A nomogram for preeclampsia risk prediction in the first trimester: a nested case-control study.

Area of Science:

• Obstetrics and Gynecology
• Maternal-Fetal Medicine
• Reproductive Health

Background:

• Preeclampsia (PE) is a severe multisystem disorder with significant adverse outcomes for neonates.
• Early identification of high-risk pregnancies is crucial for timely intervention and improved maternal-fetal outcomes.

Purpose of the Study:

• To develop and validate a predictive nomogram for identifying women at high risk of developing preeclampsia (PE) during the first trimester.
• To establish a clinical tool for early PE risk stratification.

Main Methods:

• A nested case-control study was conducted with 47 PE patients and 122 controls.
• Multivariate logistic regression analysis identified independent risk factors for PE.
• A nomogram was constructed and validated using calibration curves and decision curve analysis (DCA).

Main Results:

• Pre-pregnancy body mass index (BMI), mean arterial pressure (MAP), and uric acid (UA) were positively correlated with PE risk.
• Placental growth factor (PLGF) showed a negative correlation with PE.
• The nomogram demonstrated excellent discrimination (AUC = 0.97) and significant clinical utility.

Conclusions:

• The developed nomogram, incorporating pre-pregnancy BMI, PLGF, MAP, and UA, effectively predicts first-trimester preeclampsia risk.
• This tool can aid clinicians in identifying high-risk pregnancies for early management strategies.
• The nomogram offers a promising approach for improving preeclampsia screening and prevention.