Citation

Subbian V, Ratcliff JJ, Korfhagen JJ, Hart KW, Meunier JM, Shaw GJ, Lindsell CJ, Beyette FR. Acad. Emerg. Med. 2016; 23(4): 382-392.

Affiliation

Electrical Engineering, University of Cincinnati, 2600, Clifton Avenue, PO Box 210030, Cincinnati, OH, 45221-0030.

Copyright

(Copyright © 2016, Society for Academic Emergency Medicine, Publisher John Wiley and Sons)

DOI

10.1111/acem.12906

PMID

26806406

Abstract

OBJECTIVE: Post-Concussion 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 is 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: (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 (BAL) of < 100 mg/dl. Eligible mild TBI patients were enrolled and their neuromotor function assessed in the ED using a battery of five tests that cover a range of proprioceptive, visuomotor, visuospatial, and executive function performance metrics. At three weeks post-injury, 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% CI 0.54 - 0.90). The AUC for tests that primarily measure visuomotor and proprioceptive performance was 0.80 (95% CI: 0.65 - 0.95) and 0.71 (95% CI: 0.53 - 0.89), respectively.

CONCLUSION: 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. This article is protected by copyright. All rights reserved.

Language: en