Dataset Information

Predictive Performance of Placental Protein 13 for Screening Preeclampsia in the First Trimester: A Systematic Review and Meta-Analysis.

ABSTRACT: Preeclampsia is a pregnancy-specific syndrome that affects maternal and neonatal mortality. Several serum biomarkers can be used to predict preeclampsia. Among these proteins, placental protein 13 (PP13) has received progressively more interest in recent studies. The decrease in PP13 expression is one of the earliest signs for the development of preeclampsia and has shown its predictive performance for preeclampsia. In this meta-analysis, we collected 17 observational studies with 40,474 pregnant women. The overall sensitivity of PP13 to predict preeclampsia was 0.62 [95% confidence interval (CI) = 0.49-0.74], the specificity was 0.84 (95%CI = 0.81-0.86), and the diagnostic odds ratio was nine (95%CI = 5-15). The area under the curve for summary receiver operating characteristic was 0.84. We then chose the early-onset preeclampsia as a subgroup. The sensitivity of early-onset subgroup was 0.63 (95%CI = 0.58-0.76), the specificity was 0.85 (95%CI = 0.82-0.88), and the diagnostic odds ratio was 10 (95%CI = 6-18). The findings of our meta-analysis indicate that PP13 may be an effective serum biomarker for the predictive screening of preeclampsia. Nonetheless, large prospective cohort studies and randomized controlled trials are expected to uncover its application in clinical practice. The heterogeneity of the original trials may limit the clinical application of PP13. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=188948 The meta-analysis was registered in PROSPERO (CRD42020188948).

SUBMITTER: Wu Y

PROVIDER: S-EPMC8640131 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Biomarkers commonly assessed in prenatal screening have been associated with a number of adverse perinatal and birth outcomes. However, it is not clear whether first trimester measurements of prenatal screening biomarkers are associated with subsequent risk of gestational diabetes mellitus (GDM). We aimed to systematically review and statistically summarize studies assessing the relationship between first trimester prenatal screening biomarker levels and GDM development. We comprehensively searched PubMed/MEDLINE, EMBASE, CINAHL, and Scopus (from inception through January 2018) and manually searched the reference lists of all relevant articles. We included original, published, observational studies examining the association of first trimester pregnancy associated plasma protein-A (PAPP-A) and/or free β-human chorionic gonadotropin (free β-hCG) levels with GDM diagnosis. Mean differences were calculated comparing PAPP-A and free β-hCG multiples of median (MoM) levels between women who developed GDM and those who did not and were subsequently pooled using two-sided random-effects models. Our meta-analysis of 13 studies on PAPP-A and nine studies on free β-hCG indicated that first trimester MoM levels for both biomarkers were lower in women who later developed GDM compared to women who remained normoglycemic throughout pregnancy (MD -0.17; 95% CI -0.24, -0.10; MD -0.04; 95% CI -0.07-0.01). There was no evidence for between-study heterogeneity among studies on free β-hCG (I2 = 0%). A high level of between-study heterogeneity was detected among the studies reporting on PAPP-A (I2 = 90%), but was reduced after stratifying by geographic location, biomarker assay method, and timing of GDM diagnosis. Our meta-analysis indicates that women who are diagnosed with GDM have lower first trimester levels of both PAPP-A and free β-hCG than women who remain normoglycemic throughout pregnancy. Further assessment of the predictive capacity of these biomarkers within large, diverse populations is needed.

Project description:IntroductionThe aim of this cross-sectional questionnaire study was to investigate motivation to participate in a possible new screening for preeclampsia in the first trimester of pregnancy among Danish pregnant women through a questionnaire based on Theory of Planned Behavior developed for this specific purpose. The new screening combines maternal characteristics with mean arterial pressure, uterine artery pulsatility index and biochemical markers to predict the risk of preeclampsia, whereas the current Danish screening uses maternal characteristics alone.Material and methodsParticipation was offered to a proportion of women attending a first or a second trimester screening scan at two University Hospitals in Copenhagen. The questionnaire was set up in REDCap® and answers were entered directly into the database, which was accessed via a QR-code.ResultsWe invited 772 pregnant women to participate in the questionnaire survey between November 2021 and April 2022 at Copenhagen University Hospital Rigshospitalet (study site one) (n = 238) and Copenhagen University Hospital Hvidovre (study site two) (n = 534). The response rate was 71.8% (171/238) at study site one and 33.9% (181/534) at study site two. A total of 352 women were included in the study (total participation rate 45.6%). Most women had a positive attitude towards preeclampsia screening in pregnancy, and 99.4% said they would participate in a risk assessment for preeclampsia if given the opportunity. A total of 97.4% answered "yes" to whether a first trimester preeclampsia screening should be offered to all pregnant women in Denmark. Positive motivation to participate in preeclampsia screening was correlated with having a network with a positive attitude towards preeclampsia screening.ConclusionsThe results of this study indicate that Danish pregnant women have a positive attitude towards participation in a first trimester screening for preeclampsia. This observation might be useful in relation to possible future implementation in Denmark.

Dataset Information

Predictive Performance of Placental Protein 13 for Screening Preeclampsia in the First Trimester: A Systematic Review and Meta-Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets