Evidence map›Paper›PMID 38568284›Full record

ArticleArchives of gynecology and obstetrics2024

Prediction of preeclampsia using maternal circulating mRNAs in early pregnancy.

Jieyun Chen, Xiuting Xu, Xingneng Xu, Si Yang, Xuwei Wang, Anqi Ye, Bolan Yu

Abstract read
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In one paragraph

Article in Archives of gynecology and obstetrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.9field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 5 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Jieyun Chen *Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, No. 63 Duobao Road, Liwan District, Guangzhou, 510150, Guangdong, China.
Xiuting Xu *Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, Guangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Xingneng XuGuangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, Guangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Si YangDepartment of Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, No. 63 Duobao Road, Liwan District, Guangzhou, 510150, Guangdong, China.
Xuwei WangGuangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, Guangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Anqi YeBioResource Research Center, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Bolan YuDepartment of Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, No. 63 Duobao Road, Liwan District, Guangzhou, 510150, Guangdong, China. yubolan-q@qq.com.ORCID 0000-0002-4498-8976
Third Affiliated Hospital of Guangzhou Medical University · CN

Funding

Guangzhou Science, Technology and Innovation Commission 2023A03J0379National Key Research and Development Program of China 2018YFC1004104
6 · The paper itself

Abstract

purposePreeclampsia (PE) is one of the most common and serious complications of pregnancy, and novel methods for the early prediction of PE are needed for clinical application.

methodsIn this study, a circulating cell-free RNA (cfRNA) panel of target genes for PE prediction was designed and validated in a case-control cohort and a nested case-control cohort. The QPCR was applied to quantify the copy number of cfRNA, and the data were normalized as multiples of the median. Ratios of serum placental growth factor (PIGF) and soluble fms-like tyrosine kinase 1 (sFLT-1) were also measured, and transabdominal ultrasonography was conducted for subjects in the prospective cohort. Binary logistic regression models for PE prediction were constructed and tested.

resultsOur results revealed that the women with PE showed significant alterations in serum cfRNA profiles from early pregnancy onward and before the onset of PE symptoms. Compared with PIGF/sFLT-1 measurement and ultrasonographic imaging, cfRNA test can detect PE at a very early stage of pregnancy. The predictive model exhibited the best performance at gestation week 32, with a detection rate of 100%. At 12 weeks of gestation, the model still manifested an area under curve (AUC) of 0.9144, and sensitivity of 1.0000. If combined with clinical parameters and ultrasonographic indicators, the model can achieve the highest AUC for PE prediction at early gestation.

conclusionMeasurement of cfRNA can be used to effectively predict PE with high performance, providing an additional method for monitoring PE throughout the course of pregnancy.

Indexed as

Cell-Free Nucleic AcidsPlacenta Growth FactorPre-EclampsiaRNA, MessengerVascular Endothelial Growth Factor Receptor-1AdultArea Under CurveBiomarkersCase-Control StudiesFemaleHumansLogistic ModelsPredictive Value of TestsPregnancyPregnancy Trimester, FirstProspective StudiesBiomarkersCell-Free Nucleic AcidsFLT1 protein, humanPlacenta Growth FactorRNA, MessengerVascular Endothelial Growth Factor Receptor-1Circulating mRNAPredictive modelPreeclampsia

Identifiers

PMID38568284
OpenAlexW4393855142

What OpenQuestion holds

Textmetadata
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.