Department of Pediatrics, MedStar Georgetown University Hospital, Washington, District of Columbia, U.S.A.
Department of Neurology, The George Washington University School of Medicine, Children's National Hospital, Washington, District of Columbia, U.S.A.
J Clin Neurophysiol. 2023 Feb 1;40(2):136-143. doi: 10.1097/WNP.0000000000000865. Epub 2021 Jun 17.
Pediatric cerebral malaria has high rates of mortality and neurologic morbidity. Although several biomarkers, including EEG, are associated with survival or morbidity, many are resource intensive or require skilled interpretation for clinical use. Automation of quantitative interpretation of EEG may be preferable in resource-limited settings, where trained interpreters are rare. As currently used quantitative EEG factors do not adequately describe the spectrum of variability seen in studies from children with cerebral malaria, the authors developed and validated a new quantitative EEG variable, theta-alpha variability (TAV).
The authors developed TAV, a new quantitative variable, as a composite of multiple automated EEG outputs. EEG records from 194 children (6 months to 14 years old) with cerebral malaria were analyzed. Independent EEG interpreters performed standard quantitative and qualitative analyses, with the addition of the newly created variable. The associations of TAV with other quantitative EEG factors, a qualitative assessment of variability, and outcomes were assessed.
Theta-alpha variability was not highly correlated with alpha, theta, or delta power and was not associated with qualitative measures of variability. Children whose EEGs had higher values of TAV had a lower risk of death (odds ratio = 0.934, 95% confidence interval = 0.902-0.966) or neurologic sequelae (odds ratio = 0.960, 95% confidence interval = 0.932-0.990) compared with those with lower values. Receiver operating characteristic analysis in predicting death at a TAV threshold of 0.244 yielded a sensitivity of 74% and specificity of 70% for an area under the receiver operating characteristic curve of 0.755.
Theta-alpha variability is independently associated with outcome in pediatric cerebral malaria and can predict death with high sensitivity and specificity. Automated determination of this newly created EEG factor holds promise as a potential method to increase the clinical utility of EEG in resource-limited settings by allowing interventions to be targeted to those at higher risk of death or disability.
小儿脑型疟疾的死亡率和神经发病率都很高。尽管包括脑电图在内的几种生物标志物与存活率或发病率有关,但许多都需要大量资源或需要熟练的解释才能在临床上使用。在资源有限的环境中,自动化的脑电图定量解读可能更可取,因为那里很少有经过培训的解释者。由于目前使用的定量脑电图因素不能充分描述来自脑型疟疾儿童的研究中观察到的变异性谱,因此作者开发并验证了一种新的定量脑电图变量,即θ-α变异性(TAV)。
作者开发了 TAV,这是一种新的定量变量,由多个自动脑电图输出组合而成。对 194 名患有脑型疟疾的儿童(6 个月至 14 岁)的脑电图记录进行了分析。独立的脑电图解释者进行了标准的定量和定性分析,并增加了新创建的变量。评估了 TAV 与其他定量脑电图因素、变异性的定性评估以及结局之间的关系。
θ-α变异性与α、θ或δ功率的相关性不高,与变异性的定性测量也没有关联。脑电图 TAV 值较高的儿童死亡(比值比=0.934,95%置信区间=0.902-0.966)或出现神经后遗症(比值比=0.960,95%置信区间=0.932-0.990)的风险较低。在 TAV 阈值为 0.244 预测死亡的受试者工作特征分析中,受试者工作特征曲线下面积为 0.755,其灵敏度为 74%,特异性为 70%。
θ-α变异性与小儿脑型疟疾的结局独立相关,可高度敏感和特异性地预测死亡。该新创建的脑电图因素的自动测定有望成为一种潜在的方法,通过允许针对那些死亡或残疾风险较高的患者进行干预,增加资源有限环境中脑电图的临床实用性。