Diagnostic accuracy of tablet-based software for the detection of concussion.
Suosuo YangBenjamin FloresRotem MagalKyrsti HarrisJonathan GrossAmy EwbankSasha DavenportPablo OrmacheaWaleed NasserWeidong LeW Frank PeacockYael KatzDavid M EaglemanPublished in: PloS one (2017)
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.
Keyphrases
- emergency department
- traumatic brain injury
- mild traumatic brain injury
- severe traumatic brain injury
- loop mediated isothermal amplification
- white matter
- end stage renal disease
- ejection fraction
- chronic pain
- computed tomography
- resting state
- newly diagnosed
- chronic kidney disease
- spinal cord injury
- primary care
- prognostic factors
- healthcare
- magnetic resonance imaging
- adverse drug
- big data
- label free
- multiple sclerosis
- real time pcr
- patient reported outcomes
- artificial intelligence
- contrast enhanced
- clinical evaluation
- patient reported