Data · dataset · 2026
Clinical utility of 3D power doppler ultrasound and maternal biomarkers in the prediction of pre-eclampsia in high-risk pregnancies
Listed in ZivaHub and Deakin Research Online and DMU Figshare and UCL Research Data Repository — shown once because both records carry DOI 10.17034/32630826.v1
Globally, pre-eclampsia is a leading cause of maternal and fetal morbidity and mortality.
Description
Approximately 2% of all pregnant women develop pre-eclampsia; women with high-risk co-morbidities are particularly at risk with reported incidences of up to 20%. Evolving evidence suggests that an integrated screening tool combining medical history, ultrasound parameters and serum biomarkers may be of use in defining the patient-specific risk for pre-eclampsia.<br><br>Against this background, this thesis examines the ability of baseline maternal characteristics, placental vascularisation indices, uterine artery Doppler and maternal serum biomarkers (Pregnancy Associated Plasma Protein-A (PAPP-A), Placental like Growth Factor (PlGF), soluble Fms-like tyrosine kinase (sFLt-1) and soluble Endoglin (sEng)) measured in the first and second trimesters of pregnancy to predict pre-eclampsia in high-risk women.<br><br>To determine the added clinical utility and predictive value of these biophysical and biochemical parameters, a prospective longitudinal observational study of high-risk women and low-risk control participants was carried out (PREDICT).
Set within the context of a systematic review evaluating the ability of (first trimester) placental vascularisation indices to predict pre-eclampsia, findings from the PREDICT study demonstrate that placental vascularisation indices perform well for prediction of pre-eclampsia in the first trimester and that measurements are repeatable and reproducible within a high-risk cohort. The added clinical utility of uterine artery Doppler ultrasound for prediction of pre-eclampsia in high-risk women was not apparent, however the additional clinical utility of a number of first (sFlt-1, sFlt-1:PlGF) and second trimester biomarkers (PlGF:sEng) was demonstrated.
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Results from the PREDICT study indicate a potential role for a first trimester combined screening model in high-risk women incorporating information about baseline maternal characteristics, vascularisation flow index and sFlt-1. In addition, an integrated screening model combining baseline maternal characteristics and flow index is proposed for prediction of pre-eclampsia in the second trimester.<br><br>Exploratory sub-group analysis demonstrated differences in performance of placental vascularisation indices, uterine artery Doppler and serum biomarkers in prediction of pre-eclampsia.
In particular, this thesis highlights the increased prevalence of obesity in pregnancy and its subsequent impact on performance of placental vascularisation indices and maternal serum biomarkers.<br><br>Future research should focus on better understanding the underlying mechanisms for pre-eclampsia in different sub-groups. Additional research is needed to extend current understanding of pre-eclampsia risk in relation to Body Mass Index trajectory and to explore suitable biomarker threshold ranges for prediction of pre-eclampsia in obese cohorts.<br><br>Adoption of a combined screening model early in pregnancy to identify those women at highest risk of pre-eclampsia has the potential to significantly improve maternal and neonatal outcomes.
It is evident that supplementary research to investigate the role of combined screening models for pre-eclampsia within high-risk sub-groups is required before introduction in a clinical setting. In challenging the existing pathways of antenatal care, clinicians have an opportunity to provide personalised medical care for women at greatest risk.
Links
Where it is published
- DOI doi.org/10.17034/32630826.v1 ↗
DOI / persistent id · from zivahub uct ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from zivahub uct ac za
Topics
- From keywords
- Earth & Environmental Science · Earth & Environmental Science · Earth & Environmental Science · Earth & Environmental Science
- Inferred from text
- Longitudinal study 65%
Provenance · 4 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ZivaHub | oai:figshare.com:article/32630826 | 13 d ago | JSON v1 |
| Deakin Research Online | oai:figshare.com:article/32630826 | 13 d ago | JSON v1 |
| DMU Figshare | oai:figshare.com:article/32630826 | 13 d ago | JSON v1 |
| UCL Research Data Repository | oai:figshare.com:article/32630826 | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].local:field:earth-environmental | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · rdr ucl ac uk | connector:rdr_ucl_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare dmu ac uk | connector:figshare_dmu_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · dro deakin edu au | connector:dro_deakin_edu_au@1.0.0 | |
| concepts[method].local:method:longitudinal-study | enrichment · zivahub uct ac za | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/description |
| license_text | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| publication_date | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| title | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/title |