Perforation and post-polypectomy bleeding complicating colonoscopy in a population-based screening program
Bibliographic record
Abstract
Abstract Background and study aims We aimed to estimate the rate of hospital admissions for perforation and for post-polypectomy bleeding, after outpatient colonoscopy following a first positive fecal occult blood test screen through the population-based ColonCancerCheck program in Ontario, Canada. Patients and methods We identified all individuals aged 50 to 74 years with a first positive CCC gFOBT screening result from 2008 to 2017 who underwent outpatient colonoscopy ≤ 6 months later and who did not receive a diagnosis of CRC ≤ 24 months later. We identified inpatient hospital admissions for colonic perforation ≤ 7 days after and for post-polypectomy bleeding ≤ 14 days following colonoscopy. Results Among 121,626 individuals who underwent colonoscopy, the rate of perforation was 0.6 per 1000 from 2008 to 2012 and 0.4 per 1000 from 2013 to 2017. The rate was elevated among those aged 70 to 74 years; those with comorbidities; when colonoscopy was performed by endoscopists other than gastroenterologists or endoscopists with low prior year volume; and when polypectomy was performed during colonoscopy. The rate of bleeding was 4.3 per 1000 and was elevated among those aged 70 to 74 years, those with comorbidity, and with complex polypectomy. Both outcomes were more common among those aged 70 to 74 years, those with a 5-year cumulative Charlson score ≥ 1, those with prior hospitalization for ischemic heart disease, and those with endoscopists whose prior year colonoscopy volume was in the three lower quartiles. Conclusions Colonic perforation and post-polypectomy bleeding, among participants of population-based colorectal screening programs who test positive in the absence of colorectal cancer, are infrequent but serious complications, which increase with participant age and comorbidity, and with endoscopist characteristics.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".