A Novel Tool for Evaluation of Mild Traumatic Brain Injury Patients in the Emergency Department: Does Robotic Assessment of Neuromotor Performance Following Injury Predict the Presence of Postconcussion Symptoms at Follow-up?

Vignesh Subbian, Jonathan J. Ratcliff, Joseph J. Korfhagen, Kimberly W. Hart, Jason M. Meunier, George J. Shaw, Christopher J. Lindsell, Fred R. Beyette

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Objectives Postconcussion symptoms (PCS) are a common complication of mild traumatic brain injury (TBI). Currently, there is no validated clinically available method to reliably predict at the time of injury who will subsequently develop PCS. The purpose of this study was to determine if PCS following mild TBI can be predicted during the initial presentation to an emergency department (ED) using a novel robotic-assisted assessment of neurologic function. Methods All patients presenting to an urban ED with a chief complaint of head injury within the preceding 24 hours were screened for inclusion from March 2013 to April 2014. The enrollment criteria were as follows: 1) age of 18 years or greater, 2) ability and willingness to provide written informed consent, 3) blunt head trauma and clinical diagnosis of isolated mild TBI by the treating physician, and 4) blood alcohol level of <100 mg/dL. Eligible mild TBI patients were enrolled and their neuromotor function was assessed in the ED using a battery of five tests that cover a range of proprioceptive, visuomotor, visuospatial, and executive function performance metrics. At 3 weeks postinjury, participants were contacted via telephone to complete the Rivermead Post-Concussion Symptoms Questionnaire to assess the presence of significant PCS. Results A total of 66 mild TBI patients were enrolled in the study with 42 of them completing both the ED assessment and the follow-up; 40 patients were included in the analyses. The area under the receiver operating characteristic curve (AUC) for the entire test battery was 0.72 (95% confidence interval [CI] = 0.54 to 0.90). The AUC for tests that primarily measure visuomotor and proprioceptive performance were 0.80 (95% CI = 0.65 to 0.95) and 0.71 (95% CI = 0.53 to 0.89), respectively. Conclusions The robotic-assisted test battery has the ability to discriminate between subjects who developed PCS and those who did not. Additionally, poor visuomotor and proprioceptive performance were most strongly associated with subsequent PCS.

Original languageEnglish (US)
Pages (from-to)382-392
Number of pages11
JournalAcademic Emergency Medicine
Volume23
Issue number4
DOIs
StatePublished - Apr 1 2016
Externally publishedYes

ASJC Scopus subject areas

  • Emergency Medicine

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