Unveiling preeclampsia: The risk factors, clinical profiles, and outcomes in early vs. late onset: A prospective observational study

Background : Preeclampsia is a heterogeneous disorder involving multiple system during pregnancy. It poses a significant health burden globally contributing to huge chunk of adverse fetomaternal outcomes. The aim of this research is to evaluate the fetomaternal outcomes linked to early onset preeclampsia (EOPE) versus late onset preeclampsia (LOPE), highlighting the distinct risks and clinical features associated with each. Materials and Methods: In this prospective hospital based observational study, 134 cases of preeclampsia were included out with 40 categorized as EOPE and 94 as LOPE, all tracked until delivery. The clinical behaviors and pregnancy outcomes of the two groups were analyzed. Odds ratios (OR) and 95% confidence intervals (CI) were computed, and p-values were assessed to determine statistical significance. Results: The findings revealed that the risk factor profiles for EOPE and LOPE were largely comparable; however, the early-onset group exhibited a significantly higher incidence of HELLP syndrome, organ damage, operative delivery, and extended hospital stays. Adverse perinatal outcomes, including intrauterine fetal demise (IUFD) (22.5% vs. 2.1%, OR=13.355, p=0.001), intrauterine growth restriction (IUGR) (20.0% vs. 3.2%, OR=7.583, p=0.004), respiratory distress (37.5% vs. 11.7%, OR=4.527, p=0.001), jaundice (15.0% vs. 4.3%, OR=3.971, p=0.041), and low birth weight (70.0% vs. 19.1%, OR=9.852, p<0.001), were also significantly more prevalent in the EOPE cohort. Conclusion: In conclusion, early onset preeclampsia is linked to a more severe clinical course than late onset preeclampsia, resulting in a greater likelihood of adverse fetomaternal outcomes. Factors such as the gestational age at onset, proteinuria, low platelet counts, elevated uric acid and serum creatinine levels, along with fetal growth restriction and Doppler abnormalities, play a crucial role in determining the severity of the condition and its prognosis.