Nasal endoscopy score thresholds to trigger consideration of chronic rhinosinusitis treatment escalation and implications for disease control
Bibliographic record
Abstract
BACKGROUND: In the absence of direct evidence supporting how to use nasal endoscopy findings to judge chronic rhinosinusitis (CRS) disease control, experts' practice patterns could provide guidance. METHODOLOGY: Participants consisted of a diverse group of twenty-nine rhinologists. Participants were presented with every possible combination of bilateral nasal endoscopy findings represented by the modified Lund-Kennedy (MLK; range: 0-12) endoscopic scoring system and Nasal Polyp Score (NPS; range: 0-8). Reflecting the practical consequence of CRS disease control assessment, participants were asked whether they would consider CRS treatment escalation based on each scenario in the absence of any CRS symptoms, and how strongly they considered escalating therapy. The same scenarios were then presented in the context of 1 burdensome CRS symptom and participants again were asked whether they would consider treatment escalation. RESULTS: The median threshold total MLK score for considering treatment escalation was ≥ 4 and 75.9% of participants' MLK thresholds were within 1 point of 4. The median threshold total NPS for considering treatment escalation was ≥ 3 and 62.5% of participants' NPS thresholds were within 1 point of 3. Endoscopy score thresholds decreased in the presence of 1 burdensome symptom and generally increased when requiring stronger affirmation for considering CRS treatment escalation. CONCLUSION: Reflecting the practice patterns of a diverse group of rhinologists, MLK score ≥ 4 or NPS ≥ 3 may serve as thresholds for considering CRS treatment escalation. Alternatively, MLK score under 4 or NPS under 3 may serve as endoscopic goals of CRS treatment. These results provide guidance for using nasal endoscopy findings as a criterion of CRS 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 | 0.013 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".