脑电图标志物预测小儿疟疾性脑病的癫痫风险——一项可行性研究。
EEG markers predictive of epilepsy risk in pediatric cerebral malaria - A feasibility study.
机构信息
Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; F.M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
出版信息
Epilepsy Behav. 2020 Dec;113:107536. doi: 10.1016/j.yebeh.2020.107536. Epub 2020 Nov 21.
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.
目的
每年有 5000 万至 1 亿儿童罹患脑疟疾（CM），其中 10%的儿童会在两年内发展为癫痫。急性识别 CM 后癫痫的生物标志物将允许对资源有限地区的高风险人群进行随访。我们研究了在急性 CM 感染期间获得的脑电图（EEG）和临床指标在预测癫痫方面的效用。
方法
我们分析了在 Blantyre Malaria Project Epilepsy Study（2005-2007 年）中获得的 70 例 CM 住院患者入院后 24 小时内记录的脑电图，这是一项儿科 CM 幸存者的前瞻性队列研究。虽然所有研究都进行了频谱分析以比较平均功率频带频率，但对发生癫痫的 10 名患者和 10 名年龄和性别匹配的对照组的一部分脑电图进行了常规视觉分析。研究结果测试了与癫痫结果的关系。
结果
70 名患者中有 10 名发生了癫痫。通过视觉脑电图检查进行分析的两组之间没有显著差异；然而，频谱脑电图分析显示，发生癫痫的 CM 幸存者的伽马-德尔塔功率比（0.23±0.10）明显高于未发生癫痫的患者（0.16±0.06），p=0.003。在排除潜在混杂因素后，多变量逻辑回归分析发现相对伽马功率（p=0.003）和入院期间的最高温度（p=0.03）是 CM 后癫痫的显著和独立预测因素，受试者工作特征曲线（AUROC）下面积为 0.854。
结论
我们发现，急性 CM 发作期间获得的临床和脑电图指标与 CM 后癫痫的风险相关。需要进一步研究来研究伽马活动作为癫痫发生潜在生物标志物的效用，并随着时间的推移研究这个过程。此外，资源限制目前阻止了对所有 CM 病例进行随访以监测癫痫，而在该人群中识别急性生物标志物将提供更有效地分配资源的机会。
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