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Updated: Jun 3, 2026

09:03
Semiconductor Sequencing for Preimplantation Genetic Testing for Aneuploidy
Published on: August 25, 2019
Beyond the first trimester screen: can we predict who will choose invasive testing?
Suzanne van Landingham1, Jessica Bienstock, Elizabeth Wood Denne
1Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. swestbr3@jhmi.edu.
Summary
Maternal age, race, and marital status influence decisions on invasive prenatal testing after a positive aneuploidy screen. Understanding these factors can help healthcare providers identify patients needing more education.
Area of Science:
- Maternal-Fetal Medicine
- Prenatal Diagnostics
- Genetics
Background:
- A positive first trimester aneuploidy screen is a common indication for invasive prenatal testing.
- Patient decisions regarding invasive testing are complex and influenced by various factors.
Purpose of the Study:
- To identify demographic and clinical factors correlating with invasive prenatal testing uptake in pregnancies with a positive first trimester aneuploidy screen.
- To understand patient decision-making beyond the initial screening result.
Main Methods:
- Retrospective cohort study of singleton pregnancies with positive first trimester screens.
- Analysis of demographic factors and numerical screen results against invasive testing uptake.
- Utilized risk difference calculations and linear modeling for statistical analysis.
Main Results:
- Maternal age, race, residual risk, marital status, and year of screen significantly correlated with invasive testing uptake.
- Family history was predictive only for patients under 35.
- Specific risk types (e.g., trisomy 21 vs. 18/13) and ART status did not predict uptake.
Conclusions:
- Demographic factors play a significant role in the decision to undergo invasive prenatal testing after a positive screen.
- Identifying at-risk patients can help providers tailor educational interventions.
- Further research is needed to explore the impact of misinformation and differing value systems on testing decisions.
