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Teratogenicity

Teratogenicity

The ability of a drug to produce structural deformations and functional abnormalities in the developing embryo or the fetus is called teratogenicity, and the drug producing this effect is known as a teratogen. Teratogenic effects include stillbirth, miscarriage, intrauterine growth restriction, and neurocognitive delay. A teratogen may affect the embryo at different stages of development, which is important in determining the type and extent of the damage. During blastocyst formation, the early...

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Assessment of Maternal Vascular Remodeling During Pregnancy in the Mouse Uterus

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First-Trimester Prediction Models Based on Maternal Characteristics for Adverse Pregnancy Outcomes: A Systematic

Jacintha C A van Eekhout¹, Ellis C Becking², Peter G Scheffer²

¹Department of Genetics, Erasmus Medical Centre, Rotterdam, The Netherlands.

BJOG : an International Journal of Obstetrics and Gynaecology

|October 25, 2024

Summary

First-trimester prediction models for adverse pregnancy outcomes like preeclampsia (PE) and gestational diabetes mellitus (GDM) are numerous. However, most models have a high risk of bias and lack sufficient validation, limiting their clinical use.

Keywords:

adverse pregnancy outcomes first trimester gestational diabetes prediction models preeclampsia risk stratification small for gestational age neonates spontaneous preterm birth

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Area of Science:

Obstetrics and Gynecology
Maternal-Fetal Medicine
Epidemiology

Background:

Early risk stratification for adverse pregnancy outcomes (APOs) is crucial for timely interventions.
APOs include preeclampsia (PE), small-for-gestational-age neonates (SGA), spontaneous preterm birth (sPTB), and gestational diabetes mellitus (GDM).

Purpose of the Study:

To conduct a systematic review and meta-analysis of prediction models developed in the first trimester for APOs.
To evaluate the performance, validation, and risk of bias of these models.

Main Methods:

A systematic search of the PubMed database was performed up to June 6, 2024.
Included were first-trimester prediction models based solely on maternal characteristics, excluding those with biochemical or ultrasound markers.
Data extraction and risk of bias assessment were conducted using PROBAST by two independent reviewers.

Main Results:

77 articles were included, detailing 91 prediction models for PE, SGA, sPTB, and GDM.
Median AUCs varied: PE (0.75), SGA (nulliparous: 0.62; multiparous: 0.74), sPTB (nulliparous: 0.65; multiparous: 0.71), and GDM (0.71).
High risk of bias was found in 94.5% of developed models, and only 43.9% underwent internal validation, while 49.5% had external validation.

Conclusions:

Numerous first-trimester prediction models exist for APOs.
However, significant methodological limitations, including high risk of bias and inadequate validation, are prevalent.
Improvements in methodological quality and clinical utility assessment are necessary before widespread adoption.