Studies on the Association of GCK and GCKR Polymorphisms with Susceptibility to Gestational Diabetes Mellitus: A Meta-Analysis
Bibliographic record
Abstract
Background: A prevalent condition during pregnancy, gestational diabetes mellitus (GDM) affects a significant proportion of pregnancies worldwide and poses substantial risks to maternal as well as fetal health. Polymorphisms in the glucokinase (GCK) and glucokinase regulatory protein (GCKR) genes, which are crucial for glucose homeostasis, may modulate susceptibility to GDM. Hence, this meta-analysis aimed to assess the relationship between GDM and polymorphisms in GCK (rs1799884, rs4607517) and GCKR (rs780094, rs1260326). Methods: In this systematic review, we retrieved data from PubMed, EMBASE, Medline, EBSCO, Cochrane Library, and Chinese National Knowledge Infrastructure (CNKI) databases. Studies were critically appraised using the Newcastle-Ottawa Scale, and meta-analyses were performed using STATA 12.0. The odds ratios (ORs) were calculated with 95% confidence intervals (CIs) and heterogeneity was assessed with Cochran’s Q test as well as I2 statistical tests, respectively. Moreover, Begg’s test helped in evaluating publication bias. Results: We included 20 studies, comprising 9745 GDM women and 15,830 controls. All genetic models showed a strong correlation between the GCK rs1799884 polymorphism and GDM, with carriers of the A allele exhibiting an increased risk. Conversely, GCK rs4607517, GCKR rs780094, and rs1260326 were not significantly associated. However, heterogeneity was influenced by ethnicity and diagnostic criteria. Conclusions: The GCK rs1799884 polymorphism can be a potential predictive marker because it is significantly associated with an increased risk of GDM.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".