Major Radiodiagnostic Imaging in Pregnancy and the Risk of Childhood Malignancy: A Population-Based Cohort Study in Ontario
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The association between fetal exposure to major radiodiagnostic testing in pregnancy-computed tomography (CT) and radionuclide imaging-and the risk of childhood cancer is not established. METHODS AND FINDINGS: We completed a population-based study of 1.8 million maternal-child pairs in the province of Ontario, from 1991 to 2008. We used Ontario's universal health care-linked administrative databases to identify all term obstetrical deliveries and newborn records, inpatient and outpatient major radiodiagnostic services, as well as all children with a malignancy after birth. There were 5,590 mothers exposed to major radiodiagnostic testing in pregnancy (3.0 per 1,000) and 1,829,927 mothers not exposed. The rate of radiodiagnostic testing increased from 1.1 to 6.3 per 1,000 pregnancies over the study period; about 73% of tests were CT scans. After a median duration of follow-up of 8.9 years, four childhood cancers arose in the exposed group (1.13 per 10,000 person-years) and 2,539 cancers in the unexposed group (1.56 per 10,000 person-years), a crude hazard ratio of 0.69 (95% confidence interval 0.26-1.82). After adjusting for maternal age, income quintile, urban status, and maternal cancer, as well as infant sex, chromosomal or congenital anomalies, and major radiodiagnostic test exposure after birth, the risk was essentially unchanged (hazard ratio 0.68, 95% confidence interval 0.25-1.80). CONCLUSIONS: Although major radiodiagnostic testing is now performed in about 1 in 160 pregnancies in Ontario, the absolute annual risk of childhood malignancy following exposure in utero remains about 1 in 10,000. Since the upper confidence limit of the relative risk of malignancy may be as high as 1.8 times that of an unexposed pregnancy, we cannot exclude the possibility that fetal exposure to CT or radionuclide imaging is carcinogenic.
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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 | 0.001 |
| 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 | 0.001 |
| 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 it