Consensus on the management of united airways disease with type 2 inflammation: a multidisciplinary Delphi study
Bibliographic record
Abstract
BACKGROUND: Scientific evidence on patients with multimorbid type 2 asthma and chronic rhinosinusitis with nasal polyps (CRSwNP) from a united airways disease (UAD) perspective remains scarce, despite the frequent coexistence of these entities. We aimed to generate expert consensus-based recommendations for the management of UAD patients. METHODS: Using a two-round Delphi method, Spanish expert allergists, pulmonologists and otolaryngologists expressed their agreement on 32 statements (52 items) on a 9-point Likert scale, classified as appropriate (median 7-9), uncertain (4-6) or inappropriate (1-3). Consensus was considered when at least two-thirds of the panel scored within the range containing the median. RESULTS: A panel of 30 experts reached consensus on the appropriateness of 43 out of the 52 (82.7%) items. The usefulness of certain biomarkers (tissue and peripheral blood eosinophil count, serum total IgE, and fraction of exhaled nitric oxide [FeNO]) in the identification and follow-up of type 2 inflammation, and assessment of the response to biologics, were agreed. Some of these biomarkers were also associated with disease severity and/or recurrence after endoscopic sinus surgery (ESS). Consensus was achieved on treatment strategies related to the prescription of anti-IL-4/IL-13 or anti-IgE agents, concomitant treatment with systemic corticosteroids, and combining or switching to biologics with a different mechanism of action, considering a number of UAD clinical scenarios. CONCLUSION: We provide expert-based recommendations to assist in clinical decision-making for the management of patients with multimorbid type 2 asthma and CRSwNP. Specific clinical trials and real-world studies focusing on the single-entity UAD are required to address controversial items.
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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 | 0.231 | 0.200 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".