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简短报告:综合心率变异性生物标志物能否为学龄儿童自闭症谱系障碍提供新见解?

Brief Report: Can a Composite Heart Rate Variability Biomarker Shed New Insights About Autism Spectrum Disorder in School-Aged Children?

作者信息

Frasch Martin G, Shen Chao, Wu Hau-Tieng, Mueller Alexander, Neuhaus Emily, Bernier Raphael A, Kamara Dana, Beauchaine Theodore P

机构信息

Department of Obstetrics and Gynecology, University of Washington, Seattle, WA, USA.

Center on Human Development and Disability, University of Washington, Seattle, WA, USA.

出版信息

J Autism Dev Disord. 2021 Jan;51(1):346-356. doi: 10.1007/s10803-020-04467-7.

Abstract

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.

摘要

多项研究表明,自闭症谱系障碍(ASD)患者的心率变异性(HRV)存在改变,但这些发现既不具有普遍性,也并非ASD所特有。我们将一组线性和非线性HRV测量方法——包括相位整流信号平均法——应用于从患有ASD的学龄儿童、年龄匹配的发育正常对照儿童以及患有其他以HRV改变为特征的精神疾病(品行障碍、抑郁症)的儿童采集的静息心电图数据片段。我们使用机器学习来识别ASD特有的时间、频率和几何信号分析域(受试者工作特征曲线面积 = 0.89)。这是第一项将患有ASD的儿童与其他以HRV改变为特征的疾病区分开来的研究。尽管样本量小且缺乏外部验证,但研究结果值得开展更大规模的前瞻性研究。

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