AUTHOR=Samadani Uzma , Spinner Robert J. , Dynkowski Gerard , Kirelik Susan , Schaaf Tory , Wall Stephen P. , Huang Paul 

TITLE=Eye tracking for classification of concussion in adults and pediatrics

JOURNAL=Frontiers in Neurology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2022.1039955

DOI=10.3389/fneur.2022.1039955

ISSN=1664-2295

ABSTRACT=Potentially concussed subjects recruited in emergency department and concussion clinic settings prospectively underwent eye tracking and a subset of the Sport Concussion Assessment Tool 3 at 6 sites. The results of an eye tracking-based classifier model were then validated against a pre-specified algorithm with a cutoff for concussed vs. non-concussed. The sensitivity and specificity of eye tracking were calculated after plotting of the receiver operating characteristic curve and calculation of the AUC (area under curve). The sensitivity and specificity of the algorithm was 80.4% and 66.1%, The AUC was 0.718. The misclassification rate (n = 282) was 31.6%. A pre-specified algorithm and cutoff for diagnosis of concussion vs. non-concussion has a sensitivity and specificity that is useful as a baseline-free aid in diagnosis of concussion.  Eye tracking has potential to serve as an objective “gold-standard” for detection of neurophysiologic disruption due to brain injury.