Impact of topical nasal steroid therapy on symptoms of nasal polyposis
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Topical steroid therapy is an important strategy in the management of chronic rhinosinusitis (CRS) with nasal polyposis. The objective of this study was to determine the impact of topical steroid therapy on nasal symptoms in patients with nasal polyposis. STUDY DESIGN: Systematic review with meta-analysis using standardized methodology. METHODS: Study inclusion criteria included: randomized, placebo controlled trials, nasal polyposis, and topical steroid therapy. Exclusion criteria included: failure to report at least one symptom-based outcome measure, concurrent use of systemic steroids, or mixed CRS cohorts (polyp and nonpolyp patients). Quantitative analysis was performed using a random effect model. The PRISMA guidelines for meta-analysis reporting were followed. RESULTS: A total of 19 studies fulfilled eligibility. Seven studies were excluded from the meta-analysis due to significant heterogeneity in outcome reporting. A total of 12 studies were combined for quantitative analysis and demonstrated a pooled risk ratio of 1.72 (95% confidence interval, 1.41-2.09), indicating a significant improvement in nasal symptoms. All three topical steroid preparations (fluticasone, mometasone, and budesonide) resulted in symptom improvement. All seven studies excluded from the meta-analysis qualitatively confirmed the overall findings. CONCLUSIONS: Topical nasal steroid therapy improves nasal symptoms in CRS patients with nasal polyposis. Future studies will need to evaluate the impact on quality of life, preferably using validated disease-specific instruments.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.016 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".