The investigators' objective is to test an innovative method of autism diagnosis that integrates clinical evaluation and assessment of biobehavioral markers in a large high-risk community-referral sample of children in the primary care setting.
Determine whether eye-tracking biomarkers can reliably differentiate young children with and without autism in a community referred sample. The study will use a non-invasive remote eye-tracking system (Eyelink Portable Duo) to acquire a short series (less than 15 mins) of eye-tracking measures (e.g., looking time, pupil diameter, oculomotor dynamics), which may be associated with autism in young children. Differences in metrics between children with and without autism will be compared to validate potential eye-tracking biomarkers. Determine whether a combination of clinical (i.e., EE Hub PCP measures) and eye-tracking biomarkers can be used to accurately predict autism diagnostic outcome in a sample of young children evaluated for autism in the primary care setting.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
154
Eye-tracking data will be collected using a commercially-available remote eye-tracking system (Eyelink Portable Duo). Eye movements and pupil diameter will be collected while participants view a series of developmentally appropriate pictures and movies. The eye-tracker consists of two cameras; one that monitors eye movements and a second scene camera that monitors head movements, which permits eye tracking to take place without any equipment touching the child. Children will be asked to sit in highchair or on a caregiver's lap and will face a computer monitor. After a sticker is applied to the child's forehead and brief eye-movement calibration completed, next visual stimuli (i.e., pictures and videos) will be presented on a laptop computer monitor that is placed at approximately 60-80cm from the child. The eye tracking portion of the visit will last approximately 15 minutes or until the child is no longer able to attend to pictures/videos.
A Classification and Regression Tree (CART) Analysis, based on recursive partitioning, was used to determine which combination of variables (EE Hub PCP diagnosis, diagnostic certainty, composite biomarker, and biomarker frequency \[sum of all individual biomarkers (0-6) that exceeded the 95% specificity threshold for each child\]) best predicted reference standard autism diagnosis.
Community Health Network
Anderson, Indiana, United States
Margaret Mary Health Pediatrics
Batesville, Indiana, United States
Riley Hospital for Children
Indianapolis, Indiana, United States
Meridian Health Pediatrics
Muncie, Indiana, United States
Agreement Between Composite Eye-tracking Biomarker and Expert Autism-specialist
Sensitivity and specificity of a composite eye-tracking (i.e., index) test, which was a consolidated measure based on significant eye-tracking indices, compared to reference standard expert clinical autism diagnosis.
Time frame: Day 1
Agreement Between Integrated PCP, Eye-tracking Biomarker Score and Expert Autism-specialist
Classification and Regression Tree (CART) analysis, based on recursive partitioning, is used to determine which combination of variables (EE Hub PCP diagnosis, diagnostic certainty, composite biomarker, and biomarker frequency \[sum of all individual biomarkers (0-6) that exceeded the 95% specificity threshold for each child\]) best predicted reference standard autism diagnosis.
Time frame: Day 1
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Deaconess Riley Children's Specialty Center
Newburgh, Indiana, United States
Primary Care Partners of South Bend
South Bend, Indiana, United States
Lutheran Health Physicians Pediatric Healthcare
Warsaw, Indiana, United States