The presence of polycystic ovary syndrome increases the risk of maternal but not neonatal complications in women with type 2 diabetes in pregnancy
Bibliographic record
Abstract
AIMS: Our aims were, in the setting of type 2 diabetes mellitus (T2DM) in pregnancy, to investigate the association of polycystic ovary syndrome (PCOS) with perinatal outcomes and to examine whether treatment with metformin had a differential effect in those with and without PCOS. MATERIALS AND METHODS: We performed a retrospective cohort study using the metformin in women with type 2 diabetes in pregnancy (MiTy) trial data. We examined differences in maternal and neonatal outcomes among MiTy participants with and without PCOS using linear and logistic regression to adjust for potential confounders. We additionally examined the relative difference in the effect of metformin treatment on pregnancy outcomes among MiTy participants with PCOS versus those without PCOS. RESULTS: Among women with T2DM in pregnancy, PCOS was significantly associated with higher excess gestational weight gain (unadjusted 12.0 vs. 11.4 kg, adjusted mean difference 2.1 kg [0.3, 3.9], p = 0.021) and higher total insulin dose at 34-36 weeks (unadjusted 172 vs. 124 units per day, adjusted mean difference 44 units [15, 73], p = 0.004), but no difference was seen in neonatal outcomes. Unlike the non-PCOS subgroup, metformin treatment versus placebo in the PCOS subgroup was associated with an increase in extremely large-for-gestational-age infants (28.6 vs. 14.0%, p = 0.008 for interaction) and an increase in worsened pre-existing maternal hypertension (16.7 vs. 4.5%, p = 0.046 for interaction). CONCLUSIONS: Clinicians should be alerted to the potential for high insulin requirements and excess weight gain in pregnant patients with T2DM and comorbid PCOS. Moreover, metformin may not be as beneficial in this population as previously understood.
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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 | 0.007 |
| 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 | 0.000 |
| Research integrity | 0.001 | 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".