Patient Tolerability of Bowel Preparation is Associated with Polyp Detection Rate During Colonoscopy
Bibliographic record
Abstract
BACKGROUND & AIMS: A number of factors have been identified that influence the yield of screening colonoscopy. The perceived tolerability of bowel preparation has not been studied as a predictor of quality outcomes in colonoscopy. We aimed to characterize the association between patient-perceived tolerability of bowel preparation and polyp detection during colonoscopy. METHODS: We performed a cross-sectional cohort study of 413 consecutive adult patients presenting for outpatient colonoscopy at two outpatient endoscopy centers at our institution. We developed a standardized questionnaire to assess the patient's experience with bowel preparation. Bowel preparation quality was measured using the validated Ottawa scale and colonoscopic findings were recorded for each patient. The primary outcome was polyp detection and the secondary outcome was the quality of bowel preparation. RESULTS: Patient-reported clarity of effluent during bowel preparation correlated poorly with Ottawa score during colonoscopy, ĸ=0.15. Female gender was an independent risk factor for a poorly tolerated bowel prep (OR 3.93, 95% CI 2.30 - 6.72, p<0.001). Report of a poorly tolerated bowel prep was independently associated with the primary outcome, polyp detection (OR 0.39, 95% CI 0.18 - 0.84, p=0.02) and also with the secondary outcome, lower quality bowel preparation (OR 2.39, 95% CI 1.17 - 4.9, p=0.02). CONCLUSIONS: A patient-perceived negative experience with bowel preparation independently predicted both a lower quality bowel preparation and a lower rate of polyp of detection. Assessment of the tolerability of bowel preparation before colonoscopy may be a clinically useful predictor of quality outcomes during colonoscopy.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".