What is the optimal outcome after endoscopic sinus surgery in the treatment of chronic rhinosinusitis? A consultation of Canadian experts
Bibliographic record
Abstract
Abstract Objectives Many experts feel that in the absence of well-defined goals for success, they have an easier time identifying failure. As success ought to not be defined only by absence of failure, we aimed to define optimal outcomes for endoscopic sinus surgery (ESS) in chronic rhinosinusitis (CRS) by obtaining expert surgeon perspectives. Methods A total of 12 surgeons participated in this targeted consultation. Face to face semi-structured interviews were performed with expert surgeons in the field of CRS and ESS. General impressions and personal definitions of acceptable operative success and optimal operative outcomes were compiled and summarized. Results According to an expert survey, patients’ main objectives are an improvement in their chief complain, a general improvement in quality of life (QoL), and a better overall symptomatic control. The most important aspects of endoscopy for defining a successful intervention were an adequate mucus circulation, a healthy mucosa, minimal edema, and patency of all explored cavities or ostia. In the assessment of surgical outcomes, it was determined that both objective and patient reported data must be carefully examined, with more attention given to subjective outcomes. Conclusions According to data gathered from a Canadian expert consultation, a definition of success must be based on both subjective data and nasal endoscopy. We propose to define an acceptable outcome as either a subjective improvement of at least the minimal clinically improvement difference of a validated patient reported outcome questionnaire, along with a satisfactory endoscopic result (1) or a complete subjective resolution with a sub-optimal endoscopy (2). Graphical abstract
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".