The Efficacy of Split-Dose Bowel Preparations for Polyp Detection: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: Split-dose bowel preparation leads to superior colon cleansing for colonoscopy. However, the magnitude of benefit in detecting colonic polyps is uncertain. We performed a systematic review to synthesize the data on whether using a split-dose bowel preparation regimen improves the detection of polyps when compared with other dosing methods or regimen products. METHODS: We searched MEDLINE, EMBASE, and CENTRAL databases (from the inception to June 2017) for randomized controlled trials that assessed the following: split-dose vs day-before, split-dose vs same-day (as colonoscopy), or different types of split-dose regimens for patients undergoing colonoscopy. We excluded studies limited to inpatients, children, or individuals with inflammatory bowel disease. We compared the number of patients undergoing colonoscopy with recorded detection of polyps, adenomas, advanced adenomas, sessile serrated polyps (SSPs), right colonic adenomas, right colonic polyps, or right colonic SSPs. RESULTS: Twenty-eight trials fulfilled the inclusion criteria (8,842 participants). Of the seven trials comparing split-dose vs day-before bowel preparation regimens, there was an increased detection rate of adenomas (risk ratio (RR) 1.26, 95% confidence intervals (CIs): 1.10-1.44; 4 trials; 1,258 participants), advanced adenomas (RR 1.53, 95% CI: 1.22-1.92; 3 trials; 1,155 participants), and SSPs (RR 2.48, 95% CI: 1.21-5.09; 2 trials; 1,045 participants). Pooled estimates from 8 trials (1,587 participants) evaluating split-dose vs same-day bowel preparations yielded no evidence of statistical difference. For various split-dose vs split-dose trials, 14 fulfilled the criteria (5,496 participants) and no superior split-regimen was identified. CONCLUSIONS: Compared with day-before bowel preparation regimens, split-dose bowel preparations regimens increase the detection of adenomas, advanced adenomas, and have the greatest benefit in SSP detection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".