High-Risk Pregnancies & Fetal Abnormalities: Seoul Study Reveals 60% Rate
- Nearly six in ten births at Asan Medical Center in Seoul, South Korea, over the past three years have been classified as high-risk pregnancies or involved serious fetal...
- The hospital’s analysis of 2023 through 2025 data revealed that 4,163 out of 6,999 deliveries – approximately 59.5% – fell into high-risk categories.
- Preeclampsia, a pregnancy-specific condition characterized by high blood pressure and signs of damage to another organ system, can lead to serious complications for both mother and baby.
Nearly six in ten births at Asan Medical Center in Seoul, South Korea, over the past three years have been classified as high-risk pregnancies or involved serious fetal conditions, according to data released . This represents a significant proportion of deliveries facing potential complications, highlighting the increasing complexity of prenatal care.
The hospital’s analysis of through data revealed that 4,163 out of 6,999 deliveries – approximately 59.5% – fell into high-risk categories. These categories encompass a range of maternal and fetal health concerns, including severe preeclampsia, preterm labor, preterm premature rupture of membranes, placental abruption, placenta previa, abnormal amniotic fluid levels, cervical incompetence, and intrauterine growth restriction. Severe fetal anomalies were identified in 1,517 cases over the same period.
Preeclampsia, a pregnancy-specific condition characterized by high blood pressure and signs of damage to another organ system, can lead to serious complications for both mother and baby. Placental abruption involves the premature separation of the placenta from the uterine wall, potentially causing severe bleeding and fetal distress. Intrauterine growth restriction (IUGR) refers to a condition where a fetus doesn’t grow at the expected rate, which can have long-term health consequences.
The increasing prevalence of high-risk pregnancies underscores the need for advanced diagnostic tools and specialized care. Chromosomal microarray analysis (CMA) is one such tool gaining prominence in prenatal diagnosis. A recent study analyzing data from 4,211 fetuses undergoing CMA with high-risk prenatal indications found an overall detection rate of 11.4% for chromosomal abnormalities. This included 5.82% with abnormal chromosome numbers and 5.58% with copy number variants – alterations in the amount of DNA.
The study, which focused on pregnancies in China, categorized indications for CMA and found varying detection rates. For pregnant women with advanced maternal age (AMA), the detection rate was 6.42%. For those with high-risk maternal serum screening (MSS) results, it was 6.01%. However, the highest detection rate – 39.09% – was observed in pregnancies with abnormal non-invasive prenatal testing (NIPT) results. Abnormal ultrasound results yielded a detection rate of 9.21%, while other indications showed a rate of 5.1%.
Copy number variants (CNVs) are particularly important as they can be associated with a range of developmental and intellectual disabilities. The study identified clinically significant CNVs in 3.78% of cases and variants of uncertain significance in 1.8% of cases. This highlights the complexity of interpreting CMA results and the need for careful genetic counseling.
The outcomes of the pregnancies analyzed in the CMA study were also tracked. The majority – 87.32% (3677 out of 4211) – resulted in the birth of normal infants. However, 10.97% (462 out of 4211) of pregnancies were terminated, and 1.21% (51 out of 4211) resulted in the birth of infants with abnormalities. A small percentage, 0.50% (21 out of 4211), refused follow-up.
The data from Asan Medical Center also points to the increasing need for specialized care for specific fetal anomalies. Conditions like congenital heart defects and congenital diaphragmatic hernia require accurate prenatal diagnosis and often necessitate immediate emergency treatment after birth. The hospital emphasized that it handles a substantial portion of the country’s most critical fetal treatments.
Researchers are also exploring the use of machine learning to identify high-risk pre-term pregnancies. A study analyzing fetal heart rate (FHR) recordings from over 8,000 pregnancies – both pre-term and term – found that machine learning models trained on clinically validated FHR patterns could potentially identify fetuses at heightened risk of adverse outcomes. The study extracted seven FHR features from each recording and used six different machine learning classifiers to predict risk.
While these advancements in diagnostic tools and predictive modeling offer promise, it’s important to remember that prenatal testing is not foolproof. The detection rates for chromosomal abnormalities and fetal anomalies vary depending on the indication for testing and the specific technology used. Variants of uncertain significance require careful interpretation and may not always indicate a health problem.
The increasing rates of high-risk pregnancies and fetal anomalies underscore the importance of comprehensive prenatal care, including genetic counseling, advanced diagnostic testing, and access to specialized medical expertise. Continued research and technological advancements are crucial for improving outcomes for both mothers and babies.