Single-Dose Lubiprostone Along With Split-Dose PEG Solution Without Dietary Restrictions for Bowel Cleansing Prior to Colonoscopy: A Randomized, Double-Blind, Placebo-Controlled Trial
Bibliographic record
Abstract
OBJECTIVES: Proper colonic cleansing prior to colonoscopy is paramount to ensuring complete mucosal visualization and polyp identification. In a double-blind fashion, we compared single-dose lubiprostone (24 microg) versus placebo pretreatment prior to a split-dose polyethylene glycol electrolyte (PEG-E) bowel preparation without dietary restriction to determine the efficacy, safety, and patient tolerability. METHODS: Two hundred patients referred for outpatient colorectal cancer screening were randomized to receive a single-dose of unlabeled lubiprostone (24 microg) or placebo prior to a split-dose PEG-E bowel preparation without dietary restriction. The patients were surveyed prior to the colonoscopy on the tolerability of the bowel preparation, and any adverse events were recorded. The cleanliness of the colon was graded by the endoscopist during the procedure utilizing the Ottawa bowel preparation scale. RESULTS: One hundred ninety-one patients completed the study (95%). Split-dose PEG-E with lubiprostone pretreatment was found to be more effective at bowel cleansing in each segment of the colon when compared with split-dose PEG-E with placebo (P < 0.001). Patients enrolled in the lubiprostone treatment arm rated the overall experience as more tolerable (P 0.003) and complained of less abdominal bloating (P 0.049). No differences were observed between the groups for treatment-emergent side effects or adverse events (P > 0.05). CONCLUSIONS: Single-dose lubiprostone prior to split-dose PEG-E without dietary restriction significantly improves colonic mucosa visualization during colonoscopy and is well tolerated by patients.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".