Consensus criteria for chronic rhinosinusitis disease control: an international Delphi Study
Bibliographic record
Abstract
BACKGROUND: Chronic rhinosinusitis (CRS) disease control is a global metric of disease status for CRS. While there is broad acceptance that it is an important treatment goal, there has been inconsistency in the criteria used to define CRS control. The objective of this study was to identify and develop consensus around essential criteria for assessment of CRS disease control. METHODS: Modified Delphi methodology consisting of three rounds to review a list of 24 possible CRS control criteria developed by a 12-person steering committee. The core authorship of the multidisciplinary EPOS 2020 guidelines was invited to participate. RESULTS: Thirty-two individuals accepted the invitation to participate and there was no dropout of participants throughout the entire study (3 rounds). Consensus essential criteria for assessment of CRS control were: overall symptom severity, need for CRS-related systemic corticosteroids in the prior 6 months, severity of nasal obstruction, and patient-reported CRS control. Near-consensus items were: nasal endoscopy findings, severity of smell loss, overall quality of life, impairment of normal activities and severity of nasal discharge. Participants’ comments provided insights into caveats of, and disagreements related to, near-consensus items. CONCLUSIONS: Overall symptom severity, use of CRS-related systemic corticosteroids, severity of nasal obstruction, and patient-reported CRS control are widely agreed upon essential criteria for assessment of CRS disease control. Consideration of near-consensus items to assess CRS control should be implemented with their intrinsic caveats in mind. These identified consensus CRS control criteria, together with evidence-based support, will provide a foundation upon which CRS control criteria with wide-spread acceptance can be developed.
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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 | 0.209 | 0.187 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".