Increased prognostic accuracy of TBI when a brain electrical activity biomarker is added to loss of consciousness (LOC).

Background: Extremely high accuracy for predicting CT+ traumatic brain injury (TBI) using a quantitative EEG (QEEG) based multivariate classification algorithm was demonstrated in an independent validation trial, in Emergency Department (ED) patients, using an easy to use handheld device. This study...

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Publicado en:American Journal of Emergency Medicine Vol. 35; no. 7; pp. 949 - 953
Autores principales: Hack, Dallas, Huff, J. Stephen, Curley, Kenneth, Naunheim, Roseanne, Ghosh Dastidar, Samanwoy, Prichep, Leslie S.
Formato: research Journal Article
Publicado: Elsevier B.V. Jul2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul2017
      vid: 35
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      pub: Elsevier B.V.
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        10.1016/j.ajem.2017.01.060
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        atl: Increased prognostic accuracy of TBI when a brain electrical activity biomarker is added to loss of consciousness (LOC).
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          Hack, Dallas
          Huff, J. Stephen
          Curley, Kenneth
          Naunheim, Roseanne
          Ghosh Dastidar, Samanwoy
          Prichep, Leslie S.
        affil: Brain Health, Sevierville, TN, USA
      sug:
        subj:
          Electroencephalography
          Amnesia Diagnosis
          Unconsciousness Physiopathology
          Subarachnoid Hemorrhage Diagnosis
          Aged
          Male
          Aged, 80 and Over
          Head Injuries Complications
          Algorithms
          Human
          Adolescence
          Adult
          Subarachnoid Hemorrhage Physiopathology
          Predictive Value of Tests
          Tomography, X-Ray Computed
          Head Injuries Diagnosis
          Female
          Middle Age
          Prognosis
          Subarachnoid Hemorrhage Complications
          Head Injuries Physiopathology
          Unconsciousness Complications
          Reproducibility of Results
          Amnesia Complications
          Amnesia Physiopathology
          Retrospective Design
          Young Adult
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Aged: 65+ years
          Aged, 80 & over
          Adolescent: 13-18 years
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Male
          Female
      ab: Background: Extremely high accuracy for predicting CT+ traumatic brain injury (TBI) using a quantitative EEG (QEEG) based multivariate classification algorithm was demonstrated in an independent validation trial, in Emergency Department (ED) patients, using an easy to use handheld device. This study compares the predictive power using that algorithm (which includes LOC and amnesia), to the predictive power of LOC alone or LOC plus traumatic amnesia.Participants: ED patients 18-85years presenting within 72h of closed head injury, with GSC 12-15, were study candidates. 680 patients with known absence or presence of LOC were enrolled (145 CT+ and 535 CT- patients).Methods: 5-10min of eyes closed EEG was acquired using the Ahead 300 handheld device, from frontal and frontotemporal regions. The same classification algorithm methodology was used for both the EEG based and the LOC based algorithms. Predictive power was evaluated using area under the ROC curve (AUC) and odds ratios.Results: The QEEG based classification algorithm demonstrated significant improvement in predictive power compared with LOC alone, both in improved AUC (83% improvement) and odds ratio (increase from 4.65 to 16.22). Adding RGA and/or PTA to LOC was not improved over LOC alone.Conclusions: Rapid triage of TBI relies on strong initial predictors. Addition of an electrophysiological based marker was shown to outperform report of LOC alone or LOC plus amnesia, in determining risk of an intracranial bleed. In addition, ease of use at point-of-care, non-invasive, and rapid result using such technology suggests significant value added to standard clinical prediction.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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