The Value of One Year Post-Operative Colonoscopy in the Surveillance of Cancer of the Colon and Rectum
Bibliographic record
Abstract
Intensive follow-up of cancer of the colon and rectumincludes colonoscopy 1 year after curative resection and is the current practice in Calgary. There is much debate in the literature as to the value of this intensive follow-up,including 2 prospective randomized controlled trials showing no benefit. The purpose of this study was to assess the benefit of 1-year follow-up colonoscopy by documenting the findings at the time of the procedure. One hundred and four (104) charts were randomly selected and reviewed. All had undergone peri-operative colonoscopy, resection for curative intent and follow-up colonoscopy approximately 1 year post-op. There were 16 (15%) abnormal findings at the time of follow-up colonoscopy. In 10, the colon had notbeen “cleared” peri-operatively and the polyps identified were anticipated and removed. In 6 (6%) there were newfindings not previously documented: 3 hyperplastic polyps; 2 small ( < 0.75 cm) adenomatous polyps and 1 anastomotic recurrence of a rectal cancer. The recurrent cancer was within reach of a rigid sigmoidoscope and the polyps can be considered not clinically significant. This review of our experience with surveillance colonoscopy 1 year after curative resection for cancer of the colon and rectum supports the previously published data from 2 randomized controlled trials showing no benefit.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".