Interrater reliability of endoscopic parameters following sinus surgery
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To determine the interrater reliability of a set of postoperative endoscopic scoring parameters in patients with chronic rhinosinusitis who have undergone endoscopic sinus surgery (ESS). STUDY DESIGN: Prospective cohort with retrospective review. METHODS: One hundred twenty video-endoscopic evaluations in 20 subjects recorded at 14, 30, and 45 days after ESS were scored in real time by the clinical investigators who performed the endoscopies and recorded the videos and retrospectively by an independent panel of four sinus surgeons who were blinded to all information. The scoring parameters included categoric grading for adhesion formation and middle turbinate position and continuous grading (visual analog scale) for degree of inflammation and crusting. Interrater reliability of the panel members was assessed using the Fleiss kappa test, bias index and prevalence index for categoric data, and the Shrout-Fleiss test for continuous data. The level of agreement between the panel and the real-time clinical investigator was also assessed. RESULTS: For categoric variables, strong agreement between raters on the panel was found for both middle turbinate position (kappa=0.499, prevalence index=0.925) and adhesions (kappa=0.364, prevalence index=0.829). For continuous data, good agreement between raters was found for both inflammation (reliability coefficient=0.554) and crusting (reliability coefficient=0.620). Real-time investigator scoring and panel scoring showed strong agreement. CONCLUSIONS: These results suggest that the endoscopic scoring parameters assessed (middle turbinate position, adhesions, inflammation, and crusting) have acceptable interexaminer reproducibility and are suitable for evaluating ESS outcomes in the postsurgical period.
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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 | 0.034 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".