Maternal glycaemic control and risk of neonatal hypoglycaemia in Type 1 diabetes pregnancy: a secondary analysis of the CONCEPTT trial
Bibliographic record
Abstract
AIMS: To examine the relationship between maternal glycaemic control and risk of neonatal hypoglycaemia using conventional and continuous glucose monitoring metrics in the Continuous Glucose Monitoring in Type 1 Diabetes Pregnancy Trial (CONCEPTT) participants. METHODS: A secondary analysis of CONCEPTT involving 225 pregnant women and their liveborn infants. Antenatal glycaemia was assessed at 12, 24 and 34 weeks gestation. Intrapartum glycaemia was assessed by continuous glucose monitoring measures 24 hours prior to delivery. The primary outcome was neonatal hypoglycaemia defined as glucose concentration < 2.6 mmol/l and requiring intravenous dextrose. RESULTS: [48 ± 7 (6.6 ± 0.6) vs. 45 ± 7 (6.2 ± 0.6); P = 0.0009 and 50 ± 7 (6.7 ± 0.6) vs. 46 ± 7 (6.3 ± 0.6); P = 0.0001] and lower continuous glucose monitoring time-in-range (46% vs. 53%; P = 0.004 and 60% vs. 66%; P = 0.03). Neonates with hypoglycaemia had higher cord blood C-peptide concentrations [1416 (834, 2757) vs. 662 (417, 1086) pmol/l; P < 0.00001], birthweight > 97.7th centile (63% vs. 34%; P < 0.0001) and skinfold thickness (P ≤ 0.02). Intrapartum continuous glucose monitoring was available for 33 participants, with no differences between mothers of neonates with and without hypoglycaemia. CONCLUSIONS: Modest increments in continuous glucose monitoring time-in-target (5-7% increase) during the second and third trimesters are associated with reduced risk for neonatal hypoglycaemia. While more intrapartum continuous glucose monitoring data are needed, the higher birthweight and skinfold measures associated with neonatal hypoglycaemia suggest that risk is related to fetal hyperinsulinemia preceding the immediate intrapartum period.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 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".