RESUMO

The aim was to assess the role of Metabolic Syndrome (MetS) diagnostic markers, recommended by three different guidelines, in the prediction of hyperglycemia in pregnancy. This cross-sectional cohort study included 506 non-diabetic women, with a singleton pregnancy, who underwent a diagnostic test for hyperglycemia at 24-28 weeks. Clinical, anthropometric, and laboratory data were obtained. The relationship between MetS markers and the risk of hyperglycemia was evaluated by backward stepwise logistic regression analysis (OR, 95% CI). The limit of statistical significance was 95% (p < 0.05). Triglycerides (TG) ≥ 150 mg/dL, blood pressure (BP) ≥ 130/85 mmHg, fasting glucose (FG) ≥ 100 mg/dL, and waist circumference (WC) > 88 cm were identified as independent risk factors for hyperglycemia in pregnancy. These results might help the selective screening of hyperglycemia in pregnancy.

Assuntos

Hiperglicemia/sangue , Síndrome Metabólica/sangue , Complicações na Gravidez/sangue , Adulto , Biomarcadores/sangue , Pressão Sanguínea , Feminino , Humanos , Hiperglicemia/epidemiologia , Síndrome Metabólica/epidemiologia , Gravidez , Complicações na Gravidez/epidemiologia , Triglicerídeos/sangue , Circunferência da Cintura

RESUMO

BACKGROUND: While sufficient evidence supporting universal screening is not available, it is justifiable to look for specific risk factors for gestational diabetes mellitus (GDM) or hyperglycemia in pregnancy (HIP). The objective of this study is to identify independent risk factors for HIP and its adverse perinatal outcomes in a Brazilian public referral center. METHODS: We included 569 singleton pregnant women who were split into three groups by glucose status: GDM (n = 207), mild gestational hyperglycemia (MGH; n = 133), and control (n = 229). Women who used corticosteroids or had a history of DM were excluded. HIP comprised both GDM and MGH, diagnosed by a 100 g- or 75 g-oral glucose tolerance test (OGTT) and a glucose profile at 24-28 weeks. Maternal characteristics were tested for their ability to predict HIP and its outcomes. Bivariate analysis (RR; 95% CI) was used to identify potential associations. Logistic regression (RRadj; 95% CI) was used to confirm the independent risk factors for HIP and its perinatal outcomes (p < 0.05). RESULTS: Age ≥ 25 years [1.83, 1.12-2.99], prepregnancy BMI ≥ 25 kg/m2 [2.88, 1.89-4.39], family history of DM [2.12, 1.42-3.17] and multiparity [2.07, 1.27-3.37] were independent risk factors for HIP. Family history of DM [169, 1.16-2.16] and hypertension [2.00, 1.36-2.98] were independent risk factors for C-section. HbA1c ≥ 6.0% at birth was an independent risk factor for LGA [1.99, 1.05-3.80], macrosomia [2.43, 1.27-4.63], and birthweight Z-score > 2.0 [4.17, 1.57-11.10]. CONCLUSIONS: MGH presents adverse pregnancy outcomes similar to those observed in the GDM group but distinct from those observed in the control (no diabetes) group. In our cohort, age ≥ 25 years, prepregnancy BMI ≥ 25 kg/m2, family history of DM, and multiparity were independent risk factors for HIP, supporting the use of selective screening for this condition. These results should be validated in populations with similar characteristics in Brazil or other low- and middle-income countries.