Prediction of adverse neonatal outcome at admission for early-onset preeclampsia with severe features.

Pregnancy hypertension(2023)

引用 0|浏览1
暂无评分
摘要
BACKGROUND:Preeclampsia remains the leading cause of maternal morbidity and mortality. Consequently, research has focused on validating tools to predict maternal outcomes regarding clinical and biochemical features from the maternal compartment. However, preeclampsia also leads to neonatal complications due to placental insufficiency and prematurity, being the early-onset type associated with the poorest outcome. Hence, it is imperative to study whether these existing tools can predict adverse neonatal outcome. OBJECTIVE:To assess the predictive value for adverse neonatal outcome of Doppler ultrasound, angiogenic factors and multi-parametric risk-score models in women with early-onset severe preeclampsia. STUDY DESIGN:This is a prospective cohort study of consecutive singleton pregnancies complicated by early-onset (developed before 34 week's gestation) severe preeclampsia. RESULTS:63 women with early-onset severe preeclampsia, 18 (28.6%) presented an adverse neonatal outcome. Placental growth factor (PlGF) showed the best discrimination between neonatal outcomes among angiogenic factors. PREP-L score is a multi-parametric risk-score for the prediction of complications in early-onset preeclampsia which includes maternal characteristics and clinical and analytical data obtained at admission. Good predictive values for the prediction of neonatal complications were found with the combination of PREP-L score with advanced Doppler (AUC ROC 0.9 95% CI 0.82-0.98]) and with PlGF levels (AUC ROC 0.91 [95% CI 0.84-0.98]). CONCLUSIONS:The combination of maternal risk scoring (PREP-L score) with angiogenic factors or fetal Doppler ultrasound at the time of diagnosis of early-onset preeclampsia with severe features performs well in predicting adverse neonatal outcome.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要