Faculty Opinions recommendation of Outcomes for Women with Gestational Diabetes Treated with Metformin: A Retrospective, Case-Control Study.
Bibliographic record
Abstract
Metformin is increasingly being used a therapeutic option for the management of gestational diabetes mellitus (GDM).The aim of this study was to compare the maternal characteristics and perinatal outcomes of women with GDM treated with metformin (with or without supplemental insulin) with those receiving other management approaches.A retrospective, case-control study was carried out and 83 women taking metformin were matched 1:1 with women receiving insulin or diet and lifestyle modification alone.Women managed with diet and lifestyle modification had a significantly lower fasting plasma glucose (p < 0.001) and HbA1c (p < 0.01) at diagnosis of GDM.Furthermore, women managed with metformin had a higher early pregnancy body mass index (BMI) compared to those receiving insulin or diet and lifestyle modification (p < 0.001).There was no difference in mode of delivery, birth weight or incidence of large-or small-for-gestational-age neonates between groups.Women receiving glucose lowering therapies had a higher rate of neonatal hypoglycaemia (p < 0.05).The incidence of other adverse perinatal outcomes was similar between groups.Despite their greater BMI, women with metformin-treated GDM did not have an increased risk of adverse perinatal outcomes.Metformin is a useful alternative to insulin in the management of GDM.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".