Patients With IBD are Exposed to High Levels of Ionizing Radiation Through CT Scan Diagnostic Imaging
Bibliographic record
Abstract
GOALS: The objective of this study was to assess the total effective dose of ionizing radiation from abdominal diagnostic imaging in patients with inflammatory bowel disease (IBD) over a 5-year period. BACKGROUND: Radiation exposure from diagnostic imaging is becoming increasingly common in IBD patients, in part due the availability of computed tomography (CT). Increased risk of malignancy has been associated with radiation exposure. STUDY: This is a retrospective chart review. A university-based gastroenterology database was searched for patients with a diagnosis of Crohn's disease (CD) or ulcerative colitis (UC) seen between 2003 and 2008. The cumulative ionizing radiation exposure, expressed in milli-Sieverts (mSv), was then calculated from standard tables and by counting the number of abdominal imaging studies. RESULTS: Patients with CD had higher cumulative radiation exposure from diagnostic imaging than patients with UC (14.3 ± 1.45 mSv/5-y period vs. 5.9 ± 0.81 mSv/5-y period, P=0.00003). Three-quarters of the radiation exposure in both CD and UC was from CT scans. Thirty-four percent (127 of 373) of CD patients had CT scans, compared with just 20% (37 of 182) of UC patients. Importantly, 7% of CD patients were exposed to high levels of radiation (>50 mSv/5 y), in contrast to none of the UC patients. CONCLUSIONS: Patients with IBD, and especially CD patients, undergo frequent diagnostic imaging and thus significant exposure to ionizing radiation. This radiation exposure reaches high levels in 7% of CD patients, mainly from CT scanning. Efforts should be made to minimize the radiation exposure from diagnostic imaging by reducing either the number of studies or radiation dose in modalities with ionizing radiation.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".