Adenoma Detection Rates Decline with Increasing Procedural Hours in an Endoscopist’s Workload
Bibliographic record
Abstract
BACKGROUND: Operator fatigue may negatively influence adenoma detection (AD) during screening colonoscopy. OBJECTIVE: To better characterize factors affecting AD, including the number of hours worked, and the number and type of procedures performed before an index screening colonoscopy. METHODS: A retrospective cohort study was conducted involving individuals undergoing a screening colonoscopy at a major tertiary care hospital in Montreal, Quebec. Individuals were identified using an endoscopic reporting database; AD was identified by an electronic chart review. A hierarchical logistic regression analysis was performed to determine the association between patient- and endoscopist-related variables and AD. RESULTS: A total of 430 consecutive colonoscopies performed by 10 gastroenterologists and two surgeons were included. Patient mean (± SD) age was 63.4±10.9 years, 56.3% were males, 27.7% had undergone a previous colonoscopy and the cecal intubation rate was 95.7%. The overall AD rate was 25.7%. Age was associated with AD (OR 1.06 [95% CI 1.03 to 1.08]), while female sex (OR 0.44 [95% CI 0.25 to 0.75]), an indication for average-risk screening (OR 0.47 [95% CI 0.27 to 0.80]) and an increase in the number of hours during which endoscopies were performed before the index colonoscopy (OR 0.87 [95% CI 0.76 to 0.99]) were associated with lower AD rates. On exploratory univariable analysis, a threshold of 3 h of endoscopy time performed before the index colonoscopy was associated with decreased AD. CONCLUSION: The number of hours devoted to endoscopies before the index colonoscopy was inversely associated with AD rate, with decreased performance possibly as early as within 3 h. This metric should be confirmed in future studies and considered when optimizing scheduling practices.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".