Effect of Coffee Added to a Polyethylene glycol plus Ascorbic acid Solution for Bowel Preparation prior to Colonoscopy
Bibliographic record
Abstract
BACKGROUND AND AIMS: Conventional bowel cleansers for colonoscopy have an unpleasant taste and a large volume of solution must be ingested. Coffee increases bowel motility and has an intense flavor. The addition of coffee to a polyethylene glycol+ascorbic acid solution reduces the volume of the solution to be consumed without reducing efficacy, improves the taste of the solution and enhances patient comfort. METHODS: Outpatients with clinical indication or people who wanted screening for cancer were considered eligible. Control group (PEGAS group) consumed a 1-L solution of polyethylene glycol+ascorbic acid twice. Study group (COF group) consumed 750 mL of coffee+polyethylene glycol+ascorbic acid twice. Bowel cleansing was rated using the Aronchick, Ottawa scale, polyp detection rate and colonoscopic insertion time. Tolerability, acceptability, preference, and adverse events were investigated by questionnaires. RESULTS: The COF group had non-inferiority in efficacy (non-inferiority margin, -15%; lower limit of 95% confidence interval for difference between success rates, -4.7% and -8.4% from both scales, respectively). Polyp detection rates were 0.48 and 0.60, respectively (P=0.067). Colonoscopic insertion times were 323.6+/-166.8 s and 330.7+/-243.6 s, respectively (P=0.831). Significant improvement was observed with respect to ease of drinking (P=0.012), taste (P=0.026) and preference (P=0.046) in the COF group. Adverse events occurred in 52.4% and 60.4% in the two groups, respectively (P = 0.251). CONCLUSION: The addition of coffee to polyethylene glycol+ascorbic acid solution reduces the required volume for bowel preparation without reduced efficacy and enhances patient comfort in coffee-drinkers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".