Rates of minor adverse events following outpatient colonoscopies: A longitudinal cohort study
Bibliographic record
Abstract
Background: Little is known about minor adverse events (MAEs) following outpatient colonoscopies and the few existing studies are limited by possible recall bias and outcome misclassification. Objective: To estimate the rate of MAEs at 2, 14 and 30 days after outpatient colonoscopies and assess health-care resources utilization and work absenteeism associated with MAEs from colonoscopy. Methods: A longitudinal cohort study with follow-ups at 2, 14 and 30 days was conducted among patients having an outpatient colonoscopy at the Montreal General Hospital site of the McGill University Health Centre. Consecutive participants were interviewed by a research assistant prior to colonoscopy to obtain baseline characteristics. Endoscopy reports were consulted for colonoscopy indication, findings, biopsies, and polypectomies. Follow-up was conducted by either phone interview or internet survey according to the participant's choice. Information was collected on occurrence of MAEs, work absenteeism for participant and companion, and health resources utilization. MAE rates were calculated at each follow-up using a Bayesian hierarchical model accounting for clustering of patients within physicians Results: 421 participants were recruited in the study. MAE rates at the 2, 14 and 30 days follow-up were 0.172 (95% CI 0.08,0.296), 0.097 (95% CI 0.024, 0.234) and 0.031 (0.0008-0.132), respectively. There was little variation among physician specific rates. Health resources utilization overall for MAEs was low (1.8%). Work absenteeism was primarily due to attending to the colonoscopy (82%) and the bowel preparation (35.3%), but not to MAEs (2.9%). Among working companions, 62.5% missed work. Conclusion: MAEs are common after colonoscopy, occur mainly in the first two weeks and result in only minor health resource utilization and work absenteeism
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".