Major Radiodiagnostic Imaging in Pregnancy and the Risk of Childhood Malignancy: A Population-Based Cohort Study in Ontario
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.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".