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Early prediction of preeclampsia and small-for-gestational-age via multi-marker model in Chinese pregnancies: a prospective screening study

BACKGROUND: Recent evidence suggests early screening of preeclampsia and small-for-gestational-age (SGA) would benefit pregnancies followed by subsequent prophylactic use of aspirin. Multi-marker models have shown capability of predicting preeclampsia and SGA in first trimester. Yet the clinical fea...

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Autores principales: Zhang, Jing, Han, Luhao, Li, Wei, Chen, Qiaobin, Lei, Jie, Long, Min, Yang, Weibin, Li, Wenya, Zeng, Lizhen, Zeng, Sifan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6700825/
https://www.ncbi.nlm.nih.gov/pubmed/31426761
http://dx.doi.org/10.1186/s12884-019-2455-8
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author Zhang, Jing
Han, Luhao
Li, Wei
Chen, Qiaobin
Lei, Jie
Long, Min
Yang, Weibin
Li, Wenya
Zeng, Lizhen
Zeng, Sifan
author_facet Zhang, Jing
Han, Luhao
Li, Wei
Chen, Qiaobin
Lei, Jie
Long, Min
Yang, Weibin
Li, Wenya
Zeng, Lizhen
Zeng, Sifan
author_sort Zhang, Jing
collection PubMed
description BACKGROUND: Recent evidence suggests early screening of preeclampsia and small-for-gestational-age (SGA) would benefit pregnancies followed by subsequent prophylactic use of aspirin. Multi-marker models have shown capability of predicting preeclampsia and SGA in first trimester. Yet the clinical feasibility of combined screening model for Chinese pregnancies has not been fully assessed. The aim of this study is to evaluate the applicability of a multi-marker screening model to the prediction of preeclampsia and SGA in first trimester particularly among Chinese population. METHODS: Three thousand two hundred seventy pregnancies meeting the inclusion criteria took first-trimester screening of preeclampsia and SGA. A prior risk based on maternal characteristics was evaluated, and a posterior risk was assessed by combining prior risk with multiple of median (MoM) values of mean arterial pressure (MAP), serum placental growth factor (PLGF) and pregnancy associated plasma protein A (PAPP-A). Both risks were calculated by Preeclampsia PREDICTOR™ software, Perkin Elmer. Screening performance of prior and posterior risks for early and late preeclampsia by using PREDICTOR software was shown by Receiver Operating Characteristics (ROC) curves. The estimation of detection rates and false positive rates of delivery with both preeclampsia and SGA was made. RESULTS: Eight cases developed early preeclampsia (0.24%) and 35 were diagnosed as late preeclampsia (1.07%). Five with early preeclampsia and ten with late preeclampsia later delivered SGA newborns (0.46%); 84 without preeclampsia gave birth to the SGAs (2.57%). According to ROC curves, posterior risks performed better than prior risks in terms of preeclampsia, especially in early preeclampsia. At 10% false positive rate, detection rates of early and late preeclampsia were 87.50 and 48.57%, detection rates of early and late SGA were 41.67 and 28.00%, respectively. For SGA, detection rates in cases with preeclampsia were much higher than those in absence of it. CONCLUSIONS: This study demonstrates that combined screening model could be useful for predicting early preeclampsia in Chinese pregnancies. Furthermore, the performance of SGA screening by same protocol is strongly associated with preeclampsia. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12884-019-2455-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-67008252019-08-26 Early prediction of preeclampsia and small-for-gestational-age via multi-marker model in Chinese pregnancies: a prospective screening study Zhang, Jing Han, Luhao Li, Wei Chen, Qiaobin Lei, Jie Long, Min Yang, Weibin Li, Wenya Zeng, Lizhen Zeng, Sifan BMC Pregnancy Childbirth Research Article BACKGROUND: Recent evidence suggests early screening of preeclampsia and small-for-gestational-age (SGA) would benefit pregnancies followed by subsequent prophylactic use of aspirin. Multi-marker models have shown capability of predicting preeclampsia and SGA in first trimester. Yet the clinical feasibility of combined screening model for Chinese pregnancies has not been fully assessed. The aim of this study is to evaluate the applicability of a multi-marker screening model to the prediction of preeclampsia and SGA in first trimester particularly among Chinese population. METHODS: Three thousand two hundred seventy pregnancies meeting the inclusion criteria took first-trimester screening of preeclampsia and SGA. A prior risk based on maternal characteristics was evaluated, and a posterior risk was assessed by combining prior risk with multiple of median (MoM) values of mean arterial pressure (MAP), serum placental growth factor (PLGF) and pregnancy associated plasma protein A (PAPP-A). Both risks were calculated by Preeclampsia PREDICTOR™ software, Perkin Elmer. Screening performance of prior and posterior risks for early and late preeclampsia by using PREDICTOR software was shown by Receiver Operating Characteristics (ROC) curves. The estimation of detection rates and false positive rates of delivery with both preeclampsia and SGA was made. RESULTS: Eight cases developed early preeclampsia (0.24%) and 35 were diagnosed as late preeclampsia (1.07%). Five with early preeclampsia and ten with late preeclampsia later delivered SGA newborns (0.46%); 84 without preeclampsia gave birth to the SGAs (2.57%). According to ROC curves, posterior risks performed better than prior risks in terms of preeclampsia, especially in early preeclampsia. At 10% false positive rate, detection rates of early and late preeclampsia were 87.50 and 48.57%, detection rates of early and late SGA were 41.67 and 28.00%, respectively. For SGA, detection rates in cases with preeclampsia were much higher than those in absence of it. CONCLUSIONS: This study demonstrates that combined screening model could be useful for predicting early preeclampsia in Chinese pregnancies. Furthermore, the performance of SGA screening by same protocol is strongly associated with preeclampsia. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12884-019-2455-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-08-19 /pmc/articles/PMC6700825/ /pubmed/31426761 http://dx.doi.org/10.1186/s12884-019-2455-8 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Zhang, Jing
Han, Luhao
Li, Wei
Chen, Qiaobin
Lei, Jie
Long, Min
Yang, Weibin
Li, Wenya
Zeng, Lizhen
Zeng, Sifan
Early prediction of preeclampsia and small-for-gestational-age via multi-marker model in Chinese pregnancies: a prospective screening study
title Early prediction of preeclampsia and small-for-gestational-age via multi-marker model in Chinese pregnancies: a prospective screening study
title_full Early prediction of preeclampsia and small-for-gestational-age via multi-marker model in Chinese pregnancies: a prospective screening study
title_fullStr Early prediction of preeclampsia and small-for-gestational-age via multi-marker model in Chinese pregnancies: a prospective screening study
title_full_unstemmed Early prediction of preeclampsia and small-for-gestational-age via multi-marker model in Chinese pregnancies: a prospective screening study
title_short Early prediction of preeclampsia and small-for-gestational-age via multi-marker model in Chinese pregnancies: a prospective screening study
title_sort early prediction of preeclampsia and small-for-gestational-age via multi-marker model in chinese pregnancies: a prospective screening study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6700825/
https://www.ncbi.nlm.nih.gov/pubmed/31426761
http://dx.doi.org/10.1186/s12884-019-2455-8
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