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

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-ag...

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Publicado en:Journal of Autism & Developmental Disorders Vol. 51; no. 1; pp. 346 - 357
Autores principales: Frasch, Martin G., Shen, Chao, Wu, Hau-Tieng, Mueller, Alexander, Neuhaus, Emily, Bernier, Raphael A., Kamara, Dana, Beauchaine, Theodore P.
Formato: research tables/charts tracings Journal Article
Publicado: Springer Nature 2021
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Brief Report: Can a Composite Heart Rate Variability Biomarker Shed New Insights About Autism Spectrum Disorder in School-Aged Children?
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          Frasch, Martin G.
          Shen, Chao
          Wu, Hau-Tieng
          Mueller, Alexander
          Neuhaus, Emily
          Bernier, Raphael A.
          Kamara, Dana
          Beauchaine, Theodore P.
        affil: Department of Obstetrics and Gynecology, University of Washington, Seattle, WA, USA
      sug:
        subj:
          Autism Spectrum Disorder Physiopathology
          Heart Rate Evaluation
          Heart Rate Variability
          Biological Markers
          Human
          Secondary Analysis
          Electrocardiography
          Child
          Female
          Male
          Comparative Studies
          Child Behavior Disorders
          Depression
          ROC Curve
          Autism Spectrum Disorder Diagnosis
          Descriptive Statistics
          Child: 6-12 years
          Female
          Male
      ab: 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.
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