Impact of previous gestational diabetes management on perinatal outcomes in subsequent pregnancies affected by gestational diabetes mellitus
Bibliographic record
Abstract
OBJECTIVE: To determine the impact of prior gestational diabetes mellitus (GDM) on perinatal outcomes in a subsequent GDM pregnancy. METHODS: This retrospective cohort study included 544 multiparous patients with two consecutive pregnancies between 2012-2019, where the second (index) pregnancy was affected by GDM. The primary exposure was prior GDM diagnosis, categorized into medical and dietary management. The primary outcome was a composite including need for pharmacotherapy, large-for-gestational age, or neonatal hypoglycemia. Adjusted odds ratios (aOR) were calculated using multivariable logistic regression controlling for maternal age, pre-pregnancy body mass index, and gestational age at GDM diagnosis in the index pregnancy. RESULTS: Of the 544 patients, 164 (30.1%) had prior GDM. Prior GDM significantly increased the likelihood of composite outcome compared to no prior GDM (74.4% vs. 57.4%; P < 0.001). After adjusting for confounders, prior GDM remained significantly associated with the composite outcome (aOR 2.03, 95% confidence interval [CI] 1.31-3.15). Stratifying by prior GDM treatment modality, a significant association was found for prior pharmacotherapy-controlled GDM (aOR 3.29, 95% CI 1.64-6.59), but not for prior diet-controlled GDM (aOR = 1.54, 95% CI 0.92-2.60). CONCLUSION: A history of pharmacotherapy-controlled GDM in a previous pregnancy increases odds of adverse perinatal outcomes in a subsequent GDM 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".