Neurology, Division of Epilepsy & Clinical Neurophysiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
Department of Paediatrics and Child Health, University of Zambia School of Medicine, Lusaka, Zambia.
BMJ Open. 2022 Jul 18;12(7):e062948. doi: 10.1136/bmjopen-2022-062948.
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.
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.
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.
疟疾影响中枢神经系统（CM）是资源匮乏地区导致儿科癫痫的主要原因，10%-16%的感染者在感染后 2 年内会发展为癫痫。尽管存在很高的疟疾后癫痫（PME）风险，但缺乏表明哪些 CM 幸存者会发展为癫痫的生物标志物。这些生物标志物对于确定风险最高的人群至关重要，这些人群可能最受益于密切监测和/或预防治疗。脑电图（EEG）包含与 PME 风险较高相关的信号（特别是伽马频率活动），并为癫痫的发生提供了生物标志物。我们建议研究定量和定性脑电图指标预测 PME 的敏感性，以及该指标与额外临床指标结合的潜在更高敏感性。我们的目标是开发一种由 EEG 和临床病史指标组成的预测 PME 指数，该指数在资源匮乏地区非常易于获取。
这项前瞻性观察性研究正在赞比亚东部进行，将招募 250 名 6 个月至 11 岁患有急性 CM 的儿童，并对他们进行为期两年的随访。患有预先存在的癫痫诊断的儿童将被排除在外。主要终点是包括定性和定量分析常规脑电图记录，以及急性和亚急性期间的临床指标，包括寄生虫负荷的组氨酸丰富蛋白 2 水平、昏迷的深度和长度、急性发作的存在和严重程度、低血糖的存在、最高温度和 1 个月后 CM 的神经发育评估评分。我们将通过多元逻辑回归分析测试这些 EEG 和临床指标在预测癫痫发展中的表现。
这项研究已获得波士顿儿童医院机构审查委员会、赞比亚大学生物医学伦理委员会以及赞比亚国家卫生研究管理局的批准。结果将在赞比亚当地进行传播，然后在可行的情况下在国际、开放获取、同行评审期刊上发表。
