Emergency Department Triage of Traumatic Head Injury Using a Brain Electrical Activity Biomarker: A Multisite Prospective Observational Validation Trial.
Objectives A brain electrical activity biomarker for identifying traumatic brain injury ( TBI) in emergency department ( ED) patients presenting with high Glasgow Coma Scale ( GCS) after sustaining a head injury has shown promise for objective, rapid triage. The main objective of this study was to p...
| Publicado en: | Academic Emergency Medicine Vol. 24; no. 5; pp. 617 - 628 |
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| Autores principales: | , , , , , , , , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
May2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=122988084&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 122988084 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10696563 Z27 jtl: Academic Emergency Medicine issn: 10696563 maglogo: Y pubinfo: dt: May2017 vid: 24 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 122988084 122988084 122988084 10.1111/acem.13175 122988084 ppf: 617 ppct: 11 formats: tig: atl: Emergency Department Triage of Traumatic Head Injury Using a Brain Electrical Activity Biomarker: A Multisite Prospective Observational Validation Trial. aug: au: Hanley, Daniel Prichep, Leslie S. Bazarian, Jeffrey Huff, J. Stephen Naunheim, Rosanne Garrett, John Jones, Elizabeth B. Wright, David W. O'Neill, John Badjatia, Neeraj Gandhi, Dheeraj Curley, Kenneth C. Chiacchierini, Richard O'Neil, Brian Hack, Dallas C. Panagos, Peter D. affil: Brain Injury Outcomes, The Johns Hopkins Medical Institutions, Baltimore MD sug: subj: Emergency Service Triage Brain Injuries Diagnosis Trauma Human Deep Brain Stimulation Electroencephalography Biological Markers Prospective Studies Glasgow Coma Scale Patient Admission Patient Selection Adolescence Adult Middle Age Aged Aged, 80 and Over Sensitivity and Specificity Data Analysis Software Confidence Intervals Tomography, X-Ray Computed Data Collection ROC Curve Funding Source Adolescent: 13-18 years Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Aged, 80 & over ab: Objectives A brain electrical activity biomarker for identifying traumatic brain injury ( TBI) in emergency department ( ED) patients presenting with high Glasgow Coma Scale ( 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 computed tomography ( 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 to 15 were candidates for study. A total of 720 patients (18-85 years) meeting inclusion/exclusion criteria were enrolled in this observational, prospective validation trial, at 11 U.S. EDs. GCS was 15 in 97%, with the first and third quartiles being 15 (interquartile range = 0) in the study population at the time of the evaluation. Standard clinical evaluations were conducted and 5 to 10 minutes of electroencephalogram ( 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 (likely CT+ or CT-) was 92.3% (95% confidence interval [ CI] = 87.8%-95.5%) for detection of any intracranial injury visible on CT ( CT+), with specificity of 51.6% (95% CI = 48.1%-55.1%) and negative predictive value ( NPV) of 96.0% (95% CI = 93.2%-97.9%). Using ternary classification (likely CT+, equivocal, likely CT-) demonstrated enhanced sensitivity to traumatic hematomas (≥1 mL of blood), 98.6% (95% CI = 92.6%-100.0%), and NPV of 98.2% (95% CI = 95.5%-99.5%). Conclusion 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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