More than half of all cases of preeclampsia occur in healthy first-time pregnant women. Our aim was to develop a method to predict those at risk by combining clinical factors and measurements of biomarkers in women recruited to the Screening for Pregnancy Endpoints (SCOPE) study of low-risk nulliparous women. Forty-seven biomarkers identified on the basis of (1) association with preeclampsia, (2) a biological role in placentation, or (3) a role in cellular mechanisms involved in the pathogenesis of preeclampsia were measured in plasma sampled at 14 to 16 weeks' gestation from 5623 women. The cohort was randomly divided into training (n=3747) and validation (n=1876) cohorts. Preeclampsia developed in 278 (4.9%) women, of whom 28 (0.5%) developed early-onset preeclampsia. The final model for the prediction of preeclampsia included placental growth factor, mean arterial pressure, and body mass index at 14 to 16 weeks' gestation, the consumption of ≥3 pieces of fruit per day, and mean uterine artery resistance index. The area under the receiver operator curve (95% confidence interval) for this model in training and validation cohorts was 0.73 (0.70-0.77) and 0.68 (0.63-0.74), respectively. A predictive model of early-onset preeclampsia included angiogenin/placental growth factor as a ratio, mean arterial pressure, any pregnancy loss <10 weeks, and mean uterine artery resistance index (area under the receiver operator curve [95% confidence interval] in training and validation cohorts, 0.89 [0.78-1.0] and 0.78 [0.58-0.99], respectively). Neither model included pregnancy-associated plasma protein A, previously reported to predict preeclampsia in populations of mixed parity and risk. In nulliparous women, combining multiple biomarkers and clinical data provided modest prediction of preeclampsia.
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http://dx.doi.org/10.1161/HYPERTENSIONAHA.114.03578 | DOI Listing |
Ultrasound Obstet Gynecol
January 2025
Harris Birthright Research Centre for Fetal Medicine, King's College Hospital, London, UK.
Objective: Globally, one in four pregnant women is classified as overweight or obese, based on their prepregnancy body mass index (BMI). Obese pregnant women are at increased risk of adverse pregnancy outcomes and long-term cardiovascular disease that occurs earlier in life. This study aimed to assess maternal hemodynamic and vascular parameters at 35-37 weeks' gestation, to understand the alterations that may occur in association with increased maternal BMI and gestational weight gain, and to evaluate obesity-related pregnancy outcomes.
View Article and Find Full Text PDFBMC Health Serv Res
January 2025
Faculty of Health Sciences, Durban University of Technology, Durban, 4001, South Africa.
Introduction: Prenatal care is crucial, but accessing healthcare services has been a challenge for pregnant homeless women in Africa. The majority in this marginalised group are not screened for common pregnancy complications such as preeclampsia, infection, and stillbirth. Therefore, this scoping review aims to explore the barriers to accessing prenatal healthcare services for pregnant homeless women in Africa.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
January 2025
Genetic Program, North York General Hospital, Toronto, ON, Canada.
Background: Preeclampsia significantly impacts maternal and perinatal health. Early screening using advanced models and primary prevention with low-dose acetylsalicylic acid for high-risk populations is crucial to reduce the disease's incidence. This study assesses the feasibility of implementing preterm preeclampsia screening and prevention by leveraging information from our current aneuploidy screening program in a real-world setting with geographic separation clinical site and laboratory analysis site.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Gynecology and Obstetrics, First Hospital of Jilin University, Changchun, 130031, Jilin, China.
Preeclampsia (PE) is a major pregnancy-specific cardiovascular complication posing latent life-threatening risks to mothers and neonates. The contribution of immune dysregulation to PE is not fully understood, highlighting the need to explore molecular markers and their relationship with immune infiltration to potentially inform therapeutic strategies. We used bioinformatics tools to analyze gene expression data from the Gene Expression Omnibus (GEO) database using the GEOquery package in R.
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