PLoS ONE (Jan 2017)

Diagnostic accuracy of tablet-based software for the detection of concussion.

  • Suosuo Yang,
  • Benjamin Flores,
  • Rotem Magal,
  • Kyrsti Harris,
  • Jonathan Gross,
  • Amy Ewbank,
  • Sasha Davenport,
  • Pablo Ormachea,
  • Waleed Nasser,
  • Weidong Le,
  • W Frank Peacock,
  • Yael Katz,
  • David M Eagleman

DOI
https://doi.org/10.1371/journal.pone.0179352
Journal volume & issue
Vol. 12, no. 7
p. e0179352

Abstract

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Despite the high prevalence of traumatic brain injuries (TBI), there are few rapid and straightforward tests to improve its assessment. To this end, we developed a tablet-based software battery ("BrainCheck") for concussion detection that is well suited to sports, emergency department, and clinical settings. This article is a study of the diagnostic accuracy of BrainCheck. We administered BrainCheck to 30 TBI patients and 30 pain-matched controls at a hospital Emergency Department (ED), and 538 healthy individuals at 10 control test sites. We compared the results of the tablet-based assessment against physician diagnoses derived from brain scans, clinical examination, and the SCAT3 test, a traditional measure of TBI. We found consistent distributions of normative data and high test-retest reliability. Based on these assessments, we defined a composite score that distinguishes TBI from non-TBI individuals with high sensitivity (83%) and specificity (87%). We conclude that our testing application provides a rapid, portable testing method for TBI.