Prospective evaluation of preoperative concern among patients considering endoscopic sinus surgery: initial validation
Bibliographic record
Abstract
BACKGROUND: Patients considering surgery face many uncertainties and concerns. This investigation aimed to develop an objective assessment tool for characterizing the areas of greatest concern among patients considering endoscopic sinus surgery (ESS). METHODS: As part of validating a clinical measure concerning perioperative concerns, patients presenting with chronic rhinosinusitis with or without nasal polyposis were voluntarily recruited. A total of 30 individuals completed a novel 19-item questionnaire during their initial clinical visit and again 3 days later. Outcomes included descriptive statistics and test-retest reliability. RESULTS: Data suggest that patient responses did not vary with age or gender. The questionnaire demonstrated strong test-retest reliability, with alpha values from 0.881 to 0.942. Between-rater reliability was consistent, with an average intraclass correlation coefficient (ICC) of 0.913. No relationships between question order and patient response was identified. CONCLUSION: Patients considering ESS have concerns that remain stable in the early preoperative period requiring surgeon-initiated inquiry and counsel. This is the first study to evaluate preoperative patient concerns, and initially establishes the Western Surgical Concern Inventory-ESS (WSCI-ESS) as a means of ensuring adequate patient counseling and a method of evaluating perioperative patient education.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".