Middle meatal spacers for the prevention of synechiae following endoscopic sinus surgery: a systematic review and meta‐analysis of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Middle meatal (MM) synechiae is the most common complication following endoscopic sinus surgery (ESS) for chronic rhinosinusitis. To prevent synechiae formation, a variety of MM spacers have been employed, with varying success in the reported literature. There remains a continued debate on whether MM spacers actually reduce the risk of synechiae following ESS. METHODS: The Preferred Reporting of Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was used for reporting this review of randomized controlled trials evaluating the effectiveness of MM spacers compared to no spacers in patients undergoing ESS. Where appropriate, a meta-analysis on outcome data using a random effects model was performed. RESULTS: Eight randomized controlled trials were included in this systematic review. A pooled analysis on relevant trials found a nonsignificant trend favoring MM spacers compared to no spacers for the prevention of synechiae following ESS (relative risk [RR], 0.40; 95% confidence interval [CI], 0.14-1.12). Subgroup analysis suggested that nonabsorbable spacers (NAS) may be more effective than absorbable spacers (AS) for reducing the risk of synechiae compared to no spacers. CONCLUSION: MM spacers may be more effective than no spacers for the prevention of synechiae following ESS, especially when employing the use of an NAS. However, significant heterogeneity is observed among included trials and future studies are needed to further validate these findings.
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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 | 0.013 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.035 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".