Literature DB >> 32892958

Early Detection and Diagnosis of Autism Spectrum Disorder: Why Is It So Difficult?

Patrick McCarty1, Richard E Frye2.   

Abstract

Autism spectrum disorder (ASD) affects approximately 2% of children in the United States (US). Therapeutic interventions are most effective if applied early, yet diagnosis often remains delayed, partly because the diagnosis is based on identifying abnormal behaviors that may not emerge until the disorder is well established. Universal screening has been recommended by the America Academy of Pediatrics at 18 and 24 months yet studies show low compliance by pediatricians and the US Preventive Services Task Force does not support universal screening. To better understand the limitations of universal screening this article looks at the performance of screening tests given the prevalence of ASD. Specifically, although the sensitivity and specificity of the Modified Checklist for Autism in Toddlers, Revised with Follow-up, the de facto screening tool, exceeds 90%, the relatively low prevalence of ASD in the general population (∼2%) results in a positive predictive value of about 33%, resulting in only 1 of 3 children identified by the Modified Checklist for Autism in Toddlers, Revised with Follow-up actually having ASD. To mitigate this issue, the America Academy of Pediatrics has recently recommended the use of a Level 2 screener after failing a Level 1 screener, before referring children on for a full comprehensive evaluation for ASD. In this way, a series of screening tools are used to enrich the population of children referred for further evaluation so fewer without an ASD diagnosis are evaluated. We have developed a program to train pediatricians to utilize these instruments as well as learn to diagnose ASD so children can effectively be referred for appropriate services at the front lines. Given the current burden on the medical system with the diagnosis and evaluation of children with ASD, it is important to create efficient systems for screening children which can best identify those most likely to have ASD. Developing methods to identify those children most at risk for developing ASD, either through consideration of medical or family history or through the use of biomarkers, may be helpful in identifying the children that require increased surveillance and those that do not need screening.
Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.

Entities:  

Year:  2020        PMID: 32892958     DOI: 10.1016/j.spen.2020.100831

Source DB:  PubMed          Journal:  Semin Pediatr Neurol        ISSN: 1071-9091            Impact factor:   1.636


  11 in total

1.  'If I don't Do It, I'm Out of Rhythm and I Can't Focus As Well': Positive and Negative Adult Interpretations of Therapies Aimed at 'Fixing' Their Restricted and Repetitive Behaviours in Childhood.

Authors:  Lynne McCormack; Sze Wing Wong; Linda E Campbell
Journal:  J Autism Dev Disord       Date:  2022-07-04

2.  Multivariate Analysis of Metabolomic and Nutritional Profiles among Children with Autism Spectrum Disorder.

Authors:  Fatir Qureshi; James B Adams; Tapan Audhya; Juergen Hahn
Journal:  J Pers Med       Date:  2022-06-01

Review 3.  AGEomics Biomarkers and Machine Learning-Realizing the Potential of Protein Glycation in Clinical Diagnostics.

Authors:  Naila Rabbani
Journal:  Int J Mol Sci       Date:  2022-04-21       Impact factor: 6.208

4.  Autism Spectrum Disorder Diagnostic Criteria Changes and Impacts on the Diagnostic Scales-Utility of the 2nd and 3rd Versions of the Gilliam Autism Rating Scale (GARS).

Authors:  Sayyed Ali Samadi; Cemal A Biçak; Hana Noori; Barez Abdalla; Amir Abdullah; Lizan Ahmed
Journal:  Brain Sci       Date:  2022-04-23

Review 5.  Information and Communication Technologies to Support Early Screening of Autism Spectrum Disorder: A Systematic Review.

Authors:  Lorenzo Desideri; Patricia Pérez-Fuster; Gerardo Herrera
Journal:  Children (Basel)       Date:  2021-02-01

6.  A New Perspective on Assessing Cognition in Children through Estimating Shared Intentionality.

Authors:  Igor Val Danilov; Sandra Mihailova
Journal:  J Intell       Date:  2022-03-29

7.  Modern Biomarkers for Autism Spectrum Disorder: Future Directions.

Authors:  Amanda R Jensen; Alison L Lane; Brianna A Werner; Sallie E McLees; Tessa S Fletcher; Richard E Frye
Journal:  Mol Diagn Ther       Date:  2022-06-27       Impact factor: 4.476

8.  Blood RNA Sequencing Indicates Upregulated BATF2 and LY6E and Downregulated ISG15 and MT2A Expression in Children with Autism Spectrum Disorder.

Authors:  Irena Voinsky; Yazeed Zoabi; Noam Shomron; Moria Harel; Hanoch Cassuto; Joseph Tam; Shannon Rose; Adrienne C Scheck; Mohammad A Karim; Richard E Frye; Adi Aran; David Gurwitz
Journal:  Int J Mol Sci       Date:  2022-08-30       Impact factor: 6.208

9.  Recent trends in autism spectrum disorder research using text mining of PubMed: importance of early detection.

Authors:  Seung Soo Kim
Journal:  Clin Exp Pediatr       Date:  2020-11-09

10.  Comparison of the Metabolic Profiles in the Plasma and Urine Samples Between Autistic and Typically Developing Boys: A Preliminary Study.

Authors:  Xin-Jie Xu; Xiao-E Cai; Fan-Chao Meng; Tian-Jia Song; Xiao-Xi Wang; Yi-Zhen Wei; Fu-Jun Zhai; Bo Long; Jun Wang; Xin You; Rong Zhang
Journal:  Front Psychiatry       Date:  2021-06-04       Impact factor: 4.157

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