EEG markers predictive of epilepsy risk in pediatric cerebral malaria - A feasibility study

Abstract

Objective: Cerebral malaria (CM) affects 500,000 million children annually, 10% whom develop epilepsy within two years. Acute identification of biomarkers for post-CM epilepsy would allow for follow-up of the highest risk populations in resource-limited regions. We investigated the utility of electroencephalogram (EEG) and clinical metrics obtained during acute CM infection for predicting epilepsy.

Methods: We analyzed 70 EEGs recorded within 24 h of admission for CM hospitalization obtained during the Blantyre Malaria Project Epilepsy Study (2005-2007), a prospective cohort study of pediatric CM survivors. While all studies underwent spectral analyses for comparisons of mean power band frequencies, a subset of EEGs from the 10 subjects who developed epilepsy and 10 age- and sex-matched controls underwent conventional visual analysis. Findings were tested for relationships to epilepsy outcomes.

Results: Ten of the 70 subjects developed epilepsy. There were no significant differences between groups that were analyzed via visual EEG review; however, spectral EEG analyses revealed a significantly higher gamma-delta power ratio in CM survivors who developed epilepsy (0.23 ± 0.10) than in those who did not (0.16 ± 0.06), p = 0.003. Excluding potential confounders, multivariable logistic-regression analyses found relative gamma power (p = 0.003) and maximum temperature during admission (p = 0.03) significant and independent predictors of post-CM epilepsy, with area under receiver operating characteristics (AUROC) curve of 0.854.

Conclusions: We found that clinical and EEG metrics acquired during acute CM presentation confer risk of post-CM epilepsy. Further studies are required to investigate the utility of gamma activity as a potential biomarker of epileptogenesis and study this process over time. Additionally, resource limitations currently prevent follow-up of all CM cases to surveil for epilepsy, and identification of acute biomarkers in this population would offer the opportunity to allocate resources more efficiently.

Keywords: Biomarkers; Cerebral malaria; EEG; Epilepsy; Pediatric.

Conflict of interest statement

Conflict of Interests Statement

A.R. is a founder and advisor for Neuromotion, serves on the medical advisory board or has consulted for Cavion, Epihunter, Gamify, Neural Dynamics, NeuroRex, Roche, Otsuka, and is listed as inventor on a patent related to integration of TMS and EEG. The remaining authors have no conflicts of interest to disclose and declare that the research was conducted in the absence of any relevant commercial or financial relationships. We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.

Copyright © 2020 Elsevier Inc. All rights reserved.

Figures

Figure 1.

Tmax (mean ± SD) was significantly higher in the cerebral malaria survivors who developed epilepsy (CM+Epi) (39.1°C ± 1.3) than in those who did not (CM–Epi) (38.2°C ± 1.0), p = 0.02.

Figure 2.

(A) Spectral EEG analysis identifies a significant difference in gamma (30–60 Hz) and delta (1–4 Hz) frequency power bands during the acute CM phase between CM+Epi and CM–Epi groups. (B) Independent-samples t-tests found that the CM+Epi group had significantly higher relative gamma power (0.61 ± 0.13) compared to CM–Epi (0.50 ± 0.08), p<0.001, and (C) significantly lower relative delta power (2.95 ± 0.75) than the CM–Epi group (3.38 ± 0.56), p = 0.038. Error bars represent standard error of the mean, * p<0.05, ***p<0.001.

Figure 3.

Logistic-regression models predicting post-CM epilepsy, sorted in ascending order of predictiveness. The numbers indicate the area under the receiver operating characteristic (AUROC) curve associated with each model.