Bowel Preparation for a Better Colonoscopy Using Polyethylene Glycol or C-lax: A Double Blind Randomized Clinical Trial
Bibliographic record
Abstract
BACKGROUND Ideal bowel preparation regimen for a suitable colonoscopy should be safe, and well tolerated, and should rapidly clear gastrointestinal tract. Soluble polyethylene glycol (PEG) is the most common cleansing drug and Senna or C-Lax (Cassia angustifolia Vahl) is an alternative herbal one. This study was designed to compare the efficacy of PEG and C-lax in bowel preparation. METHODS In this randomized double blind trial (registry number in IRCT.ir: IRCT201601161264N7), 320 patients were randomly assigned in PEG or C-lax groups. PEG solution was prepared from 5×70 gr sachets in 20×250cc water (250 ml every 15 minutes), prescribed 24h before the colonoscopy. In the other group 3×60 ml C-lax syrup glasses (each containing 90 mg senozid B) was given in two divided doses (1.5 glasses of 250cc every 12 hours), 24h before the colonoscopy. Ottawa score was used to evaluate the quality of bowel preparation. Chi-square test, Student t test, MannWhitney test and multivariate analysis were used to analyze the data. RESULTS Of these patients with the mean (SD) age of 50 (15.16) years, 162 (50.8%) were men. Mean (SD) Ottawa score was 2.57 (0.2) and 3.15 (0.31) in the PEG and C-lax group, respectively (p value = 0.81). Multivariate analysis showed that less opium consumption (p < 0.001) and higher educational level (p =0.005) were associated with better bowel preparation. CONCLUSION C-Lax is non-inferior to PEG solution in cleansing colon. The quality of bowel preparation was lower in opium consumers and better in those with higher educational level.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 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 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".