Hypertension in pregnancy: effects on maternal and fetal health and long-term outcomes - Sanjay Gupte; Manjusha G. Deulkar; Divya R. Chatla; Preeti S. Arora; Sarjan D. Shah (International Journal of Reproduction, Contraception, Obstetrics and Gynecology, 2026)
Hypertensive disorders of pregnancy (HDP) are heterogeneous maternal-placental syndromes and continue to be a major cause of maternal and perinatal morbidity and mortality worldwide. Their clinical spectrum ranges from gestational and chronic hypertension to preeclampsia, eclampsia and HELLP syndrome with markedly different biological mechanisms and outcomes. This narrative review critically discusses the current knowledge on the pathophysiology, classification, diagnosis, complications, and long-term outcomes of HDP. Current evidence supports a multifactorial model whereby abnormal placentation and impaired spiral artery remodelling interact with maternal cardiovascular, metabolic, immune, genetic and environmental susceptibility to produce endothelial dysfunction and clinical disease. Imbalances in angiogenesis, in particular sFlt-1 and PlGF changes, have improved our understanding of disease biology and have provided clinically useful tools to assess risk in suspected preeclampsia. However, biomarker performance is dependent on gestational age, disease phenotype, population and clinical setting, which limits their universal applicability. Severe HDP can lead to eclampsia, HELLP syndrome, renal and hepatic dysfunction, stroke, placental insufficiency, foetal growth restriction, stillbirth, and medically indicated preterm birth. Emerging evidence links HDP with subsequent maternal cardiovascular and renal disease and potential long-term cardiometabolic effects in exposed offspring. Importantly, the evidence available indicates that no single biomarker or molecular pathway is sufficient to represent the heterogeneity of HDP. Therefore, future strategies should focus on integrating clinical features with angiogenic, placental, cell-free nucleic acid, metabolomic and proteomic markers, possibly supported by artificial intelligence.