Quantifying Surgical Completeness in Patients with Aspirin Exacerbated Respiratory Disease
Bibliographic record
Abstract
BACKGROUND: Aspirin exacerbated respiratory disease (AERD) in patients who have had sinus surgery remains a management challenge. Aspirin desensitization and biologics are additional treatment options. It remains unclear if patients require a more comprehensive surgery prior to implementing such additional therapies. The purpose of this study was to quantify prior surgery completeness in AERD patients at a tertiary rhinology practice. METHODS: Paranasal sinus CT scans were reviewed by four academic rhinologists to assess surgery completeness. Using a published CT grading system, each sinus was graded on the completeness of surgery and middle turbinate reduction. A score out of 14 was calculated for each patient (7 per side). RESULTS: Sixty-one patients with AERD out of 141 available were included. Mean inter-rater agreement across all sinuses was moderate (k = 0.42). The mean completeness score was 6.7/14. The following procedures were rated as complete (means): uncinectomy (L: 84%, R: 82%, k = 0.44), maxillary (L: 83%, R: 77%, k = 0.32), middle turbinate reduction (L: 45%, R: 46%, k = 0.31), anterior ethmoid (L: 35%, R: 39%, k = 0.51), sphenoid (L: 36%, R: 35%, k = 0.4), posterior ethmoid (L: 30%, R: 30%, k = 0.48), frontal (L: 22%, R: 21%, k = 0.46). CONCLUSION: Prior surgery in AERD patients were mostly deemed incomplete. Uncinectomy and maxillary antrostomy are the most common procedures previously performed. It remains toe seen whether this would be considered 'adequate' surgery or more 'complete' surgery is required to achieve greater disease control.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".