Journal Article

Identification of Essential, Equivocal and Complex Autism by the Autism Dysmorphology Measure: An Observational Study

Sharma, Suvasini, Neelam, Kapoor, Seema, Mukherjee, Sharmila B.

2021

Overview

The Autism Dysmorphology Measure is designed for non-expert clinicians. It uses an algorithm to assess 12 body regions and categorizes Autism on the number of dysmorphic regions identified; Essential (≤ 3), Equivocal (4–5) or Complex (≥ 6). We evaluated 200 Indian children with Autism (mean age 3.7 years) in a hospital-based cross-sectional study and compared inter-group profiles. We found 31% Essential, 49% Equivocal and 20% Complex Autism. On comparing results with existing literature, it appeared that genetic ancestry and age significantly influenced dysmorphism and hence categorization. No significant differences were observed between complex and essential autism in epilepsy, severity of autism or development, as reported earlier. These shortcomings make the present tool unsuitable for use in young Indian children with Autism.

• Publisher: Springer US,Springer,Springer Nature B.V
• Subject: Age Differences / Algorithms / Anatomy / Autism / Autism Spectrum Disorders / Autistic children / Behavior Problems / Behavioral Science and Psychology / Brain / Child and School Psychology / Children / Classification / Clinical Diagnosis / Complexity / Congenital Impairments / Cross-sectional studies / Definitions / Diagnosis / Dysmorphology / Epilepsy / Evaluation / Foreign Countries / Genetic Disorders / Genetics / Hospitals / Human Body / Identification and classification / Interpersonal Relationship / Measurement Techniques / Meta Analysis / Neurosciences / Observational studies / Original Paper / Pediatrics / Pervasive Developmental Disorders / Pregnancy / Psychology / Public Health / Regions / Schizophrenia / Severity (of Disability) / Validity / Young Children