Literature DB >> 30527122

Prospective biomarkers in preterm preeclampsia: A review.

Fergus P McCarthy1, Roisin M Ryan2, Lucy C Chappell3.   

Abstract

Preterm pre-eclampsia (prior to 37 weeks' gestation) remains a major cause of maternal and fetal morbidity and mortality particularly in low to middle income countries. Much research has focused on first and second trimester predictors of pre-eclampsia with the aim of allowing stratification of antenatal care and trialling of potential preventative and therapeutic agents. However, none have been shown to be of benefit in randomised controlled trials. In this literature review we critically evaluate predictive and diagnostic tests for preterm pre-eclampsia and discuss their clinical use and potential value in the management of preterm pre-eclampsia. We defined preterm pre-eclampsia as pre-eclampsia occurring prior to 37 weeks' gestation. Substantial progress has been made in the development of predictive screening tests for preterm pre-eclampsia, but further research is needed prior to their introduction and integration into routine clinical practice. The performance of diagnostic tests mainly utilising angiogenic and anti-angiogenic factors for determining time to delivery in later pregnancy currently hold more promise than first trimester predictive tests, possible reflecting the heterogeneity of pre-eclampsia.
Copyright © 2018 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Hypertension; Placental growth factor; Pregnancy; Preterm pre-eclampsia; Screening

Mesh:

Substances:

Year:  2018        PMID: 30527122     DOI: 10.1016/j.preghy.2018.03.010

Source DB:  PubMed          Journal:  Pregnancy Hypertens        ISSN: 2210-7789            Impact factor:   2.899


  9 in total

1.  Identification and validation of key non-coding RNAs and mRNAs using co-expression network analysis in pre-eclampsia.

Authors:  Jing He; Kang Liu; Xiaohong Hou; Jieqiang Lu
Journal:  Medicine (Baltimore)       Date:  2021-04-09       Impact factor: 1.817

2.  Assessing the Role of Uric Acid as a Predictor of Preeclampsia.

Authors:  Ana I Corominas; Yollyseth Medina; Silvia Balconi; Roberto Casale; Mariana Farina; Nora Martínez; Alicia E Damiano
Journal:  Front Physiol       Date:  2022-01-13       Impact factor: 4.566

3.  Early prediction of preeclampsia in pregnancy with cell-free RNA.

Authors:  Mira N Moufarrej; Sevahn K Vorperian; Ronald J Wong; Ana A Campos; Cecele C Quaintance; Rene V Sit; Michelle Tan; Angela M Detweiler; Honey Mekonen; Norma F Neff; Courtney Baruch-Gravett; James A Litch; Maurice L Druzin; Virginia D Winn; Gary M Shaw; David K Stevenson; Stephen R Quake
Journal:  Nature       Date:  2022-02-09       Impact factor: 49.962

4.  First Trimester Mean Platelet Volume, Neutrophil to Lymphocyte Ratio, and Platelet to Lymphocyte Ratio Values Are Useful Markers for Predicting Preeclampsia.

Authors:  Süleyman Cemil Oğlak; Şeyhmus Tunç; Fatma Ölmez
Journal:  Ochsner J       Date:  2021

5.  Integrated Analysis Identifies Four Genes as Novel Diagnostic Biomarkers Which Correlate with Immune Infiltration in Preeclampsia.

Authors:  Mu-Yi Yang; Ming-Hui Ji; Tian Shen; Lei Lei
Journal:  J Immunol Res       Date:  2022-04-28       Impact factor: 4.493

Review 6.  Animal models of preeclampsia: investigating pathophysiology and therapeutic targets.

Authors:  Bhavisha A Bakrania; Eric M George; Joey P Granger
Journal:  Am J Obstet Gynecol       Date:  2021-03-12       Impact factor: 8.661

Review 7.  Unravelling the potential of angiogenic factors for the early prediction of preeclampsia.

Authors:  Juilee S Deshpande; Deepali P Sundrani; Akriti S Sahay; Sanjay A Gupte; Sadhana R Joshi
Journal:  Hypertens Res       Date:  2021-04-01       Impact factor: 3.872

8.  Analysis of SIRT1 Expression in Plasma and in an In Vitro Model of Preeclampsia.

Authors:  Sarah Viana-Mattioli; Priscila Nunes; Ricardo Cavalli; Valeria Sandrim
Journal:  Oxid Med Cell Longev       Date:  2020-04-28       Impact factor: 6.543

9.  Metabolomic biomarkers in midtrimester maternal plasma can accurately predict the development of preeclampsia.

Authors:  Seung Mi Lee; Yujin Kang; Eun Mi Lee; Young Mi Jung; Subeen Hong; Soo Jin Park; Chan-Wook Park; Errol R Norwitz; Do Yup Lee; Joong Shin Park
Journal:  Sci Rep       Date:  2020-09-30       Impact factor: 4.379

  9 in total

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