Sleep Disturbances, Bowel Movement Kinetics, and Travel Interruption With Bowel Preparation: A Bowel CLEANsing National Initiative Substudy
Bibliographic record
Abstract
INTRODUCTION: We investigated sleep disturbances, bowel movement (BM) kinetics, and travel experience with different bowel preparation regimens in a substudy of patients enrolled in a randomized multicenter Canadian clinical trial. METHODS: Patients scheduled to have a colonoscopy between 7:30 am and 10:30 am (early morning) were randomized to (i) 4-L single-dose polyethylene glycol (PEG) given in the evening before, (ii) 2-L split-dose PEG (+bisacodyl 15 mg), or (iii) 4-L split-dose PEG. Patients scheduled to undergo a colonoscopy between 10:30 am and 4:30 pm (afternoon) were randomized to (iv) 2-L single-dose PEG (+bisacodyl 15 mg) in the morning, (v) 2-L split-dose PEG (+bisacodyl 15 mg), or (vi) 4-L split-dose PEG. Patients were asked to record information on BM kinetics, sleep, and travel to the endoscopy unit. Continuous and categorical variables were compared between groups using a Kruskal-Wallis test or χ 2 test, respectively. Intention-to-treat analyses were performed. RESULTS: Overall, 641 patients were included in this substudy. Patients undergoing early morning colonoscopies reported the most awakenings in the night when assigned to 4-L single-dose day-before PEG and the highest reduction in sleep hours when assigned to 4-L split-dose PEG. There were no significant between-group differences in urgent BMs, fecal incontinence episodes, or travel interruptions. Overall, 17% of those traveling for more than an hour had to stop for a BM during travel, with no significant difference between groups. DISCUSSION: Day-before and split-dose high-volume PEG regimens for colonoscopies scheduled before 10:30 am lead to the greatest sleep disturbance.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".