Polyethylene glycol plus ascorbic acid is as effective as sodium picosulfate with magnesium citrate for bowel preparation: A randomized trial
Bibliographic record
Abstract
OBJECTIVE: This study was aimed to evaluate the efficacy and safety of two low-volume agents, polyethylene glycol (PEG)-3350 plus ascorbic acid (PEG + Asc) and sodium picosulfate with magnesium citrate (SPMC), for bowel preparation. METHODS: We performed a prospective, endoscopist-blinded, single-center, randomized controlled trial comparing PEG + Asc with SPMC to evaluate the bowel cleansing efficacy of the two regimens using the modified Ottawa bowel preparation scale (OBPS) and the Aronchick scale. Patients' taste and overall tolerance were assessed with a questionnaire. RESULTS: In total, 200 patients were randomized to receive either PEG + Asc (n = 98) or SPMC (n = 102). Both treatments were similarly efficacious in bowel cleansing, based on the modified OBSP (PEG + Asc 4.01 ± 2.29 vs SPMC 3.86 ± 2.47, P = 0.62) and Aronchick scale (PEG + Asc 1.96 ± 0.70 vs SPMC 1.89 ± 0.70, P = 0.42). Patient-reported taste and tolerance of each regimen, as reported by the questionnaire, were significantly greater in the PEG + Asc group than in the SPMC group (P = 0.01). In terms of adverse events, dizziness was more frequently observed in the PEG + Asc group (P = 0.03), whereas nausea was more common in the SPMC group (P = 0.02). CONCLUSIONS: PEG + Asc and SPMC show similar efficacy for bowel preparation. However, patient's overall tolerance is higher in the PEG + Asc group.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".