Sensitivity and specificity of an eye movement tracking-based biomarker for concussion. (March 2016)

• Record Type: Journal Article
• Authors: Samadani, Uzma; Li, Meng; Qian, Meng; Laska, Eugene; Ritlop, Robert; Kolecki, Radek; Reyes, Marleen; Altomare, Lindsey; Sone, Je Yeong; Adem, Aylin; Huang, Paul; Kondziolka, Douglas; Wall, Stephen; Frangos, Spiros; Marmar, Charles
• Is Part Of: Concussion. Volume 1:Number 1(2016)
• Publication Date: 2016-03
• Subjects: biomarker -- concussion -- eye movement tracking; Brain -- Concussion -- Periodicals; 617.481044
• DOI: 10.2217/cnc.15.3
• Languages: English
• ISSNs: 2056-3299

Abstract

Object: The purpose of the current study is to determine the sensitivity and specificity of an eye tracking method as a classifier for identifying concussion.Methods: Brain injured and control subjects prospectively underwent both eye tracking and Sport Concussion Assessment Tool 3. The results of eye tracking biomarker based classifier models were then validated against a dataset of individuals not used in building a model. The area under the curve (AUC) of receiver operating characteristics was examined.Results: An optimal classifier based on best subset had an AUC of 0.878, and a cross-validated AUC of 0.852 in CT- subjects and an AUC of 0.831 in a validation dataset. The optimal misclassification rate in an external dataset (n = 254) was 13%.Conclusion: If one defines concussion based on history, examination, radiographic and Sport Concussion Assessment Tool 3 criteria, it is possible to generate an eye tracking based biomarker that enables detection of concussion with reasonably high sensitivity and specificity.