Aspirin desensitization for aspirin‐exacerbated respiratory disease (Samter's Triad): a systematic review of the literature
Bibliographic record
Abstract
OBJECTIVES: To critically review the current literature regarding aspirin desensitization treatment for nasal polyposis in patients with Aspirin-Exacerbated Respiratory Disease (AERD). STUDY DESIGN: Systematic review of the literature. METHODS: All English literature published between January 1995 and February 2013 reporting specifically nasal outcomes following aspirin desensitization in AERD patients were eligible for inclusion. Exclusion criteria were non-investigative, non-human, and ex-vivo studies. Studies were categorized by level of evidence and evaluated for quality using the Downs and Black scale. RESULTS: A total of 614 citations were retrieved and eleven studies met the criteria for analysis. Outcome measurements included self-reported symptom scores, amount of corticosteroid use, rate of revision surgery, and quantitative measurements such as rhinomanometry. Overall, most studies reported a significant improvement in symptom scores, decrease in corticosteroid use, and decrease in revision surgery. A few studies showed promising results with quantitative outcomes. However, most studies were of Level 2 evidence with small samples sizes. Rates of adverse events ranged from 12.5% to 23%. CONCLUSIONS: Unlike traditional treatments for nasal polyposis, aspirin desensitization targets AERD etiology rather than phenotype and can be an effective therapeutic option. While the current literature shows encouraging results, additional studies are needed to better define clinical benefits.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".