Effect of Different Types of Diagnostic Criteria for Gestational Diabetes Mellitus on Adverse Neonatal Outcomes: A Systematic Review, Meta-Analysis, and Meta-Regression

BACKGROUND: Evidence supporting various diagnostic criteria for diagnose gestational diabetes mellitus (GDM) are consensus-based, needs for additional evidence related to outcomes. Therefore, the aim of this systematic-review and meta-analysis was to assess the impact of different GDM diagnostic-criteria on the risk of adverse-neonatal-outcomes. METHODS: Electronic databases including Scopus, PubMed, and Web of Sciences were searched to retrieve English original, population-based studies with the universal GDM screening approach, up to January-2020. GDM diagnostic criteria were classified in seven groups and International Association of the Diabetes and Pregnancy Study Groups (IADPSG) was considered as reference one. We used the Mantel–Haenszel method to calculate the pooled odds of events. The possibility of publication bias was examined by Begg’s test. RESULTS: A total of 55 population-based studies consisting of 1,604,391 pregnant women with GDM and 7,770,855 non-GDM counterparts were included. Results showed that in all diagnostic-criteria subgroups, the risk of adverse neonatal outcomes including macrosomia, hyperbilirubinemia, respiratory distress syndrome, neonatal hypoglycemia, neonatal intensive care unit admission, preterm birth, and birth-trauma were significantly higher than the non-GDM counterparts were significantly higher than non-GDM counterparts. Meta-regression analysis revealed that the magnitude of neonatal risks in all diagnostic-criteria subgroups are similar. CONCLUSION: Our results showed that the risk of adverse-neonatal-outcome increased among women with GDM, but the magnitude of risk was not different among those women who were diagnosed through more or less intensive strategies. These findings may help health-care-providers and policy-makers to select the most cost-effective approach for the screening of GDM among pregnant women.