NSAID-ERD and disease burden among patients with chronic rhinosinusitis with nasal polyps in the AROMA registry
Bibliographic record
Abstract
Introduction Patients with chronic rhinosinusitis with nasal polyps (CRSwNP) and coexisting non-steroidal anti-inflammatory−exacerbated respiratory disease (NSAID-ERD) have more severe CRSwNP and lower quality of life. This study characterizes CRSwNP patients with NSAID-ERD initiating dupilumab in real-world practice. Methods AROMA (NCT04959448) is a prospective global registry, recruiting adults with CRSwNP initiating dupilumab. Quality of life assessments included the 22-item Sino-Nasal Outcome Test (SNOT-22; range 0–110) and total symptom score (TSS; 0–9). Results As of February 2023, the study had recruited 303 patients (mean [SD] SNOT-22 and TSS of 45.4 [22.2] and 5.4 [2.3], respectively). Among patients self-reporting history of NSAID-ERD (n=78), scores were 46.5 (21.5) and 5.7 (2.2), respectively. Mean (SD) age at NSAID-ERD diagnosis was 39.3 (11.8) years. Of the patients with previous surgery (n=187), 51 (27.3%) had NSAID-ERD. Among all patients with NSAID-ERD, 11 (14.1%) had undergone confirmatory aspirin challenge, 11 (14.1%) aspirin desensitization, and 15 (19.2%) reported adverse reaction to alcohol consumption. Conclusion A quarter of adults with CRSwNP initiating dupilumab in AROMA report having NSAID-ERD, many with high disease burden. However, most have not undergone aspirin challenge or desensitization to confirm their diagnosis. Publication History Article published online: 19 April 2024 © 2024. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".