Bowel Preparation Regimen for Computed Tomography Colonography
Bibliographic record
Abstract
PURPOSE: This study was designed to determine whether a reduction in oral contrast dose and a change in timing of administration will result in less residual material in the colonic lumen. METHOD: We retrospectively assessed, in a blinded fashion, the amount and nature of residual material in the colon in 40 patients who received computed tomography colonography. Half of the cohort received the standard bowel-preparation regimen, whereas a sex- and age-matched test arm received the modified regimen. A scoring system that consisted of metrics to quantify the nature and extent of residual fluid and solid material was defined. Image analysis was conducted with the investigators blinded to the group assignment of each patient. Three different trained observers independently reviewed and scored the 6 colonic segments in supine and prone positions for each patient in the cohort. In cases in which interobserver discrepancies existed, the observers reanalyzed the images together to come to an agreement on scores. RESULTS: The new bowel-preparation regimen resulted in significantly less "sticky coat" (P < .005), a problematic phenomenon in which the colonic mucosa is covered in a thin coating of residual contrast and fecal material. There was no difference in the amount of residual fluid. Fewer masses of stool were noted with the new preparation, but this was not found to be statistically significant. CONCLUSION: A new bowel-preparation regimen that consisted of lower quantities of contrast administered earlier in the day preceding computed tomography colonography resulted in a lower incidence of adherent contrast and fecal matter. The reduction of this "sticky coat" problem not only improved radiologic analysis of the colon but may permit same-day therapy via colonoscopy if indicated on imaging.
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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 | 0.000 | 0.003 |
| 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) | 0.001 | 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".