Effects of Fluticasone Furoate on Clinical and Immunological Outcomes (IL-17) for Patients With Nasal Polyposis Naive to Steroid Treatment
Bibliographic record
Abstract
OBJECTIVES: We investigated the effect of topical steroids on clinical outcomes and related immune response of chronic rhinosinusitis with nasal polyp (CRSwNP) patients and in eradicating some polyps. We want to explore a new potential mechanism linked to Th-17 cells. METHODS: Prospective, double-blind, placebo-controlled studies with 24 allergic and nonallergic patients were randomized to either placebo or fluticasone furoate for 12 weeks. Assessment of clinical response, endoscopic score with biopsies of the inferior turbinate, and polyps before and after treatment were performed. Biopsies were stained for T-cells, eosinophils, neutrophils, and IL-17A/F. RESULTS: Steroid treatment improved the mean symptoms scores from 7.12 to 4.02 (P < .01) and the polyp score from 5.13 to 3.31 (P < .05), but the comparison with placebo was not statistically significant in nonallergics due to insufficient study power. Steroid treatment decreased eosinophil counts on allergics but not neutrophils or T-cells. The IL-17A/F expression was higher in nonallergics with high neutrophil counts and was inclined by steroids. Compared to baselines, IL-17 cells were significantly less in allergic individuals and were not observed in allergics and with high neutrophil counts. CONCLUSION: Topical steroids were more effective on certain nasal polyp phenotypes. Identification of polyp phenotype might be essential to ensure a better therapeutic response to intranasal corticosteroids.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".