Falling Insulin Requirements and Adverse Pregnancy Outcomes in Women With Pre-pregnancy Diabetes [10D]
Bibliographic record
Abstract
INTRODUCTION: A subset of women with pre-gestational diabetes experience a third-trimester fall in insulin requirements (IR). There is no consensus on whether this fall represents placental dysfunction or is a variant of normal third-trimester physiology. Our study sought to determine whether a third-trimester drop in IR is associated with adverse pregnancy outcomes. METHODS: This is a retrospective cohort study of women with type 1 and 2 diabetes. We compared outcomes in those with and without a ≥15% drop in basal IR. The primary outcome was a composite of stillbirth, spontaneous preterm birth, preterm premature rupture of membranes and iatrogenic preterm birth or emergency caesarean delivery for fetal wellbeing concerns. The results were adjusted for the effect of maternal BMI, presence of microvascular disease, and pre-pregnancy hemoglobin A1c >7. The study was approved by the research ethics board at Mount Sinai Hospital. RESULTS: We included 350 women (146 type 1, 204 type 2), of which 15% had a drop of ≥15% in third-trimester basal insulin requirements. There was no difference in the primary outcome between groups (aOR 0.75 [0.27, 1.81]). In isolation the sensitivity and specificity of a ≥15% drop in basal IR as a diagnostic test for the primary outcome was 13% and 85%, respectively. CONCLUSION: A ≥15% drop in third-trimester basal IR is not associated with and is a poor predictor of adverse pregnancy outcomes in women with pre-pregnancy diabetes. It should not be used in isolation as a sole indication for delivery.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".