A Comparative Study of four Oral Contrast Agents for Small Bowel Distension with Computed Tomography Enterography
Bibliographic record
Abstract
PURPOSE: To assess the efficacy of a variety of oral contrast agents in obtaining small bowel distention for computed tomography (CT) enterography examinations. METHODS: A retrospective study was developed to quantitatively assess small bowel luminal distension during CT enterography by using 4 contrast agents, which included water, Metamucil, polyethylene glycol, and lactulose. A total of 256 patients were enrolled in the study and included 64 individuals for each oral regimen. The widest loop of small bowel in each of 4 quadrants on representative coronal images was separately measured for luminal distension. Overall distension and the greatest number of "useful" quadrants were evaluated. Overall distension was calculated by summing the 4 quadrant values into an overall luminal diameter distention score (cm). A "useful" quadrant was defined as having a measurement of ≥2 cm. Each "useful" quadrant was assigned a score of 1, with values that ranged from 0-4. RESULTS: For overall distension, multivariable liner regression analysis showed that the lactulose group had a significantly higher overall distension value than Metamucil, polyethylene glycol, and water by 0.88, 0.92, and 1.63 cm, respectively, with 95% confidence interval. The categorical multivariable logistic regression analysis showed that the lactulose group had greater odds of having more "useful" quadrants than the Metamucil, polyethylene glycol, and water groups, with odds ratios of 3.51, 2.68, and 9.19, respectively. CONCLUSION: Lactulose achieves better small bowel distension for CT enterography studies than the other 3 agents and, therefore, is the preferred oral regimen at our institution.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".