Effect of a dexamethasone Sinu‐Foam <sup>TM</sup> middle meatal spacer on endoscopic sinus surgery outcomes: A randomized, double‐blind, placebo‐controlled trial
Bibliographic record
Abstract
BACKGROUND: Off-label drug eluting middle-meatal spacers have shown promising results for improving clinical outcomes following endoscopic sinus surgery (ESS) for chronic rhinosinusitis (CRS). This study evaluates a dexamethasone Sinu-Foam™ spacer following ESS for CRS without nasal polyposis (CRSsNP). METHODS: Patients with CRSsNP (n = 36) were enrolled into a double-blind, placebo-controlled trial and randomized into either a treatment arm (dexamethasone Sinu-Foam™ mixture; n = 18) or placebo arm (Sinu-Foam™ alone; n = 18). Therapeutic outcomes were evaluated at 1 week, 4 weeks, and 3 months using sinonasal endoscopy and graded using the Lund-Kennedy scoring system. Postoperative care included nasal saline irrigations and a short course of systemic steroids. RESULTS: All patients completed the study follow-up period. Both study arms experienced significant improvement in endoscopic grading over the study duration (p < 0.001). There was no difference in average endoscopic scores between the treatment and placebo groups at 1 week, 4 weeks, and 3 months (all p > 0.489). CONCLUSION: This study demonstrated that an off-label drug-eluting middle-meatal spacer of dexamethasone and Sinu-Foam™ does not improve endoscopic outcomes in the early postoperative period following ESS when combined with postoperative saline irrigations and a short course of systemic steroids.
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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) | 0.006 | 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".