复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的见解？
Can a composite heart rate variability biomarker shed new insights about autism spectrum disorder in school-aged children?
摘要：
高频心率变异性（HRV）已经确定了自闭症谱系障碍（ASD）的副交感神经系统改变。在一组有和没有ASD的学龄儿童中，我们测试了一组替代的线性和非线性HRV测量，包括相位整流信号平均，应用于一段静息ECG，与ASD与其他精神疾病的关联。使用机器学习，我们识别出从时间、频率和几何信号分析域获得的HRV指标，这些指标（1）识别出ASD儿童相对于接受者工作曲线面积为0.89的同龄人，（2）将这些儿童与有行为问题或抑郁症的儿童区分开来。尽管队列较小且缺乏前瞻性外部验证，但这些初步结果值得进行更大规模的前瞻性验证研究。
英文摘要：
High-frequency heart rate variability (HRV) has identified parasympathetic nervous system alterations in autism spectrum disorder (ASD). In a cohort of school-aged children with and without ASD, we test a set of alternative linear and nonlinear HRV measures, including phase rectified signal averaging, applied to a segment of resting ECG, for associations with ASD vs. other psychiatric conditions. Using machine learning, we identify HRV measures derived from time, frequency, and geometric signal-analytical domains that (1) identify children with ASD relative to peers with receiver operating curve area of .89, and (2) differentiate such children from those with conduct problems or depression. Despite the small cohort and lack of prospective external validation, these preliminary results warrant larger prospective validation studies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
