Post-polypectomy surveillance: follow-up recommendations from the Alberta Colorectal Cancer Screening Program
Bibliographic record
Abstract
In 2013, the Alberta Colorectal Cancer Screening Program (ACRCSP) initially published recommendations for post-colonoscopy follow-up and polypectomy. Over time, emerging evidence and evolving surveillance guidelines from various expert groups necessitated a comprehensive review to align with the healthcare landscape in Alberta. To accomplish this, an expert panel was convened. Using the Agree II tool, we identified high-quality Clinical Practice Guidelines that were relevant to the Alberta medical context. Recommendations from these guidelines were adapted to fit the specific needs of Alberta. Recognizing inconsistencies and gaps within the existing guidelines, we conducted targeted literature reviews to ensure a comprehensive and evidence-based approach to our recommendations. Our revised recommendations build upon the assumption that a high-quality index colonoscopy has been performed at baseline. They are intended to enhance the quality of care and reduce unnecessary procedures. As well, they align with the growing consensus in the scientific literature that individuals with low-risk tubular adenomas may not require aggressive colonoscopy surveillance. The updated Alberta recommendations aim to provide clear recommendations for practicing endoscopists, referring physicians, and their patients. They address crucial questions such as determining which patients should commence surveillance via colonoscopy and which individuals should return to average-risk screening using the fecal immunochemical test (FIT). Additionally, our recommendations outline the appropriate surveillance intervals for those requiring continued monitoring.
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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 | 0.028 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".