Azithromycin in high‐risk, refractory chronic rhinosinusitus after endoscopic sinus surgery and corticosteroid irrigations: a double‐blind, randomized, placebo‐controlled trial
Bibliographic record
Abstract
BACKGROUND: Refractory chronic rhinosinusitis (CRS) remains a significant burden for patients, often leaving them with few therapeutic options that provide low-morbidity, long-term, and meaningful symptomatologic and endoscopic disease improvement. Macrolides have long been thought to offer both an immunomodulatory and antimicrobial effect. Our objective was to evaluate the efficacy of low-dose, long-term azithromycin in a carefully selected high-risk population failing appropriate medical therapy of budesonide nasal irrigations (BNIs) and endoscopic sinus surgery (ESS). METHODS: A double-blind, randomized, placebo-controlled trial was completed in a single tertiary-care center assessing the addition of 250 mg azithromycin, 3 times per week for 16 weeks, in adults failing ESS and high-volume BNIs. Associated comorbidities, as well as symptomatologic, microbiologic, and serologic values, were systematically collected. RESULTS: A total of 128 patients were enrolled and underwent ESS followed by BNI. At the 4-month post-ESS visit, 48 patients showed disease persistence and were randomized to azithromycin or placebo. Overall, azithromycin, when compared with placebo, did not show a statistically significant difference in disease clearance (54% vs 33%, respectively; p = 0.146), although patients with disease clearance who were on azithromycin showed significantly better 22-item Sino-Nasal Outcome Test score improvements than patients on placebo (18 vs -0.9, respectively; p = 0.046). In a subgroup analysis excluding aspirin-exacerbated respiratory disease (AERD) patients, azithromycin significantly improved disease clearance when compared with placebo (71% vs 35%, respectively; p = 0.031), with a number needed to treat of 3 (2.8). CONCLUSION: Low-dose azithromycin is a therapeutic option with few side effects. Its use can show favorable clinical outcomes in this difficult-to-treat population, especially if patients are AERD-negative.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".