Evidence map›Paper›PMID 29970026›Full record

Trial reportBMC pregnancy and childbirth2018

Prediction of pre-eclampsia and its subtypes in high-risk cohort: hyperglycosylated human chorionic gonadotropin in multivariate models.

Katja Murtoniemi, Pia M Villa, Jaakko Matomäki, Elina Keikkala, Piia Vuorela, Esa Hämäläinen, Eero Kajantie, Anu-Katriina Pesonen, Katri Räikkönen, Pekka Taipale and 2 more

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC pregnancy and childbirth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
1.4field-weighted citation impact, top 17% 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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.

  1. Pooled it
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  12. Predictive models of hypertensive disorders in pregnancy based on support vector machine algorithm.Technology and health care : official journal of the European Society for Engineering and Medicine · 2020
    Article
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

12 authors at 4 institutions in 1 country.

Katja MurtoniemiUniversity of Helsinki and Turunmaa District Hospital, Gynaecological Outpatient Clinic, Hospital District of Southwest Finland, Kaskenkatu 13, 20700, Turku, Finland. katja.murtoniemi@helsinki.fi.ORCID http://orcid.org/0000-0001-8971-2984
Pia M VillaObstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, P.O. Box 140, FI-00029, Helsinki, Haartmaninkatu 2, Finland.
Jaakko MatomäkiDepartment of Biostatistics, University of Turku, FI-20014 TURUN YLIOPISTO, Turku, Finland.
Elina KeikkalaDepartment of Obstetrics and Gynaecology, Oulu University Hospital and University of Oulu, Kajaanintie 50, 90220, Oulu, Finland.
Piia VuorelaObstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, P.O. Box 140, FI-00029, Helsinki, Haartmaninkatu 2, Finland.
Esa HämäläinenHUSLAB and Department of Clinical Chemistry, University of Helsinki and Helsinki University Hospital, PO BOX 720, 00029, Helsinki, Finland.
Eero KajantieHospital for Children and Adolescents, University of Helsinki and Helsinki University Hospital, Stenbäckinkatu 11, P.O. Box 281, FI-00029, Helsinki, Finland.
Anu-Katriina PesonenDepartment of Psychology and Logopedics, University of Helsinki, Siltavuorenpenger 1-5, P.O. Box 9, FI-00014, Helsinki, Finland.
Katri RäikkönenDepartment of Psychology and Logopedics, University of Helsinki, Siltavuorenpenger 1-5, P.O. Box 9, FI-00014, Helsinki, Finland.
Pekka TaipaleSuomen Terveystalo Oy, Asemakatu 22-24, 70100, Kuopio, Finland.
Ulf-Håkan StenmanHUSLAB and Department of Clinical Chemistry, University of Helsinki and Helsinki University Hospital, PO BOX 720, 00029, Helsinki, Finland.
Hannele LaivuoriInstitute for Molecular Medicine and Medical and Clinical Genetics, University of Helsinki, P.O. Box 63, FI-00014, Helsinki, Finland.
University of Helsinki · FIEtelä-Karjalan sosiaali ja terveyspiiri · FIOulu University Hospital · FIUniversity of Turku · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe proportion of hyperglycosylated human chorionic gonadotropin (hCG-h) to total human chorionic gonadotropin (%hCG-h) during the first trimester is a promising biomarker for prediction of early-onset pre-eclampsia. We wanted to evaluate the performance of clinical risk factors, mean arterial pressure (MAP), %hCG-h, hCGβ, pregnancy-associated plasma protein A (PAPP-A), placental growth factor (PlGF) and mean pulsatility index of the uterine artery (Uta-PI) in the first trimester in predicting pre-eclampsia (PE) and its subtypes early-onset, late-onset, severe and non-severe PE in a high-risk cohort.

methodsWe studied a subcohort of 257 high-risk women in the prospectively collected Prediction and Prevention of Pre-eclampsia and Intrauterine Growth Restriction (PREDO) cohort. Multivariate logistic regression was used to construct the prediction models. The first model included background variables and MAP. Additionally, biomarkers were included in the second model and mean Uta-PI was included in the third model. All variables that improved the model fit were included at each step. The area under the curve (AUC) was determined for all models.

resultsWe found that lower levels of serum PlGF concentration were associated with early-onset PE, whereas lower %hCG-h was associated with the late-onset PE. Serum PlGF was lower and hCGβ higher in severe PE, while %hCG-h and serum PAPP-A were lower in non-severe PE. By using multivariate regression analyses the best prediction for all PE was achieved with the third model: AUC was 0.66, and sensitivity 36% at 90% specificity. Third model also gave the highest prediction accuracy for late-onset, severe and non-severe PE: AUC 0.66 with 32% sensitivity, AUC 0.65, 24% sensitivity and AUC 0.60, 22% sensitivity at 90% specificity, respectively. The best prediction for early-onset PE was achieved using the second model: AUC 0.68 and 20% sensitivity at 90% specificity.

conclusionsAlthough the multivariate models did not meet the requirements to be clinically useful screening tools, our results indicate that the biomarker profile in women with risk factors for PE is different according to the subtype of PE. The heterogeneous nature of PE results in difficulty to find new, clinically useful biomarkers for prediction of PE in early pregnancy in high-risk cohorts.

trial registrationInternational Standard Randomised Controlled Trial number ISRCTN14030412 , Date of registration 6/09/2007, retrospectively registered.

Indexed as

Pre-EclampsiaUterine ArteryAdultArea Under CurveBiomarkersBlood Pressure DeterminationChorionic GonadotropinChorionic Gonadotropin, beta Subunit, HumanFemaleHumansPlacenta Growth FactorPregnancyPregnancy-Associated Plasma Protein-APregnancy, High-RiskPregnancy Trimester, FirstPrognosisBiomarkersChorionic GonadotropinChorionic Gonadotropin, beta Subunit, Humanglycosylated HCGPlacenta Growth FactorPregnancy-Associated Plasma Protein-ABiomarkersEarly-onset pre-eclampsiahCGβHyperglycosylated human chorionic gonadotropinLate-onset pre-eclampsiaPlacental growth factorPre-eclampsiaPregnancy associated plasma protein aScreeningSevere pre-eclampsia

Identifiers

PMID29970026
PMCPMC6029382
OpenAlexW2810675736

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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.