One of the most serious complications of pregnancy is preeclampsia, a condition that affects pregnant women worldwide. This condition can be dangerous for both mother and baby, making early detection and monitoring essential. A recent study, published in PLOS Medicine, examined the effectiveness of predictive models in assessing the risks of adverse maternal outcomes for women with preeclampsia.
What Is Preeclampsia?
Preeclampsia is a pregnancy-related disorder characterized by high blood pressure and signs of damage to organs such as the liver and kidneys. It usually occurs after the 20th week of pregnancy and can lead to severe complications, including seizures (eclampsia), stroke, and organ failure. Preeclampsia affects 5-7% of pregnancies worldwide and is a leading cause of maternal and fetal morbidity and mortality.
Symptoms of preeclampsia include:
- High blood pressure (above 140/90 mmHg)
- Swelling, especially in the hands and face
- Severe headaches
- Vision problems (blurry vision, seeing spots)
- Shortness of breath
- Protein in urine (detected through lab tests)
If left untreated, preeclampsia can progress to eclampsia, which includes life-threatening seizures.
According to global data, preeclampsia complicates around 2-8% of pregnancies. It is more common in first-time pregnancies, women over 35, those carrying multiples, and individuals with pre-existing conditions like hypertension, diabetes, or kidney disease. It also disproportionately affects Black women and those with limited access to healthcare.
How Does Preeclampsia Affect Pregnancy?
Preeclampsia can have serious consequences for both the mother and the baby. It can lead to:
- Preterm birth: Many women with severe preeclampsia need to deliver early to protect their health and their baby’s.
- Restricted fetal growth: High blood pressure reduces blood flow to the placenta, limiting the baby’s oxygen and nutrient supply.
- Placental abruption: The placenta may detach from the uterus prematurely, causing heavy bleeding and potential harm to the baby.
- Organ damage: Preeclampsia can affect the mother’s kidneys, liver, brain, and cardiovascular system, increasing the risk of long-term health issues.
Researchers have developed models to predict which women with preeclampsia are at the highest risk of severe complications. This study examined two tools: PIERS-ML (a machine-learning-based model) and fullPIERS (a logistic regression-based model). These models assess various health factors and calculate the likelihood of adverse maternal outcomes, including death, organ failure (heart, lungs, kidneys, liver, etc.), and placental complications.
The study analyzed data from 8,843 women diagnosed with preeclampsia across multiple countries, including the Americas, sub-Saharan Africa, South Asia, Europe, and Oceania. The participants had a median age of 31 years and were diagnosed at a median gestational age of 35.79 weeks. Researchers used this data to evaluate how well the PIERS-ML and fullPIERS models could predict severe maternal complications over a two-week period following hospital admission.
Findings showed that both models were most effective at predicting risks within the first 48 hours after a woman was admitted to the hospital. The PIERS-ML model, which uses machine learning, performed better on the first day, but its accuracy declined over time. The study revealed that after 48 hours, the ability of both models to distinguish between high-risk and low-risk patients significantly deteriorated. Over time, as women’s conditions changed, the predictive power of these models weakened, highlighting the need for continuous monitoring rather than sole reliance on these tools.
The study also categorized women into “very high risk,” “high risk,” “moderate risk,” “low risk,” and “very low risk” groups based on likelihood ratios. Women in the very high-risk category were far more likely to experience severe complications within 48 hours. However, the study found that even those in lower-risk categories required ongoing assessments since conditions could change unexpectedly. Dynamic shifts in risk levels were observed, emphasizing the need for doctors to adjust treatment plans based on real-time patient data rather than fixed model predictions.
Furthermore, the study examined decision curve analyses to determine whether using these models for treatment decisions provided clinical benefits. Results showed that while PIERS-ML had an advantage on the first day, its benefit diminished over time, indicating that serial predictions should be approached with caution. Clinicians using these models for ongoing assessments should interpret results with increasing uncertainty as pregnancy progresses.
What This Means for Expectant Mothers
Early detection and hospitalization matter. If you have preeclampsia, seeking medical care early can significantly improve outcomes. Doctors use risk models cautiously, recognizing their limitations beyond the initial assessment. Ongoing monitoring is crucial, as preeclampsia can worsen unexpectedly. Even if an initial assessment shows low risk, regular check-ups, blood pressure monitoring, and fetal assessments remain important. Expectant mothers should trust their symptoms—if they experience worsening headaches, vision problems, or swelling, they should report them to their healthcare provider immediately.
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