Jonathan J. Ratcliff

Gender and traumatic brain injury: Do the sexes fare differently?

Objective: To examine the relationship between gender and cognitive recovery 1 year following traumatic brain injury (TBI). Methods: Patients with blunt TBI were identified from the TBI Model Systems of Care National Database, multi-centre cohort study. The included patients (n = 325) were 16–45 years at injury, admitted to an acute care facility within 24 hours, received inpatient rehabilitation, had documented admission Glasgow Coma Scale (GCS) scores, completed neuropsychological follow-up 1 year post-injury and did not report pre-morbid learning problems. Multivariate analyses of variance examined the unadjusted association between gender and six cognitive domains examining attention/working memory, verbal memory, language, visual analytic skills, problem-solving and motor functioning. Analyses of covariance models were constructed to determine if confounding factors biased the observed associations. Results: Females performed significantly better than males on tests of attention/working memory and language. Males outperformed females in visual analytic skills. Gender remained significantly associated with performance in these areas when controlling for confounding variables. Conclusions: These results suggest a better cognitive recovery of females than males following TBI. However, future studies need to include non-TBI patients to control for possible pre-injury gender-related differences, as well as to conduct extended follow-ups to determine the stability of the observed differences.

ED disposition of the Glasgow Coma Scale 13 to 15 traumatic brain injury patient: Analysis of the Transforming Research and Clinical Knowledge in TBI study

OBJECTIVE Mild traumatic brain injury (mTBI) patients are frequently admitted to high levels of care despite limited evidence suggesting benefit. Such decisions may contribute to the significant cost of caring for mTBI patients. Understanding the factors that drive disposition decision making and how disposition is associated with outcomes is necessary for developing an evidence-base supporting disposition decisions. We evaluated factors associated with emergency department triage of mTBI patients to 1 of 3 levels of care: home, inpatient floor, or intensive care unit (ICU). METHODS This multicenter, prospective, cohort study included patients with isolated head trauma, a cranial computed tomography as part of routine care, and a Glasgow Coma Scale (GCS) score of 13 to 15. Data analysis was performed using multinomial logistic regression. RESULTS Of the 304 patients included, 167 (55%) were discharged home, 76 (25%) were admitted to the inpatient floor, and 61 (20%) were admitted to the ICU. In the multivariable model, admission to the ICU, compared with floor admission, varied by study site, odds ratio (OR) 0.18 (95% confidence interval [CI], 0.06-0.57); antiplatelet/anticoagulation therapy, OR 7.46 (95% CI, 1.79-31.13); skull fracture, OR 7.60 (95% CI, 2.44-23.73); and lower GCS, OR 2.36 (95% CI, 1.05-5.30). No difference in outcome was observed between the 3 levels of care. CONCLUSION Clinical characteristics and local practice patterns contribute to mTBI disposition decisions. Level of care was not associated with outcomes. Intracranial hemorrhage, GCS 13 to 14, skull fracture, and current antiplatelet/anticoagulant therapy influenced disposition decisions.

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?

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.

Integration of New Technology for Research in the Emergency Department: Feasibility of Deploying a Robotic Assessment Tool for Mild Traumatic Brain Injury Evaluation

The objective of this paper is to demonstrate the effective deployment of a robotic assessment tool for the evaluation of mild traumatic brain injury (mTBI) patients in a busy, resource-constrained, urban emergency department (ED). Methods: Functional integration of new robotic technology for research in the ED presented several obstacles that required a multidisciplinary approach, including participation from electrical and computer engineers, emergency medicine clinicians, and clinical operations staff of the hospital. Our team addressed many challenges in deployment of this advanced technology including: 1) adapting the investigational device for the unique clinical environment; 2) acquisition and maintenance of appropriate testing space for point-of-care assessment; and 3) dedicated technical support and upkeep of the device. Upon successful placement of the robotic device in the ED, the clinical study required screening of all patients presenting to the ED with complaints of head injury. Eligible patients were enrolled and tested using a robot-assisted test battery. Three weeks after the injury, patients were contacted to complete follow-up assessments. Results: Adapting the existing technology to meet anticipated physical constraints of the ED was performed by engineering a mobile platform. Due to the large footprint of the device, it was frequently moved before ultimately being fully integrated into the ED. Over 14 months, 1423 patients were screened. Twenty-eight patients could not be enrolled because the device was unavailable due to operations limitations. Technical problems with the device resulted in failure to include 20 patients. A total of 66 mTBI patients were enrolled and 42 of them completed both robot-assisted testing and follow-up assessment. Successful completion of screening and enrollment demonstrated that the challenges associated with integration of investigational devices into the ED can be effectively addressed through a collaborative patient-oriented research model. Conclusion: Effective deployment and use of new robotic technology for research in an urban academic ED required significant planning, coordination, and collaboration with key personnel from multiple disciplines. Clinical Impact: A pilot clinical study on mTBI patients using the robotic device provided useful data without disrupting the ED workflow. Integration of this technology into the ED serves as an important step toward pursing active clinical research in an acute care setting.

Quantitative assessment of post-concussion syndrome following mild traumatic brain injury using robotic technology

Post-Concussion Syndrome (PCS) is a common sequelae of mild Traumatic Brain Injury (mTBI). Currently, there is no reliable test to determine which patients will develop PCS following an mTBI. As a result, clinicians are challenged to identify patients at high risk for subsequent PCS. Hence, there is a need to develop an objective test that can guide clinical risk stratification and predict the likelihood of PCS at the initial point of care in an Emergency Department (ED). This paper presents the results of robotic-assisted neurologic testing completed on mTBI patients in the ED and its ability to predict PCS at 3 weeks post-injury. Preliminary results show that abnormal proprioception, as measured using robotic testing is associated with higher risk of developing PCS following mTBI. In this pilot study, proprioceptive measures obtained through robotic testing had a 77% specificity (95CI: 46%-94%) and a 64% sensitivity (95CI: 41%-82%).

Temporal profile of care following mild traumatic brain injury: predictors of hospital admission, follow-up referral and six-month outcome

ABSTRACT Objective: To investigate the clinical management and medical follow-up of patients with mild traumatic brain injury (mTBI) presenting to emergency departments (EDs). Methods: Overall, 168 adult patients with mTBI from the prospective, multicentre Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) Pilot study with Glasgow Coma Scale (GCS) 13–15, no polytrauma and alive at six months were included. Predictors for hospital admission, three-month follow-up referral and six-month functional disability (Glasgow Outcome Scale-Extended (GOSE) ≤ 6) were analysed using multivariable regression. Results: Overall, 48% were admitted to hospital, 22% received three-month referral and 27% reported six-month functional disability. Intracranial pathology on ED head computed tomography (multivariable odds ratio (OR) = 81.08, 95% confidence interval (CI) [10.28–639.36]) and amnesia (>30-minutes: OR = 5.27 [1.75–15.87]; unknown duration: OR = 4.43 [1.26–15.62]) predicted hospital admission. Older age (per-year OR = 1.03 [1.01–1.05]) predicted three-month referral, while part-time/unemployment predicted lack of referral (OR = 0.17 [0.06–0.50]). GCS < 15 (OR = 2.46 [1.05–5.78]) and prior history of seizures (OR = 3.62 [1.21–10.89]) predicted six-month functional disability, while increased education (per-year OR = 0.86 [0.76–0.97]) was protective. Conclusions: Clinical factors modulate triage to admission, while demographic/socioeconomic elements modulate follow-up care acquisition; six-month functional disability associates with both clinical and demographic/socioeconomic variables. Improving triage to acute and outpatient care requires further investigation to optimize resource allocation and outcome after mTBI. ClinicalTrials.gov registration: NCT01565551