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?

Traumatic brain injury (TBI) is responsible for nearly 30% of all injury-related deaths in the United States.1 Affecting 1.7 million U.S. people annually, TBI is a primary cause of death and disability.2 Approximately 75% of all TBIs are considered mild, defined as an acute injury to the head as a result of blunt force trauma or rapid acceleration/deceleration causing loss of consciousness (<30 minutes), posttraumatic amnesia (<24 hours), or other transient neurologic abnormalities with a Glasgow Coma Scale score of 13–15.3,4 While the annual incidence of mild TBI is estimated to be 100 to 300 per 100,000 U.S. people, the true incidence rate is perhaps much higher because frequently mild TBI patients may decide not to seek medical care.5,6 Serving over 1.2 million TBI patients every year,1 the emergency department (ED) is a common access point for medical care for mild TBI patients, yet nearly 38% of isolated mild TBI patients are discharged to home from the ED without specific recommendations for follow-up.7 Emergency physicians and other clinicians are often challenged with the management and prognostication of mild TBI because these patients more commonly appear normal on the acute clinical examination. Nonetheless, the sequelae following injury can be profound and may severely limit functionality and participation.7–9 Indeed, up to 80% of mild TBI patients will suffer persistent neuropsychological symptoms.10 Identification of patients at high risk for protracted postconcussion symptoms (PCS) at the time of their initial presentation to the ED is important for targeting limited clinical resources such as specialty follow-up and rehabilitation, also allowing for an enrichment strategy for improving efficiency in clinical trials.11,12 The majority of mild TBI patients will have no acute intracranial findings on head computed tomography (HCT).13 Additionally, HCT poorly discriminates between those that will suffer long-term sequelae following mild TBI and those that will not.13,14 Other neuroimaging techniques such as diffusion tensor imaging and magnetic resonance imaging are expensive and time-prohibitive and are generally unavailable in most EDs.15 Currently, clinicians have no reliable and validated mechanism for providing accurate and objective prognosis for patients with mild TBI. The Kinesiological Instrument for Normal and Altered Reaching Movements (KINARM) End-Point system (BKIN Technologies, Kingston, Ontario, Canada) is a robotic device that is capable of objectively assessing multiple neurologic domains, including sensory, motor, and cognitive functions. It has been suggested that the device may detect subtle deficits that are not reliably observed in standard neurologic examination.16 The KINARM consists of two graspable robotic arms (see Figure 1) and a two-dimensional virtual reality display that, together, can create sophisticated visual and mechanical environments. The KINARM device has the ability to combine visual scanning, sensory stimulation, and forced feedback and has been used primarily to measure and quantify deficits in patients undergoing stroke rehabilitation.17 We refer to the capabilities provided in part by the programmable, mechanized handles as “robotic.” Figure 1 Simplified top view of the graspable robotic handles of the KINARM endpoint device (Image Courtesy: BKIN Technologies Inc.). KINARM = Kinesiological Instrument for Normal and Altered Reaching Movements. The goal of this study was to determine if robotic-assisted neuromotor assessment at the time of initial ED presentation might be predictive of more severe PCS at 3-week follow-up. We hypothesized that subtle sensorimotor and cognitive impairments, detected at the time of initial ED presentation and within 24 hours of injury, could predict subsequent PCS in a mild TBI population.