Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/8270
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dc.rights.licenseopenAccess-
dc.contributor.authorRudic J.-
dc.contributor.authorRaicevic, Sasa-
dc.contributor.authorBabic, Goran-
dc.date.accessioned2020-09-19T15:15:40Z-
dc.date.available2020-09-19T15:15:40Z-
dc.date.issued2019-
dc.identifier.issn1820-8665-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/8270-
dc.description.abstract© 2019, University of Kragujevac, Faculty of Science. All rights reserved. Preeclampsia is one of the leading causes of maternal and perinatal morbidity and mortality, usually characterized by hypertension and proteinuria. Despite high incidence of preeclampsia the pathophysiological basis of preeclampsia is still not clear and there are a number of mechanisms and signaling pathways that intertwine. It is very important to develop specific and reliable predictive algorithms in order to enable early initiation of therapy due to facts that incidence of preeclampsia has upward trend and that cause adverse maternal and fetal outcome. Some of the most commonly used methods for prediction of preeclampsia include uterine artery Doppler velocimetry, determination of some microRNA, such as miR-210, and assessment of various pro-angiogenic and anti-angiogenic factors from blood. Angiogenic factors that possibly have most important role in pathogenesis of preeclampsia are vascular endothelial growth factor (VEGF) and placental growth factor (PlGF), which promote angiogenesis, and soluble fms-like tyrosine kinase-1 (sFlt1) and soluble form of endoglin (s-Eng), which exhibit anti-angiogenic properties. Aggravating circumstance is that preeclampsia has heterogeneous origin, and due to this fact, the value of individual markers can vary significantly. There is a constant tendency for creating comprehensive algorithm for prediction of preeclampsia which would be sufficiently specific and sensitive, and in the same time cheap and available. In that sense, new clinical studies are needed to show the most effective combination of parameters in the predeclampsia prediction.-
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.sourceSerbian Journal of Experimental and Clinical Research-
dc.titlePreeclampsia – Prediction and monitoring factors-
dc.typearticle-
dc.identifier.doi10.2478/sjecr-2018-0026-
dc.identifier.scopus2-s2.0-85078921406-
Appears in Collections:Faculty of Medical Sciences, Kragujevac

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