Optimal endoscopic localization of colorectal neoplasms: a comparison of rural versus urban documentation practices
Bibliographic record
Abstract
BACKGROUND: Colonoscopy is the gold standard for diagnosing colorectal neoplasms. However, colonoscopy is often repeated preoperatively due to non-standard documentation and inconsistent practices by index endoscopists. Repeat endoscopies result in treatment delays and can increase risks of complications. National consensus recommendations were recently developed for optimal endoscopic colorectal lesion localization. We aimed to assess baseline colonoscopy practice differences from the new recommendations with a focus on geographical variability in report quality between urban and rural referral sites. METHODS: We performed a retrospective review of patients who underwent elective surgery for colorectal neoplasms at a single institution in Winnipeg between 2007-2020. We compared endoscopy report quality to the national recommendations with charts stratified by endoscopy location. Our primary outcomes were overall report documentation completeness and use of recommended practices. RESULTS: One hundred ninety-four patients were included (97 rural, 97 urban). The mean overall compliance with the recommendations for urban endoscopies was marginally better compared to rural endoscopies (50% vs. 48%, p = 0.04). Sixty-eight percent of the reports complied with tattoo indications (72% urban; 63% rural, p = 0.16). On average, reports included 29% of recommended tattoo information (30% urban; 28% rural, p = 0.25) and demonstrated 74% appropriate tattoo technique (70% urban; 81% rural, p = 0.10). Twenty-one percent of reports included photographs of lesions in accordance with the national recommendations (28% urban; 13% rural, p = 0.01). CONCLUSIONS: Endoscopists frequently omit recommended practices for optimal colorectal lesion localization. Rural reports miss more recommended information compared to urban reports. Future research is needed to facilitate province-wide high-quality endoscopy reporting for patients regardless of endoscopy location.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".