Diagnostic Radiation Exposure in Patients with Inflammatory Bowel Disease
Bibliographic record
Abstract
Background: Because of the chronic and relapsing nature of inflammatory bowel disease (IBD), which often requires characterization with CT scan, IBD patients might be exposed to a large amount of radiation. As a cumulative effective dose (CED) ≥ 100 mSv is considered significant for stochastic risks of cancer, it is important to monitor and control the radiation exposure of the IBD patients. In the present work, we aimed to quantify the mean CED in IBD patients to assess any harmful effects of radiation. Methods: This study includes 200 IBD patients, identified retrospectively, from the outpatient clinics of the Centre Hospitalier de l'Université de Montréal between January 1, 2010, and February 15, 2017, from the gastroenterologists' patients lists. The number and type of each radiology test performed were listed for each patient during the study period and the CED was calculated using our institution's dose index when available and standardized tables. Results: Among the 200 IBD patients, 157 patients had Crohn's disease (CD), 41 had ulcerative colitis (UC), and 2 had indeterminate colitis. The mean CED for IBD patients was 23.1 ± 45.2 mSv during a mean follow-up duration of 4.3 years. CED was higher among patients with CD than with UC (27.5 ± 49.5 versus 6.8 ± 14.8 mSv; p<0.01). Six patients were exposed to a high CED (>100 mSv) and all had CD. Conclusion: While potentially harmful levels of radiation exposure are of concern in only a small number of patients, strategies to limit such exposure are encouraged when clinically appropriate.
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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 | 0.004 |
| 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) | 0.002 | 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".