A double-blind randomised controlled trial of gloved versus ungloved merocel middle meatal spacers for endoscopic sinus surgery
Bibliographic record
Abstract
BACKGROUND: Middle meatal spacers are commonly used following endoscopic sinus surgery to prevent post-operative bleeding and lateralization of the middle turbinates. The effects of nasal packing on post-operative sinonasal mucosal healing remain unknown in humans. OBJECTIVE: This study aims to compare the histopathalogical effects of Merocel and Merocel covered with a finger glove on mucosal healing, and patients` discomfort immediately post-operatively after endoscopic sinus surgery and at removal of the nasal packing. METHODS: Thirty-seven patients with chronic rhinosinusitis undergoing bilateral endoscopic sinus surgery were enrolled in a prospective study. Patients were randomized and blinded to receive Merocel middle meatal spacer (MMMS) in one nostril and finger glove Merocel middle meatal spacer (FGMMS) in the contra lateral side. Patients were seen on post-operative day 6, and completed a visual analogue score reporting the post-operative discomfort from nasal packing on each side. Following the removal of nasal packing, patients indicated which side caused more discomfort on removal. Biopsies were taken from the middle turbinates and sent to a blinded pathologist who scored the level of mucosal inflammation from 0 - 4. RESULTS: There was no statistically significant difference between MMMS and FGMMS in regards to their effect on sinonasal mucosal inflammation and discomfort post-operatively. A statistically significant difference was noted with respect to discomfort at removal with the uncovered Merocel more likely to cause discomfort when compared to the Merocel covered in a glove finger. CONCLUSION: MMMS and FGMMS are equivalent in the amount of sinonasal mucosal inflammation and discomfort post endoscopic sinus surgery. However, the main advantage of the FGMMS was a significant reduction in pain on removal when compared with the MMMS.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".