Split-dose Bowel Preparation for Colonoscopy: 2 Liters Polyethylene Glycol with Ascorbic Acid versus Sodium Picosulfate versus Oral Sodium Phosphate Tablets
Bibliographic record
Abstract
BACKGROUND/AIMS: Adequate bowel preparation is an essential factor affecting the visibility of colonic mucosa and safety of related therapeutic interventions. The aim of this study was to assess the efficacy, tolerability, and safety of three bowel preparation agents -2 L polyethylene glycol with ascorbic acid (PEGA), sodium picosulfate magnesium citrate (SPMC), and oral sodium phosphate tablet (NaP)- for morning colonoscopy. METHODS: Here, we analyzed the medical records of patients who had taken bowel preparation agents using the split-dose method and undergone colonoscopy in a single hospital. The efficacy of bowel preparation agents was evaluated using the Ottawa bowel preparation assessment tool. The safety and tolerability of the agents were assessed by measuring the renal function and electrolytes prior to and after the procedure as well as by assessing the self-reported questionnaire. RESULTS: Of the 365 patients (PEGA:163, SPMC: 93, NaP: 109), 98.6% ingested more than 90% of the agents. NaP showed an inferior cleansing efficacy, and serum phosphate elevation was significantly higher in the NaP group. However, the satisfaction score was lowest in the PEGA group. Age (odds ratio [OR] 0.96, 95% confidence interval [CI] 0.92-0.99, p=0.04) and preparation agents (OR of PEGA versus NaP 5.0, 95% CI 2.28-10.97, p<0.001) (OR of SPMC versus NaP 2.73, 95% CI 1.22-6.08, p=0.01) were independently associated with bowel preparation success. CONCLUSIONS: According to our analysis, NaP showed an inferior cleansing efficacy compared with PEGA and SPMC, which may be attributed to the complex administration method and lower water intake. However, large-volume ingestion remains unsatisfactory for patients. Detailed bowel preparation instructions could enhance bowel cleansing efficacy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".