Validation of a Multimodal EEG-Based Index to Aid in Diagnosing and Tracking Concussion Among Athletes
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Abstract
Objective The goal of this study was to validate an EEG based multimodal index to aid in the assessment of concussion at time of injury, severity of concussion, and aid in evaluating readiness to return to play/activity.
Background The absence of a gold standard for diagnosis of concussion results in reliance on subjective self-report of symptoms. EEG has been demonstrated to be sensitive to changes in brain function following head injury, especially in connectivity. Using machine learning with inputs primarily from EEG measures, and including multimodal inputs, an objective marker of the likelihood of concussion (Concussion Index, CI) was derived.
Design/Methods Male and female concussed athletes and controls ages of 13–25 years, represented a convenience sample (n = 580), enrolled from US High School, Colleges, and Concussion Clinics. Concussed subjects had a witnessed head impact and were removed from play by site guidelines. Assessments were performed within 72 hours of injury, at clinically determined return to play (RTP), 45 days following RTP, and included EEG (frontal and frontotemporal regions), neurocognitive performance, and standard concussion assessments.
Results Sensitivity = 85.99%, Specificity = 70.78%, NPV = 90.10% and PPV = 62.02, were obtained. Results demonstrated significance: (1) between CI at injury compared to RTP (p < 0.0001); (2) between CI in patients with rapid (<14 days) compared with those with prolonged recovery (=14 days), (p = 0.0038); (3) stability over time in controls (p < 0.0001); and (4) between CI and total symptom burden (correlation coefficient 0.8031, p < 0.0001).
Conclusions This study independently validated a multimodal, EEG-based, objective index of concussion (CI). The neurotechnology platform incorporating this capability is handheld, rapid to use, and lends itself to incorporation into the standard assessment of concussion to aid in clinical diagnosis and assessment of readiness to RTP. This data supported the FDA clearance for the Concussion Index (embedded in the BrainScope medical device).
Footnotes
Disclosure: Dr. Bazarian has received personal compensation in the range of $5,000–$9,999 for serving as a Consultant for Abbott. Dr. Bazarian has received personal compensation in the range of $500–$4,999 for serving as a Consultant for Q30 Innovations. Dr. Bazarian has received personal compensation in the range of $500–$4,999 for serving as a Consultant for Banyan Biomarkers. Dr. Bazarian has received personal compensation in the range of $500–$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Cato. The institution of Dr. Bazarian has received research support from BrainScope. The institution of Dr. Bazarian has received research support from BrainBox Solutions. Dr. Prichep has received personal compensation for serving as an employee of BrainScope Company. Dr. Prichep has received personal compensation in the range of $5,000–$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for WAVE Neuroscience. Dr. Prichep has received intellectual property interests from a discovery or technology relating to health care.
- © 2021 American Academy of Neurology
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