Objective To evaluate the association between different pre-eclampsia (PE) phenotypes and the development of metabolic syndrome postpartum, in order to identify the subgroup of formerly pre-eclamptic women with a worse cardiovascular risk profile requiring tailored postpartum follow-up. Methods This was a cohort study of 1102 formerly pre-eclamptic women in whom cardiovascular and cardiometabolic evaluation was performed at least 3 months postpartum. Women were divided into four subgroups based on PE resulting in delivery before 34 weeks (early-onset (EO)) or at or after 34 weeks (late onset (LO)) of gestation and whether they delivered a small-for-gestational-age (SGA) neonate. Metabolic syndrome was diagnosed as the presence of hyperinsulinemia along with two or more of: body mass index >= 30 kg/m(2); dyslipidemia; hypertension; and microalbuminuria or proteinuria. Data were compared between groups using ANOVA after Bonferroni correction. Odds ratios (OR) were calculated using logistic regression to determine the association between metabolic syndrome and the four subgroups. We constructed receiver-operating characteristics curves and computed the area under the curve (AUC) to quantify the ability of different obstetric variables to distinguish between women who developed metabolic syndrome and those who did not. Results The prevalence of metabolic syndrome was higher in women with EO-PE and SGA (25.8%) than in those with EO-PE without SGA (14.7%) (OR 2.01 (95% CI, 1.34-3.03)) and approximately five-fold higher than in women with LO-PE with SGA (5.6%) (OR 5.85 (95% CI, 2.60-13.10)). In women with LO-PE, the prevalence of metabolic syndrome did not differ significantly between women with and those without SGA. Multivariate analysis revealed that a history of SGA, a history of EO-PE and systolic blood pressure at the time of screening are the best predictors of developing metabolic syndrome postpartum. The AUC of the model combining these three variables was 74.6% (95% CI, 70.7-78.5%). The probability of the presence of metabolic syndrome was calculated as: P = 1/(1 + e(-LP)), where LP is linear predictor = -8.693 + (0.312 x SGA (yes = 1)) + (0.507 x EO-PE (yes = 1)) + (0.053 x systolic blood pressure). Conclusions The incidence of metabolic syndrome postpartum was associated more strongly with EO-PE in combination with SGA as compared with LO-PE or EO-PE without SGA. Both time of onset of PE and fetal growth affect the risk of metabolic syndrome after a pre-eclamptic pregnancy. Copyright (c) 2018 ISUOG. Published by John Wiley & Sons Ltd.
机构:Hosp Univ Gineco Obstetrico Mariana Graj, Santa Clara, Villa Clara, Cuba
Gonzalez, Juan A. Suarez
Machado, Mario Gutierrez
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Hosp Univ Gineco Obstetrico Mariana Graj, Santa Clara, Villa Clara, CubaHosp Univ Gineco Obstetrico Mariana Graj, Santa Clara, Villa Clara, Cuba
Machado, Mario Gutierrez
Gonzalez, Elizabeth Alvarez-Guerra
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Univ Ciencias Medicas Villa Clara, Unidad Invest Biomed, Santa Clara, Villa Clara, CubaHosp Univ Gineco Obstetrico Mariana Graj, Santa Clara, Villa Clara, Cuba
Gonzalez, Elizabeth Alvarez-Guerra
Munoz, Nelida L. Sarasa
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Univ Ciencias Medicas Villa Clara, Fac Med, Santa Clara, Villa Clara, CubaHosp Univ Gineco Obstetrico Mariana Graj, Santa Clara, Villa Clara, Cuba
Munoz, Nelida L. Sarasa
Luna, Oscar Canizares
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Univ Ciencias Medicas Villa Clara, Fac Med, Santa Clara, Villa Clara, CubaHosp Univ Gineco Obstetrico Mariana Graj, Santa Clara, Villa Clara, Cuba
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Basaveshwara Med Coll & Res Ctr, Dept Obstet & Gynaecol, Chitradurga, Karnataka, IndiaBasaveshwara Med Coll & Res Ctr, Dept Obstet & Gynaecol, Chitradurga, Karnataka, India
Poornima, M.
Rakesh, B.
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Basaveshwara Med Coll & Res Ctr, Dept Med, Chitradurga, Karnataka, IndiaBasaveshwara Med Coll & Res Ctr, Dept Obstet & Gynaecol, Chitradurga, Karnataka, India