Safety of Glyburide for Gestational Diabetes: A Meta-Analysis of Pregnancy Outcomes
Bibliographic record
Abstract
BACKGROUND: Gestational diabetes mellitus affects approximately 4% of all pregnancies. As with other oral hypoglycemics, the use of glyburide in pregnancy has been limited by fears of neonatal hypoglycemia following fetal exposure. Recent experimental and clinical studies have suggested, however, that the drug is not detectable in umbilical blood. OBJECTIVE: To determine the safety of glyburide use in pregnancy in the treatment of gestational diabetes compared with insulin therapy by analyzing all available human studies. METHODS: We conducted a systematic review and meta-analysis of all randomized and cohort studies that reported on the perinatal complications among women with gestational diabetes who received glyburide versus insulin. MEDLINE, EMBASE, and biological abstracts using BIOSIS previews were searched from inception of these databases through October 2006. The following outcomes were included: macrosomia, birthweight, gestational age, neonatal hypoglycemia, and intensive care unit (ICU) admissions. Odds ratios were calculated by the random effects method using Cochrane's Review Manager version 4.3. RESULTS: Nine studies met the inclusion criteria, including a total of 745 glyburideexposed pregnancies and 637 insulin-exposed pregnancies, with each adverse perinatal outcome reported by 4-7 studies. The use of glyburide was not associated with risk of macrosomia (OR 1.07; 95% CI 0.78 to 1.47), differences in birth weight (weighted mean difference [WMD] OR 20.46 g; 95% CI -34.90 to 75.82), rate of large for gestational age (OR 1.04; 95% CI 0.75 to 1.43), differences in gestational age at birth (WMD 0.02 wk; 95% CI -0.23 to 0.26), ICU admission (OR 0.95; 95% CI 0.43 to 2.09), or increased risk of neonatal hypoglycemia (OR 1.24; 95% CI 0.91 to 1.69). CONCLUSIONS: The data shown here do not suggest increased perinatal risks with glyburide. The effectiveness and safety of glyburide require further evaluation, as most studies to date were not randomized.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".