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Optimal First Trimester Preeclampsia Prediction: a Comparison of Multimarker Algorithm, Risk Profiles and Their Sequential Application

2016-01Journal article Open access
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dc.contributor.authorGabbay-Benziv, R
dc.contributor.authorOliveira, N
dc.contributor.authorBaschat, AA
dc.date.accessioned2017-06-08T14:08:25Z
dc.date.available2017-06-08T14:08:25Z
dc.date.issued2016-01
dc.description.abstractOBJECTIVE: To compare performance of multimarker algorithm, risk profiles and their sequential application in prediction of preeclampsia and determining potential intervention targets. STUDY DESIGN: 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. CONCLUSION: 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 treatmentpt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationPrenat Diagn. 2016 Jan;36(1):34-9pt_PT
dc.identifier.doi10.1002/pd.4707pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.17/2694
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherJohn Wiley and Sonspt_PT
dc.subjectAdolescentpt_PT
dc.subjectAdultpt_PT
dc.subjectBiomarkerspt_PT
dc.subjectFemalept_PT
dc.subjectHumanspt_PT
dc.subjectLogistic Modelspt_PT
dc.subjectMiddle Agedpt_PT
dc.subjectPre-Eclampsiapt_PT
dc.subjectPregnancypt_PT
dc.subjectProspective Studiespt_PT
dc.subjectROC Curvept_PT
dc.subjectRisk Assessmentpt_PT
dc.subjectRisk Factorspt_PT
dc.subjectUltrasonography, Prenatalpt_PT
dc.subjectYoung Adultpt_PT
dc.subjectAlgorithmspt_PT
dc.subjectDecision Support Techniquespt_PT
dc.subjectPregnancy Trimester, Firstpt_PT
dc.subjectMAC OBSpt_PT
dc.titleOptimal First Trimester Preeclampsia Prediction: a Comparison of Multimarker Algorithm, Risk Profiles and Their Sequential Applicationpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage39pt_PT
oaire.citation.issue1pt_PT
oaire.citation.startPage34pt_PT
oaire.citation.titlePrenatal Diagnosispt_PT
oaire.citation.volume36pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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