Polyethylene glycol vs sodium picosulfate/magnesium citrate for colonoscopy preparation
Bibliographic record
Abstract
BACKGROUND AND STUDY AIMS: Polyethylene glycol-based electrolyte solutions (PEG-ELS) and the combination of sodium picosulfate/magnesium citrate (SPMC) are commonly used bowel preparation agents. The aim of the present study was to compare the two agents with regard to cleansing efficacy and tolerance among individuals scheduled for outpatient colonoscopy. MATERIALS AND METHODS: The 368 colonoscopy outpatients at three Norwegian hospitals were randomized to bowel lavage with either PEG-ELS or SPMC. Compliance and patient tolerance were evaluated using a patient questionnaire. Bowel cleansing was evaluated using the Ottawa Bowel Preparation Quality Scale (OBPS), a validated scoring system with scores between 0 (best) and 14. RESULTS: There was no difference in the cleansing quality between the PEG-ELS and SPMC groups (median OBPS 5.0 in both groups). The group that received SPMC reported better overall patient tolerance than the PEG-ELS group (72.6 % vs 59.0 % reporting no or slight discomfort, P < 0.01). Compliance with the recommended total fluid intake (4 L) was better in the SPMC group than in the PEG-ELS group (94.2 % vs 81.2 % respectively, P < 0.01); moreover, the polyp detection rate was superior (34.3 % vs 23.3 %, P = 0.02). CONCLUSION: PEG-ELS and SPMC are equally effective in cleansing efficacy, but SPMC was better tolerated by patients and resulted in superior patient compliance and polyp detection rate. CLINICAL TRIAL REGISTRATION: NCT01624454.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".