Low‐dose ionising radiation from medical imaging in patients hospitalised in internal medicine
Bibliographic record
Abstract
BACKGROUND: Medical imaging is responsible for increasing exposure to low-dose ionising radiation in the general population. The extent of exposure in specific patient populations remains to be determined. AIM: We sought to determine the level of exposure in patients hospitalised in General Internal Medicine. METHODS: In this retrospective cohort study, we searched the Centre Informatisé de Recherche Évaluative en Services et Soins de Santé database for adult patients hospitalised in General Internal Medicine from 1 January 2008 to 31 December 2008. We collected data on demographics, co-morbidities, and radiological and nuclear imaging. We used data from the literature to calculate an estimated annual effective dose for each patient and searched for factors associated with higher exposure. RESULTS: One thousand one hundred eighty-seven (1187) patients were hospitalised at least once during the study period. The median age was 69 years (interquartile range 56-81) and 636 (53.6%) were men. The median annual effective dose of the whole cohort was 8.7 mSv/year. Patients aged between 55 and 80 years were exposed to a higher median effective dose compared with their younger and older counterparts (P < 0.001). Patients with cardiac, pulmonary, peripheral arterial and neoplastic disease were at higher risk of exposure to high and very high annual effective dose (P < 0.01). Patients with longer hospitalisations were at higher risk of exposure to high and very high annual effective dose (P < 0.01). CONCLUSION: Patients hospitalised on a General Internal Medicine ward are exposed to three times more ionising radiation than the general population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".