Impact of Low-Residue Diet on Bowel Preparation for Colonoscopy
Bibliographic record
Abstract
BACKGROUND: Few studies have focused on the effect of dietary residue on preparation for colonoscopy. OBJECTIVE: To determine the impact of a low-residue diet on the quality of bowel preparation. SETTING: Chang Gung Memorial Hospital, Kaohsiung Medical Center, Taiwan. PATIENTS: Eight hundred four consecutive patients (50.4 ± 11.6 y (range, 18-88 y), 43.6% female) undergoing colonoscopy between May 2008 and June 2009. INTERVENTION: Subjects were advised to consume a low-residue diet for 2 days before the procedure, and they recorded food intake by use of diet diaries. MAIN OUTCOME MEASURES: The quality of bowel cleansing was evaluated using the Ottawa bowel preparation scale. Patient variables and details of each procedure were recorded, and factors that determined the quality of colon cleansing were determined. LIMITATIONS: Categories of foods consumed were recorded, but not the amount eaten, and diet diaries were completed retrospectively. RESULTS: Data from 789 patients were analyzed. Only 44.2% of patients adhered to a low-residue diet, and 39.3% of patients were inadequately prepared. On multivariate logistic regression analysis, age (P = .007), body mass index (P = .01), abdominal girth (P = .041), bowel habit tending to constipation (P = .015), and high-residue diet (P < .0001) were independent predictors of inadequate bowel preparation. There was a linear relationship between dietary residue score and bowel cleanliness score (r = -0.475; P < .001). CONCLUSIONS: A low-residue diet for 2 days of before colonoscopy improves bowel cleansing, but compliance with this advice is poor. The importance of a low-residue diet should be emphasized to patients undergoing preparation for colonoscopy.
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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 | 0.008 |
| 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".