Brief Report: Can a Composite Heart Rate Variability Biomarker Shed New Insights About Autism Spectrum Disorder in School-Aged Children?
Brief Report: Can a Composite Heart Rate Variability Biomarker Shed New Insights About Autism Spectrum Disorder in School-Aged Children?
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DOI：
10.1007/s10803-020-04467-7
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发表时间：
2020-05-24
影响因子：
3.9
通讯作者：
Beauchaine, Theodore P.
中科院分区：
文献类型：
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作者：
Frasch, Martin G.;Shen, Chao;Beauchaine, Theodore P.
一些研究表明，自闭症谱系障碍（ASD）患者的心率变异性（HRV）发生了改变，但这一发现既不普遍，也不针对ASD。我们将一组线性和非线性HRV测量——包括相位校正信号平均——应用于从ASD学龄儿童、年龄匹配的典型发育对照和其他以HRV改变（行为障碍、抑郁症）为特征的精神疾病儿童收集的静息心电图数据片段。我们使用机器学习来识别特定于ASD的时间、频率和几何信号分析域（接收者工作曲线面积= 0.89）。这是第一个将ASD儿童与其他以HRV改变为特征的疾病区分开来的研究。尽管是一个小的队列和缺乏外部验证，结果证明更大的前瞻性研究。
Several studies show altered heart rate variability (HRV) in autism spectrum disorder (ASD), but findings are neither universal nor specific to ASD. We apply a set of linear and nonlinear HRV measures-including phase rectified signal averaging-to segments of resting ECG data collected from school-age children with ASD, age-matched typically developing controls, and children with other psychiatric conditions characterized by altered HRV (conduct disorder, depression). We use machine learning to identify time, frequency, and geometric signal-analytical domains that are specific to ASD (receiver operating curve area = 0.89). This is the first study to differentiate children with ASD from other disorders characterized by altered HRV. Despite a small cohort and lack of external validation, results warrant larger prospective studies.