Statistical regression model of standard and new laboratory markers and its usefulness in prediction of preeclampsia.

Objective: This study was undertaken to investigate the usefulness of angiogenic markers and standard laboratory parameters measurement after 20th week of pregnancy for the individual prediction of preeclampsia (PE).
Methods: A prospective designed study included 34 patients with PE and a control group of 35 uncomplicated pregnancies. Patients were recruited from 20th until 41st week of pregnancy at the Department of Obstetrics and Gynecology, General Hospital Celje, Slovenia. PlGF (placental growth factor), sFlt-1 (soluble fms-like tyrosine kinase 1), erythrocytes, leukocytes, platelets, hemoglobin, hematocrit, lactate dehydrogenase, aspartate aminotransferase, alanine aminotransferase, γ-glutamyl transferase, alkaline phosphatase, total bilirubin, urea, creatinine, urate, body mass index, body surface area, parity, and age were evaluated to predict the occurrence of PE based on multivariate logistic regression model.
Results: When parameters such as PlGF, sFlt-1, and urates were included into logistic regression model, we correctly classified 85% patients. With additional two models which also contained anthropometric parameters, we correctly classified 88% and 91% patients, respectively.
Conclusion: Our results demonstrated that angiogenic markers and urates individually and particularly when used as laboratory test panel have significant prognostic value in the prediction of PE.