Identifying biomarkers for epilepsy after cerebral malaria in Zambian children: rationale and design of a prospective observational study. Issue 7 (18th July 2022)

• Record Type: Journal Article
• Authors: Patel, Archana A; Birbeck, Gretchen L; Mazumdar, Maitreyi; Mwanza, Suzanna; Nyirongo, Rosemary; Berejena, Dixon; Kasolo, Joseph; Mwale, Tina; Nambeye, Violet; Nkole, Kafula Lisa; Kawatu, Nfwama; Zhang, Bo; Rotenberg, Alexander
• Is Part Of: BMJ open. Volume 12:Issue 7(2022)
• Publication Date: 2022-07-18
• Subjects: Epilepsy -- Paediatric neurology -- Tropical medicine -- NEUROPHYSIOLOGY; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2022-062948
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Introduction: Malaria affecting the central nervous system (CM) is a major contributor to paediatric epilepsy in resource-poor settings, with 10%–16% of survivors developing epilepsy within 2 years of infection. Despite high risk for post-malaria epilepsy (PME), biomarkers indicating which CM survivors will develop epilepsy are absent. Such biomarkers are essential to identify those at highest risk who might benefit most from close surveillance and/or preventive treatments. Electroencephalography (EEG) contains signals (specifically gamma frequency activity), which are correlated with higher risk of PME and provide a biomarker for the development of epilepsy. We propose to study the sensitivity of quantitative and qualitative EEG metrics in predicting PME, and the potential increased sensitivity of this measure with additional clinical metrics. Our goal is to develop a predictive PME index composed of EEG and clinical history metrics that are highly feasible to obtain in low-resourced regions. Methods and analyses: This prospective observational study being conducted in Eastern Zambia will recruit 250 children aged 6 months to 11 years presenting with acute CM and follow them for two years. Children with pre-existing epilepsy diagnoses will be excluded. Outcome measures will include qualitative and quantitative analysis of routine EEG recordings, as well as clinical metrics in the acute and subacute period, including histidine-rich protein 2 levels of parasite burden, depth and length of coma, presence and severity of acute seizures, presence of hypoglycaemia, maximum temperature and 1-month post-CM neurodevelopmental assessment scores. We will test the performance of these EEG and clinical metrics in predicting development of epilepsy through multivariate logistic regression analyses. Ethics and dissemination: This study has been approved by the Boston Children's Hospital Institutional Review Board, University of Zambia Biomedical Research Ethics Committee, and National Health Research Authority of Zambia. Results will be disseminated locally in Zambia followed by publication in international, open access, peer-reviewed journals when feasible.