Inadequate Bowel Cleansing Efficacy of Split-dose Polyethylene Glycol for Colonoscopy in Type 2 Diabetic Patients
Bibliographic record
Abstract
BACKGROUND/AIMS: Split-dose polyethylene glycol (PEG) is considered a standard bowel preparation regimen for colonoscopy in the general population. However, it is not clear whether the regimen is optimal for colonoscopy in diabetic patients. The aim of this study was to compare the efficacy and tolerability of split-dose PEG for diabetic versus nondiabetic patients. METHODS: This is a single-center, prospective, investigator-blinded study. A total of 55 consecutive nondiabetic and 50 diabetic patients ingested 2 L PEG solution on the day before the procedure and then 2 L of the solution on the day of colonoscopy. The quality of bowel preparation was graded using the Ottawa scale. RESULTS: There was a significant difference in bowel preparation quality, with a worse preparation except for mid colon in diabetic group (total score: 7.06±1.69 vs. 5.54±1.97, P<0.001; right colon: 2.28±0.57 vs. 1.81±0.72, P<0.001; mid colon: 1.70±0.54 vs. 1.56±0.66, P=0.253; rectosigmoid colon: 1.70±0.76 vs. 1.14±0.62, P<0.001; fluid volume: 1.38±0.53 vs. 1.01±0.59, P=0.001). About 70% of nondiabetic patients had an adequate preparation compared with only 40% of diabetic patients (P=0.003). Diabetic group had longer cecal intubation time (6.4±3.6 vs. 4.5±2.4, P=0.002) and total procedure time (22.1±7.6 vs. 18.1±8.5, P=0.015). Compliance and adverse events were not significantly different. In diabetic group, inadequate bowel preparation had a significant association with higher fasting plasma glucose (136.9±21.8 vs. 121.8±19.4 mg/dL, P=0.016). CONCLUSIONS: Diabetic patients had a worse preparation quality and longer cecal intubation and total procedure time compared with nondiabetic patients. These data suggest that split-dose PEG preparation regimen is not sufficient for optimal bowel preparation in diabetic patients undergoing colonoscopy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".