Enhanced Irrigant Delivery to the Ethmoid Sinuses Directly Following Ethmoid Punch Sinusotomy
Bibliographic record
Abstract
OBJECTIVES: Ethmoid punch sinusotomy (EPS) is a feasible treatment for ethmoid sinusitis in a subset of chronic rhinosinusitis (CRS) patients per a recent report. This adjunctive work investigates the technical characteristics of EPS and determines if EPS measurably alters the topical delivery of irrigant into the ethmoid sinuses in a cadaveric model. METHODS: The sinonasal cavities of 10 human cadaver heads were irrigated with a solution containing methylene blue and radio-opaque contrast prior to and following EPS. Procedural characteristics and irrigant distribution were assessed by endoscopy and computed tomography. RESULTS: Forty EPS procedures were performed through the ethmoid bulla and basal lamella. Compared to controls, EPS enhanced dye distribution into the anterior (90% vs 35%, P < .004) and posterior (90% vs 35%, P < .002) ethmoid sinuses, representing a 157% increase for each of these sites. Contrast was detected in a higher proportion of anterior (65% vs 5%, P < .001) and posterior (60% vs 0%, P < .001) ethmoid sinuses. Endoscopically guided catheter instillation of contrast through the EPS sites achieved radiotracer distribution throughout the ethmoid complex. CONCLUSIONS: Ethmoid punch sinusotomy sites can be reliably created via micro-minimally invasive procedures. Ethmoid punch sinusotomy improves irrigant delivery to the ethmoid sinuses, providing mechanistic understanding for the clinical outcomes observed in CRS patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".