Year: 2025
Type: article
Study design: Observational Study
Abstract: Background Hypertensive disorders during pregnancy are a major global cause of maternal and neonatal mortality. Delivery remains the only effective management for eclampsia and severe preeclampsia (PE). Currently, the decision to deliver the baby prematurely is based on clinical manifestations and neurological examinations, but there is no objective tool to monitor cerebral involvement. Eclampsia presents with abroad spectrum of signs ranging from proteinuria and severe hypertension (HTN) to moderate or non-existent HTN without proteinuria with seizure or end orang damage. This study aims to use Digital electroencephalogram (DEEG) to monitor and track the progression of PE and eclampsia and correlate DEEG findings with clinical data. This case- control study was conducted at Ain Shams University Hospitals from August 2019 to August 2022. It included 35 patients consisting of (24 with PE and 11 with eclampsia), and 35 control subjects. All participants underwent a comprehensive medical history, clinical examination, and a 25-min DEEG. Results A 25-min DEEG was performed for both cases and controls.Among the cases, 14 (40%) showed abnormal DEEG findings such as focal activity and slow waves (9 eclampsia cases and 5 PE cases). No abnormalities were observed in the control group. In patients with PE and abnormal DEEG findings, systolic blood pressure (SBP) exceeded 160 mmHg and diastolic blood pressure(DBP) exceeded 110 mmHg, indicating that those with severe HTN are at higher risk of brain injury. Conclusion Abnormal DEEG patterns are more common in pregnant women with PE and eclampsia, indicating subclinical cerebral dysfunction that may predispose to seizures. These findings were more prominent in cases of severe PE, supporting the role of DEEG as a potential tool for early central nervous system (CNS) involvement detection.
Authors: Mahmoud Ahmed, Mahmoud Hemeda, Naglaa M.Elkhayat, Ahmed Gaber, Eman Mones
Institution: Ain Shams University
Language: English
Subfield: Obstetrics and Gynecology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4416095651