Abstract
BackgroundOur primary objective was to establish a cutoff value for the soluble fms-like tyrosine kinase 1(sFlt-1)/placental growth factor (PlGF) ratio measured using the Elecsys assay to predict late-onset preeclampsia in low-risk pregnancies. Our secondary objective was to evaluate the ability of combination models using Elecsys data, second trimester uterine artery (UtA) Doppler ultrasonography measurements, and the serum fetoplacental protein levels used for Down’s syndrome screening, to predict preeclampsia.MethodsThis prospective cohort study included 262 pregnant women with a low risk of preeclampsia. Plasma levels of pregnancy-associated plasma protein-A (PAPP-A) and serum levels of alpha-fetoprotein, unconjugated estriol, human chorionic gonadotropin, and inhibin-A were measured, and sFlt-1/PlGF ratios were calculated. All women underwent UtA Doppler ultrasonography at 20 to 24 weeks of gestation.ResultsEight of the 262 women (3.0%) developed late-onset preeclampsia. Receiver operating characteristic curve analysis showed that the third trimester sFlt-1/PlGF ratio yielded the best detection rate (DR) for preeclampsia at a fixed false-positive rate (FPR) of 10%, followed by the second trimester sFlt-1/PlGF ratio, sFlt-1 level, and PlGF level. Binary logistic regression analysis was used to determine the five best combination models for early detection of late-onset preeclampsia. The combination of the PAPP-A level and the second trimester sFlt-1/PlGF ratio yielded a DR of 87.5% at a fixed FPR of 5%, the combination of second and third trimester sFlt-1/PlGF ratios yielded a DR of 87.5% at a fixed FPR of 10%, the combination of body mass index and the second trimester sFlt-1 level yielded a DR of 87.5% at a fixed FPR of 10%, the combination of the PAPP-A and inhibin-A levels yielded a DR of 50% at a fixed FPR of 10%, and the combination of the PAPP-A level and the third trimester sFlt-1/PlGF ratio yielded a DR of 62.5% at a fixed FPR of 10%.ConclusionsThe combination of the PAPP-A level and the second trimester sFlt-1/PlGF ratio, and the combination of the second trimester sFlt-1 level with body mass index, were better predictors of late-onset preeclampsia than any individual marker.
Highlights
Our primary objective was to establish a cutoff value for the soluble fms-like tyrosine kinase 1(sFlt-1)/ placental growth factor (PlGF) ratio measured using the Elecsys assay to predict late-onset preeclampsia in low-risk pregnancies
This study evaluated the ability of the plasma protein-A (PAPP-A) and inhibin-A levels, sFlt-1/PIGF ratio, and uterine artery (UtA) Doppler ultrasonography measurements to predict preeclampsia in low-risk pregnancies, and established a cutoff value for the sFlt-1/PlGF ratio determined using the Elecsys platform
Our results indicate that combination of the Elecsys sFlt-1/PlGF ratio with the pre-pregnancy body mass index (BMI) and biochemical markers during pregnancy may improve the sensitivity of predicting preeclampsia in a low-risk population
Summary
Our primary objective was to establish a cutoff value for the soluble fms-like tyrosine kinase 1(sFlt-1)/ placental growth factor (PlGF) ratio measured using the Elecsys assay to predict late-onset preeclampsia in low-risk pregnancies. Our secondary objective was to evaluate the ability of combination models using Elecsys data, second trimester uterine artery (UtA) Doppler ultrasonography measurements, and the serum fetoplacental protein levels used for Down’s syndrome screening, to predict preeclampsia. Preeclampsia is characterized by hypertension and significant proteinuria during pregnancy. This multisystem disorder occurs in approximately 3% of pregnancies [1], and can progress to eclampsia with life-threatening seizures. Early-onset preeclampsia is strongly associated with deficient trophoblast invasion and failure of normal spiral artery remodeling. Late-onset preeclampsia may be caused by increased maternal vascular susceptibility to the normal inflammatory state of pregnancy or atherosis of a placenta that initially developed normally [4]
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