patients with RARS (n = 20) and CRSsNP (n = 20) undergoing ESS were enrolled as part of a longitudinal, observational, prospective cohort. Case patients diagnosed with RARS were age- and gender-matched to controls with CRSsNP using a nested case-control design at a 1:1 ratio. Health utility was measured using the Medical Outcomes Study Short Form-6D (SF-6D) survey. RESULTS: Patients with RARS were followed for an average of 14.0 ± 6.1 (mean ± standard deviation) months compared to an average of 14.4 ± 5.3 months for CRSsNP controls (p = 0.779). Mean preoperative SF-6D health utility scores were statistically comparable between RARS (0.71 ± 0.14) and CRSsNP (0.66 ± 0.12; p = 0.341). Both patients with RARS and CRSsNP reported significant postoperative improvement in SF-6D scores from 0.71 ± 0.14 to 0.79 ± 0.13 (p = 0.031) and from 0.66 ± 0.12 to 0.77 ± 0.13 (p = 0.004), respectively. No difference in last postoperative SF-6D scores were found between RARS and CRSsNP (p = 0.583) or in the average magnitude of postoperative improvement (0.08 ± 0.16 vs 0.11 ± 0.13; p = 0.620). CONCLUSION: Patients with RARS and CRSsNP report significant impairment in health utility as measured by the SF-6D. ESS significantly improves health utility in patients with RARS and CRSsNP to near normative values. These data will help inform future economic analysis and cost-effectiveness research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".