Glycemic Targets in the Second and Third Trimester of Pregnancy for Women With Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To assess the relationship between second and third trimester glycemic control and adverse outcomes in pregnant women with type 1 diabetes, as uncertainty exists about optimum glycemic targets. RESEARCH DESIGN AND METHODS: Pregnancy outcomes were assessed prospectively in 725 women with type 1 diabetes from the Diabetes and Pre-eclampsia Intervention Trial. HbA1c (A1C) values at 26 and 34 weeks' gestation were categorized into five groups, the lowest, <6.0% (42 mmol/mol), being the reference. Average pre- and postprandial results from an eight-point capillary glucose profile the previous day were categorized into five groups, the lowest (preprandial <5.0 mmol/L and postprandial <6.0 mmol/L) being the reference. RESULTS: An A1C of 6.0-6.4% (42-47 mmol/mol) at 26 weeks' gestation was associated with a significantly increased risk of large for gestational age (LGA) (odds ratio 1.7 [95% CI 1.0-3.0]) and an A1C of 6.5-6.9% (48-52 mmol/mol) with a significantly increased risk of preterm delivery (odds ratio 2.5 [95% CI 1.3-4.8]), pre-eclampsia (4.3 [1.7-10.8]), need for a neonatal glucose infusion (2.9 [1.5-5.6]), and a composite adverse outcome (3.2 [1.3-8.0]). These risks increased progressively with increasing A1C. Results were similar at 34 weeks' gestation. Glucose data showed less consistent trends, although the risk of a composite adverse outcome increased with preprandial glucose levels between 6.0 and 6.9 mmol/L at 34 weeks (3.3 [1.3-8.0]). CONCLUSIONS: LGA increased significantly with an A1C ≥6.0 (42 mmol/mol) at 26 and 34 weeks' gestation and with other adverse outcomes with an A1C ≥6.5% (48 mmol/mol). The data suggest that there is clinical utility in regular measurement of A1C during pregnancy.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".