Risk of congenital anomalies detected during antenatal serum screening in women with pregestational diabetes
Bibliographic record
Abstract
BACKGROUND: Most studies comparing women with and without pregestational diabetes mellitus have not systematically screened for fetal anomalies in early pregnancy, potentially leading to selection bias. AIM: To evaluate the risk for certain congenital anomalies in women participating in an antenatal maternal screening program. DESIGN: Retrospective cohort study. METHODS: We studied all women who underwent antenatal maternal serum screening in Ontario from 1994 to 2000. Fetal anomalies were documented antenatally by ultrasonography or at autopsy, and postnatally diagnosed birth defects were recorded after 20 weeks gestational age for all live- and stillborn affected infants. We compared the risk of open neural tube defects and urinary tract defects among women with and without pregestational diabetes. RESULTS: Of 413,219 women screened during pregnancy, 2069 (0.5%) had diabetes. Compared to non-diabetic women, the adjusted odds ratios (95%CI) for neural tube and urinary tract defects among women with diabetes were 2.5 (0.9-6.8) and 2.6 (1.4-4.9), respectively. DISCUSSION: Among women who undergo second trimester maternal serum screening, pregestational diabetes is associated with an increased risk of having a fetus with an open neural tube defect or urinary tract disorder.
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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 | 0.000 | 0.003 |
| 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) | 0.001 | 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".