3-L Split-dose is Superior to 2-L Polyethylene Glycol in Bowel Cleansing in Chinese Population
Bibliographic record
Abstract
Large volume (4 L) of polyethylene glycol (PEG) solution would ensure a better quality of bowel cleansing but might be poorly tolerated. Due to the smaller body size, lower body weight, and different diet habits, the large volume of 4-L PEG might be poorly tolerated by the Chinese population. In view of this, a balance should be made between the volume and effectiveness. This study aimed to compare the effectiveness, compliance, and safety between 3-L split-dose and 2-L PEG in Chinese population. Consecutive patients scheduled for colonoscopy were recruited from 5 tertiary medical centers in South China between April and July, 2014. Patients were prospectively randomized into 2 groups: 3-L split-dose PEG (3L-group) and 2 L PEG (2L-group). The primary endpoint was bowel cleansing and was defined according to Ottawa Bowel Preparation Scale (OBPS). The safety and compliance were also evaluated. A total of 318 patients were included in the analysis. The mean total OBPS score was significantly higher in 2L-group than in 3L-group (4.4 ± 2.7 vs 2.9 ± 2.4, P < 0.001). Both the intention-to-treat and per-protocol analysis found that rates of successful and excellent bowel preparation were much higher in 3L-group (89.9% and 78.0%) than 2L-group (79.2% and 48.4%), respectively (P < 0.001). The average cecum intubation time was significantly shorter in 3L-group (8.2 ± 3.7 min) than in 2L-group (10.3 ± 4.2 min) (P = 0.04). Adenoma detection rate in right colon was slightly higher in 3L-group than in 2L-group (17.6% vs 12.6%, P = 0.21). The safety and compliance including the taste, smell, and dosage of PEG were similar between 2 groups (P > 0.05). 3-L split-dose PEG is superior to 2-L PEG by better bowel cleansing, improved safety and compliance, shorter cecum intubation time, and potentially higher adenoma detection rate in rightward colon in Chinese population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".