Severe neonatal hypoglycaemia and intrapartum glycaemic control in pregnancies complicated by type 1, type 2 and gestational diabetes
Bibliographic record
Abstract
AIMS: To determine if in-target intrapartum glucose control is associated with neonatal hypoglycaemia in women with type 1, type 2 or gestational diabetes. METHODS: This was a retrospective cohort study of pregnant women with diabetes and their neonates. The primary exposure was in-target glucose control, defined as all capillary glucose values within the range 3.5-6.5 mmol/l during the intrapartum period. The primary outcome, neonatal hypoglycaemia, was defined as treatment with intravenous dextrose therapy. Multiple logistic regression was used to examine the association between maternal intrapartum glycaemic control and neonatal hypoglycaemia, adjusting for covariates. RESULTS: Intrapartum glucose testing was available for 157 (86.3%), 267 (76.3%) and 3256 (52.4%) women with type 1, type 2 and gestational diabetes, respectively. In the univariate analysis, in-target glycaemic control was significantly associated with neonatal hypoglycaemia in women with gestational diabetes, but not in women with type 1 or 2 diabetes. However, after adjustment for important neonatal factors (large for gestational age, preterm delivery and infant sex), intrapartum in-target glycaemic control was not significantly associated with neonatal hypoglycaemia in women regardless of diabetes type [adjusted odds ratios 0.4 (95% CI 0.1, 1.4), 0.7 (95% CI 0.3, 1.3) and 0.7 (95% CI 0.5, 1.0) for women with type 1, type 2 and gestational diabetes, respectively]. CONCLUSIONS: There was no significant association between in-target glycaemic control and neonatal hypoglycaemia after adjustment for neonatal factors. Given the high risk of maternal hypoglycaemia and the resources required, future trials should consider whether more relaxed intrapartum glycaemic targets may be safer and yield similar neonatal outcomes.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 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".