Radiological score, asthma and NSAID‐exacerbated respiratory disease predict relapsing chronic rhinosinusitis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: The aim was to evaluate the predictive potential of Sinonasal Radiological (SR) and the Lund-Mackay (LM) score of sinus computed tomography (CT) scans on postoperative relapses of chronic rhinosinusitis (CRS). MATERIALS AND METHODS: CRS patients (n = 483, 12-80 years) underwent routine sinus CT scans. The SR score was defined by obstructed frontal recess (0 = no, 1 = yes) and visualization of middle and inferior turbinate (0 = anatomy can be easily visualized, 1 = anatomy cannot be easily visualized) on each side (a total of 0-6 points). Associations were analyzed by nonparametric, survival and Cox's proportional hazard models. RESULTS: Revision endoscopic sinus surgery (ESS) was performed in 133 (28.0%) patients on average (min-max) of 3.2 (0-12) years after performing the sinus CT scans. Of the 408 patients who underwent the baseline ESS, high preoperative SR or LM scores significantly predicted revision ESS (p < 0.001) and peroral corticosteroid courses purchased during the follow-up (p = 0.009 and p < 0.001, respectively for SR- and LM-scores). In multivariable analysis, both SR score and asthma and/or NSAID exacerbated respiratory disease (N-ERD) were significantly associated with revision ESS risk (p = 0.035, p = 0.007, respectively). CONCLUSION: LM and SR and a history of asthma or N-ERD predict CRS relapses, which may help in decision-making.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it