Emergency Department triage of traumatic head injury using brain electrical activity biomarkers: a multisite prospective observational validation trial

Abstract

Objectives

A brain electrical activity biomarker for identifying traumatic brain injury (TBI) in Emergency Department (ED) patients presenting with high GCS after sustaining a head injury has shown promise for objective, rapid, triage. The main objective of this study was to prospectively evaluate the efficacy of an automated classification algorithm to determine the likelihood of being CT positive, in high functioning TBI patients in the acute state.

Methods

Adult patients admitted to the ED for evaluation within 72 hours of sustaining a closed head injury with GCS 12-15were candidates for study. 720 patients (18-85 years) meeting inclusion/exclusion criteria were enrolled in this observational, prospective validation trial, at 11 US Emergency Departments. Glasgow Coma Scale was 15 in 97%, with the first and third quartile being 15 (IQR=0) in the study population at the time of the evaluation. Standard clinical evaluations were conducted and 5-10 minutes of EEG was acquired from frontal and frontal-temporal scalp locations. Using an a priori derived EEG based classification algorithm developed on an independent population and applied to this validation population prospectively, the likelihood of each subject being CT+ was determined, and performance metrics were computed relative to adjudicated CT findings.

Results

Sensitivity of the binary classifier (CT+ or CT-) was 92.3% (87.8%, 95.5%) for detection of any intracranial injury visible on CT (CT+), with specificity of 51·6% (48.1%, 55.1%) and negative predictive value of 96.0% (93.2%, 97.9%). Using ternary classification (CT+, Equivocal, CT-) demonstrated enhanced sensitivity to traumatic hematomas (≥1cc of blood), 98.6% (92.6%, 100.0%) and negative predictive value of 98.2% (95.5%, 99.5%).

Conclusions

Using an EEG-based biomarker high accuracy of predicting the likelihood of being CT+ was obtained, with high NPV and sensitivity to any traumatic bleeding and to hematomas. Specificity was significantly higher than standard CT decision rules. The short time to acquire results and the ease of use in the ED environment suggests that EEG based classifier algorithms have potential to impact triage and clinical management of head injured patients.

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