Concussion (Mar 2016)

Sensitivity and specificity of an eye movement tracking-based biomarker for concussion

  • Uzma Samadani,
  • Meng Li,
  • Meng Qian,
  • Eugene Laska,
  • Robert Ritlop,
  • Radek Kolecki,
  • Marleen Reyes,
  • Lindsey Altomare,
  • Je Yeong Sone,
  • Aylin Adem,
  • Paul Huang,
  • Douglas Kondziolka,
  • Stephen Wall,
  • Spiros Frangos,
  • Charles Marmar

DOI
https://doi.org/10.2217/cnc.15.3
Journal volume & issue
Vol. 1, no. 1

Abstract

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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.

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