Novel screening test may improve preeclampsia detection in early pregnancy
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Key takeaways:
- A blood test combined with ultrasound data and other factors may help predict preeclampsia during the first trimester.
- The false-positive rate of 16% was an improvement over a different predictive model.
A first-trimester algorithm that includes a blood test, ultrasound data and maternal characteristics predicted two-thirds of preterm preeclampsia and three-quarters of early-onset preeclampsia among nulliparous women, researchers reported.
The detection rate using the Fetal Medicine Foundation (FMF) algorithm, which combines maternal history, biophysical markers, biochemical markers and mean uterine artery pulsatility index, is higher than the current approach based on risk factors and is superior to the ACOG guidelines criteria, where the detection rate was 62%, Emmanuel Bujold, MD, MSc, FRCSC, professor in the department of obstetrics and gynecology of Laval University School of Medicine in Quebec, Canada, and colleagues wrote in Hypertension. The screening method could potentially lead to more women at risk for preeclampsia initiating aspirin therapy before the 16th week of gestation, as recommended by several professional societies, according to the researchers.
“It is now possible to predict and prevent severe and early forms of preeclampsia, one of the worst complications of pregnancy,” Bujold told Healio. “This research confirms that a visit involving the measurement of a patient's height, weight and blood pressure, accompanied by a blood test and ultrasound scan, would now make it possible to assess the risk of severe preeclampsia with a high degree of accuracy.”
Using personalized screenings
For the prospective study, Bujold and colleagues analyzed data from 7,554 nulliparous women recruited from 11 to 14 weeks’ gestation and followed until delivery. The mean age of participants was 29 years, 92% were white and 4% were Black, and women taking antihypertensive medications or low-dose aspirin were excluded. Researchers assessed maternal characteristics and measured mean arterial blood pressure, levels of pregnancy-associated plasma protein A (PAPP-A) and placental growth factor (P1GF) in maternal blood, and uterine artery pulsatility index via ultrasound. Researchers then calculated risk for preterm preeclampsia according to the FMF algorithm using all variables, and then identified women as high risk or not for preeclampsia according to ACOG guidelines. The primary outcome was preeclampsia with delivery before 37 weeks of gestation, reported as preterm preeclampsia. The secondary outcome was preeclampsia with delivery before 34 weeks of gestation, reported as early-onset preeclampsia.
Within the cohort, 7,325 women remained eligible after 20 weeks’ gestation; 0.9% developed preterm preeclampsia 0.3% developed early-onset preeclampsia.
Using the FMF algorithm with a cutoff of less than one in 110 for preterm preeclampsia, the detection rate was 63.1% for preterm preeclampsia and 77.3% for early-onset preeclampsia. The false-positive rate was 15.8%. Using risk factor-based ACOG criteria, equivalent detection rates would have been 61.5% and 59.1%, respectively, with a false-positive rate of 34.3%, or more than twice the false-positive rate of the FMF screening model, according to the researchers.
“Considering that taking aspirin can prevent up to 62% of preterm preeclampsia and 80% of early-onset preeclampsia, or even more with optimal compliance, we estimated that the number needed to treat is 46 women for the prevention of one case of preterm preeclampsia and less than 89 women for the prevention of one case of early-onset preeclampsia in our population of nulliparous women using the FMF algorithm, in comparison with 101 women for the prevention of one case of preterm preeclampsia and 250 women for the prevention of one case of early-onset preeclampsia using the ACOG model,” the researchers wrote.
Preventing severe preeclampsia
The researchers noted that the study excluded many women at high risk for preterm preeclampsia because they were treated with antihypertensive drugs or aspirin, and that about one-third of participants’ blood samples were analyzed after long transportation on dry ice requiring freezing and thawing once before the analysis. Researchers added that immediate analysis of blood samples may have improved the screening process.
“Just as we can prevent severe forms of preeclampsia with aspirin, this screening will make it possible to prevent preeclampsia and its consequences for both mother and child,” Bujold told Healio. “We must now work to make this test accessible to all pregnant women. We need translational research to determine solutions to any limits for universal access."
For more information:
Emmanuel Bujold, MD, MSc, FRCSC, can be reached at emmanuel.bujold@crchudequebec.ulaval.ca
Perspective
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Sadiya Sana Khan, MD, MSc, FACC, FAHA
Preeclampsia has many consequences for the person who is pregnant as well as the baby. To predict and prevent it is important. We have a prevention strategy that is really effective — something as simple as over-the-counter aspirin — that we should initiate before the 16th week of pregnancy for at-risk women.
The generalizability of risk-prediction tools is very important. I applaud the authors on taking this FMF model and asking: “How well does this work in our population?” It includes biomarkers and ultrasound measures that are not routinely collected among pregnant people in the United States. That is perhaps the biggest concern or limitation: its generalizability to U.S. populations. There are also concerns around cost and the challenges for implementation. Are there simpler models that could be useful and be more translatable, particularly in low-resource settings? We know there are challenges, particularly in rural areas, of even getting prenatal care or higher-level care.
It is also important to look at the diversity of the sample. We know that preeclampsia disproportionately affects people from minoritized populations and people living in low-income neighborhoods. A score like this may actually widen health disparities. We also need to be very careful about incorporating race and ethnicity into any clinical care model.
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