Modeling risk for severe adverse outcomes using angiogenic factor measurements in women with suspected preterm preeclampsia

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Abstract

Introduction

Preeclampsia (PE) is a pregnancy-specific syndrome associated with adverse maternal and fetal outcomes. Patient-specific risks based on angiogenic factors might better categorize those who might have a severe adverse outcome.

Methods

Women evaluated for suspected PE at a tertiary hospital (2009–2012) had pregnancy outcomes categorized as ‘referent’ or ‘severe’, based solely on maternal/fetal findings. Outcomes that may have been influenced by a PE diagnosis were considered ‘unclassified’. Soluble fms-like tyrosine kinase (sFlt1) and placental growth factor (PlGF) were subjected to bivariate discriminant modeling, allowing patient-specific risks to be assigned for severe outcomes.

Results

Three hundred twenty-eight singleton pregnancies presented at ≤34.0 weeks' gestation. sFlt1 and PlGF levels were adjusted for gestational age. Risks above 5 : 1 (10-fold over background) occurred in 77% of severe (95% CI 66 to 87%) and 0.7% of referent (95% CI <0.1 to 3.8%) outcomes. Positive likelihood ratios for the modeling and validation datasets were 19 (95% CI 6.2–58) and 15 (95% CI 5.8–40) fold, respectively.

Conclusions

This validated model assigns patient-specific risks of any severe outcome among women attending PE triage. In practice, women with high risks would receive close surveillance with the added potential for reducing unnecessary preterm deliveries among remaining women. © 2015 The Authors. Prenatal Diagnosis published by John Wiley & Sons Ltd.

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