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

作者：Palomaki Glenn E; Haddow James E; Haddow Hamish R M; Salahuddin Saira; Geahchan Carl; Cerdeira Ana Sofia; Verlohren Stefan; Perschel Frank H; Horowitz Gary; Thadhani Ravi; Karumanchi S Ananth; Rana Sarosh^*

来源：Prenatal Diagnosis, 2015, 35(4): 386-393.

DOI：10.1002/pd.4554

IntroductionPreeclampsia (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.
MethodsWomen 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.
ResultsThree hundred twenty-eight singleton pregnancies presented at 34.0weeks' 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.
ConclusionsThis 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.

• 出版日期2015-4