Maternal and Infant Outcomes in GCK-MODY Complicated by Pregnancy
Bibliographic record
Abstract
CONTEXT: Challenges exist in the management of Glucokinase-maturity-onset diabetes of the young (GCK-MODY), especially during pregnancy. OBJECTIVE: This work aimed to evaluate the prevalence of congenital anomaly in newborns from GCK-MODY mothers, and the relationship between fetus genotype and the risk of congenital malformation as well as other adverse pregnancy outcomes. METHODS: Electronic databases including PubMed, EMBASE, and Cochrane database last updated July 16, 2022, were searched. We included observational studies conducted in GCK-MODY complicated by pregnancy, and reporting at least one pregnancy outcome. We extracted data in duplicate, and the risk of bias was evaluated by the Newcastle-Ottawa Quality Assessment Scale (NOS). All statistical analysis was performed by Cochrane Review Manager. RESULTS: Eight studies were selected in the meta-analysis. Five were of high quality and 3 were of medium quality evaluated by NOS. A total of 257 GCK-MODY mothers and 499 offspring were enrolled. Among them, 370 offspring were divided into 2 groups: GCK-affected offspring (GCK+, n = 238) and GCK-unaffected offspring (GCK-, n = 132). The percentage of congenital malformations in GCK pregnant women's offspring was 2.4%. The risk of congenital malformations was similar between the GCK+ and GCK- group (odds ratio = 0.56; 95% CI, 0.07-4.51; I2 = 0%; P = .59). The risk of macrosomia/large for gestational age, neonatal hypoglycemia, and combined adverse neonatal outcome was significantly lower in offspring with the GCK mutation compared with non-GCK mutation carriers. CONCLUSION: The percentage of congenital malformations was 2.4% in GCK-MODY pregnant women's offspring, and newborns with the GCK mutation have lower birth complication than non-GCK mutation carriers.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".