title: Optimal first trimester preeclampsia prediction: a comparison of multimarker algorithm, risk profiles and their sequential application.
abstract: OBJECTIVE
  To compare performance of multimarker algorithm, risk profiles and their sequential application in prediction of preeclampsia and determining potential intervention targets.
  
  
  METHODS
  Maternal characteristics, ultrasound variables and serum biomarkers were collected prospectively at first trimester. Univariate analysis identified preeclampsia associated variables followed by logistic regression analysis to determine the prediction rule. Combined characteristics of the cardiovascular, metabolic and the personal risk factors were compared to the multimarker algorithm and the sequential application of both methods.
  
  
  RESULTS
  Out of 2433 women, 108 developed preeclampsia (4.4%). Probability scores considering nulliparity, prior preeclampsia, body mass index, diastolic blood pressure and placental growth factor had an area under the receiver operating characteristic curve 0.784 (95% CI = 0.721-0.847). While the multimarker algorithm had the lowest false negative rate, sequential application of cardiovascular and metabolic risk profiles in screen positives reduced false positives by 26% and identified blood pressure and metabolic risk in 49/54 (91%) women with subsequent preeclampsia as treatable risk factors.
  
  
  CONCLUSIONS
  Sequential application of a multimarker algorithm followed by determination of treatable risk factors in screen positive women is the optimal approach for first trimester preeclampsia prediction and identification of women that may benefit from targeted metabolic or cardiovascular treatment. © 2015 John Wiley & Sons, Ltd.
authors.affiliation: Helen Schneider Hospital for Women, Rabin Medical Center, PetachTikva; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
authors.forename: R
authors.identifier: http://orcid.org/0000-0001-6887-6314
authors.initials: R
authors.lastname: Gabbay-Benziv
authors.affiliation: Department of Obstetrics and Gynecology, Maternidade Dr. Alfredo da Costa, Lisbon, Portugal.
authors.forename: N
authors.initials: N
authors.lastname: Oliveira
authors.affiliation: Department of Gynecology and Obstetrics, Johns Hopkins School of Medicine, Baltimore, MD, United States.
authors.forename: A A
authors.initials: AA
authors.lastname: Baschat
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D015415:Biomarkers / Q000097:blood; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D011225:Pre-Eclampsia / Q000097:blood / Q000175:diagnosis* / Q000000981:diagnostic imaging; D011247:Pregnancy; D011261:Pregnancy Trimester, First / Q000097:blood; D011446:Prospective Studies; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D016216:Ultrasonography, Prenatal; D055815:Young Adult
chemical_list: D015415:Biomarkers