The power of public-private partnership in medical technology innovation: Lessons from the development of FDA-cleared medical devices for assessment of concussion.

Given the convergence of the long and challenging development path for medical devices with the need for diagnostic capabilities for mild traumatic brain injury (mTBI/concussion), the effective role of public-private partnership (PPP) can be demonstrated to yield Food and Drug Administration (FDA) clearances and innovative product introductions. An overview of the mTBI problem and landscape was performed. A detailed situation analysis of an example of a PPP yielding an innovative product was further demonstrated. The example of PPP has led to multiple FDA clearances and product introductions in the TBI diagnostic product category where there was an urgent military and public need. Important lessons included defining the primary public and military health objective for new product introduction, the importance of the government-academia-industry PPP triad with a "collaboration towards solutions" Quality-by-Design (QbD) mindset to assure clinical validity with regulatory compliance, the development of device comparators and integration of measurements into a robust, evidence-based statistical and FDA pathway, and the utility of top-down, flexible, practical action while operating within governmental guidelines and patient safety.

Improved Sobriety Rates After Brain-Computer Interface-Based Cognitive Remediation Training.

Up to 80% of individuals seeking treatment fail in their attempts at sobriety. This study investigated whether 1) a cognitive remediation therapy (CRT) program augmented with a brain-computer interface (BCI) to influence brain performance metrics would increase participants' self-agency by restoring cognitive control performance; and 2) that ability increase would produce increased sobriety rates, greater than published treatment rates. The study employed a retrospective chart review structured to replicate a switching replication methodology (i.e., waitlist group) using a pre-test and post-test profile analysis quasi-experimental design. Participants' records were organized into treatment and non-treatment groups. Adult poly-substance users were recruited from alcohol and other drugs (AOD) use outpatient programs and AOD use treatment centers in the United States. Participants volunteered for pre- and post-testing without treatment (n = 121) or chose to enter the treatment program (n = 200). The treatment group engaged in a 48-session BCI/CRT augmented treatment program. Pre- and post-treatment measures comprised 14 areas from the Woodcock-Johnson Cognitive Abilities III Assessment Battery. An 18-month follow-up assessment measured maintenance of sobriety. After testing the difference for all variables across time between test groups, a significant multivariate effect was found. In addition, at 18 months post-treatment, 89% of the treatment group maintained sobriety, compared to 31% of the non-treatment group. Consistent with addiction neurobehavioral imbalance models, traditional treatment programs augmented with BCI/CRT training, focused on improving cognitive control abilities, may strengthen self-control and improve sobriety rates.

Brain Network Integrity Changes in Subjective Cognitive Decline: A Possible Physiological Biomarker of Dementia.

Objective: The current study seeks to illustrate potential early and objective neurophysiological biomarkers of neurodegenerative cognitive decline by evaluating features of brain network physiological performance and structure utilizing different modalities. Methods: This study included 17 clinically healthy individuals with self-reported cognitive decline (Subjective Cognitive Decline group, SCD, no objective finding of cognitive decline), 12 individuals diagnosed with amnestic Mild Cognitive Impairment (aMCI), 11 individuals diagnosed with Dementia, and 15 healthy subjects. All subjects underwent computerized cognitive performance testing, MRI scans including T1 for gray matter (GM) volume quantification, DTI for quantification of white matter (WM) microstructure fractional anisotropy (FA) and mean diffusivity (MD), and brain network function evaluation using DELPHI (TMS-EEG) measures of connectivity, excitability, and plasticity. Results: Both DELPHI analysis of network function and DTI analysis detected a significant decrease in connectivity, excitability, and WM integrity in the SCD group compared to healthy control (HC) subjects; a significant decrease was also noted for aMCI and Dementia groups compared to HC. In contrast, no significant decrease was observed in GM volume in the SCD group compared to healthy norms, a significant GM volume decrease was observed only in objectively cognitively impaired aMCI subjects and in dementia subjects. Conclusions: This study results suggest that objective direct measures of brain network physiology and WM integrity may provide early-stage biomarkers of neurodegenerative-related changes in subjects that have not yet displayed any other objective measurable cognitive or GM volume deficits which may facilitate early preventive care for neurodegenerative decline and dementia.

Improved Mild Closed Head Traumatic Brain Injury Outcomes With a Brain-Computer Interface Amplified Cognitive Remediation Training.

This study is a retrospective chart review of 200 clients who participated in a non-verbal restorative cognitive remediation training (rCRT) program between 2012 and 2020. Each client participated in the program for about 16 weeks, and the study as a whole occurred over a five-year period. The program was applied to effect proper neural functional remodeling needed to support resilient, flexible, and adaptable behaviors after encountering a mild closed head traumatic brain injury (mTBI). The rCRT program focused on improving functional performance in executive cognitive control networks as defined by fMRI studies. All rCRT activities were delivered in a semi-game-like manner, incorporating a brain-computer interface (BCI) that provided in-the-moment neural network performance integrity metrics (nPIMs) used to adjust the level of play required to properly engage long-term potentiation (LTP) and long-term depression (LTD) network learning rules. This study reports on t-test and Reliable Change Index (RCI) changes found within individual cognitive abilities' performance metrics derived from the Woodcock-Johnson Cognitive Abilities III Test. We compared pre- and post-scores from seven cognitive abilities considered dependent on executive cognitive control networks against seven non-executive control abilities. We observed significant improvements (p < 10-4) with large Cohen's deffect sizes (0.78-1.20) across 13 of 14 cognitive ability domains with a medium effect size (0.49) on the remaining one. The mean percent change for the pooled trained domain was double that observed for the pooled untrained domain, at 17.2% versus 8.3%, respectively. To further adjust for practice effects, practice effect RCI values were computed and further supported the effectiveness of the rCRT (trained RCI 1.4-4.8; untrained RCI 0.-08-0.75).

Phenotyping the Spectrum of Traumatic Brain Injury: A Review and Pathway to Standardization.

It is widely appreciated that the spectrum of traumatic brain injury (TBI), mild through severe, contains distinct clinical presentations, variably referred to as subtypes, phenotypes, and/or clinical profiles. As part of the Brain Trauma Blueprint TBI State of the Science, we review the current literature on TBI phenotyping with an emphasis on unsupervised methodological approaches, and describe five phenotypes that appear similar across reports. However, we also find the literature contains divergent analysis strategies, inclusion criteria, findings, and use of terms. Further, whereas some studies delineate phenotypes within a specific severity of TBI, others derive phenotypes across the full spectrum of severity. Together, these facts confound direct synthesis of the findings. To overcome this, we introduce PhenoBench, a freely available code repository for the standardization and evaluation of raw phenotyping data. With this review and toolset, we provide a pathway toward robust, data-driven phenotypes that can capture the heterogeneity of TBI, enabling reproducible insights and targeted care.

Comprehensive Blood Coagulation Profiling in Patients Using iCoagLab: Comparison Against Thromboelastography.

Delayed identification of coagulopathy and bleeding increases the risk of organ failure and death in hospitalized patients. Timely and accurate identification of impaired coagulation at the point-of-care can proactively identify bleeding risk and guide resuscitation, resulting in improved outcomes for patients. We test the accuracy of a novel optical coagulation sensing approach, termed iCoagLab, for comprehensive whole blood coagulation profiling and investigate its diagnostic accuracy in identifying patients at elevated bleeding risk. Whole blood samples from patients (N = 270) undergoing conventional coagulation testing were measured using the iCoagLab device. Recalcified and kaolin-activated blood samples were loaded in disposable cartridges and time-varying intensity fluctuation of laser speckle patterns were measured to quantify the clot viscoelastic modulus during coagulation. Coagulation parameters including the reaction time (R), clot progression time (K), clot progression rate (α), and maximum clot strength (MA) were derived from clot viscoelasticity traces and compared with mechanical thromboelastography (TEG). In all patients, a good correlation between iCoagLab- and TEG-derived parameters was observed (p < 0.001). Multivariate analysis showed that iCoagLab-derived parameters identified bleeding risk with sensitivity (94%) identical to, and diagnostic accuracy (89%) higher than TEG (87%). The diagnostic specificity of iCoagLab (77%) was significantly higher than TEG (69%). By rapidly and comprehensively permitting blood coagulation profiling the iCoagLab innovation is likely to advance the capability to identify patients with elevated risk for bleeding, with the ultimate goal of preventing life-threatening hemorrhage.

Evaluation of White Matter Integrity Utilizing the DELPHI (TMS-EEG) System.

OBJECTIVE: The aim of this study was to evaluate brain white matter (WM) fibers connectivity damage in stroke and traumatic brain injury (TBI) subjects by direct electrophysiological imaging (DELPHI) that analyzes transcranial magnetic stimulation (TMS)-evoked potentials (TEPs). METHODS: The study included 123 participants, out of which 53 subjects with WM-related pathologies (39 stroke, 14 TBI) and 70 healthy age-related controls. All subjects underwent DELPHI brain network evaluations of TMS-electroencephalogram (EEG)-evoked potentials and diffusion tensor imaging (DTI) scans for quantification of WM microstructure fractional anisotropy (FA). RESULTS: DELPHI output measures show a significant difference between the healthy and stroke/TBI groups. A multidimensional approach was able to classify healthy from unhealthy with a balanced accuracy of 0.81 ± 0.02 and area under the curve (AUC) of 0.88 ± 0.01. Moreover, a multivariant regression model of DELPHI output measures achieved prediction of WM microstructure changes measured by FA with the highest correlations observed for fibers proximal to the stimulation area, such as frontal corpus callosum (r = 0.7 ± 0.02), anterior internal capsule (r = 0.7 ± 0.02), and fronto-occipital fasciculus (r = 0.65 ± 0.03). CONCLUSION: These results indicate that features of TMS-evoked response are correlated to WM microstructure changes observed in pathological conditions, such as stroke and TBI, and that a multidimensional approach combining these features in supervised learning methods serves as a strong indicator for abnormalities and changes in WM integrity.

The modern landscape of sport-related concussion research: key achievements and future directions.

The study of contact and collision sport athletes at risk for concussion began approximately three decades ago. Since then, sport-related concussion (SRC) research across several medical specialties has helped to develop consensus guidelines for clinical management through interdisciplinary efforts. The modern landscape of SRC research includes large-scale investigations to define the natural history of concussion and identify factors that should guide prevention, diagnosis, and treatment specific to the individual patient. We now know that the clinical and physiologic effects of concussion are related but independent constructs deserving further scientific exploration. This has sparked research that incorporates advanced neuroimaging, fluid biomarkers, biomechanics, and genomics, in addition to standard clinical outcomes. Additionally, translational research has informed our understanding of optimal rehabilitation strategies and led to a shift from the "complete rest" approach to earlier, active management interventions after concussion. Collectively, these advancements are likely to substantially improve patient outcomes after SRC and, ultimately, may prove beneficial for identifying and appropriately managing those at risk for longer-term difficulties associated with repetitive head impact exposure. The broader public health implications of improving sports safety and encouraging developmentally appropriate participation among youth and adolescents are a particularly important byproduct of continued research into SRC.

Serum GFAP and UCH-L1 for prediction of absence of intracranial injuries on head CT (ALERT-TBI): a multicentre observational study.

BACKGROUND: More than 50 million people worldwide sustain a traumatic brain injury (TBI) annually. Detection of intracranial injuries relies on head CT, which is overused and resource intensive. Blood-based brain biomarkers hold the potential to predict absence of intracranial injury and thus reduce unnecessary head CT scanning. We sought to validate a test combining ubiquitin C-terminal hydrolase-L1 (UCH-L1) and glial fibrillary acidic protein (GFAP), at predetermined cutoff values, to predict traumatic intracranial injuries on head CT scan acutely after TBI. METHODS: This prospective, multicentre observational trial included adults (≥18 years) presenting to participating emergency departments with suspected, non-penetrating TBI and a Glasgow Coma Scale score of 9-15. Patients were eligible if they had undergone head CT as part of standard emergency care and blood collection within 12 h of injury. UCH-L1 and GFAP were measured in serum and analysed using prespecified cutoff values of 327 pg/mL and 22 pg/mL, respectively. UCH-L1 and GFAP assay results were combined into a single test result that was compared with head CT results. The primary study outcomes were the sensitivity and the negative predictive value (NPV) of the test result for the detection of traumatic intracranial injury on head CT. FINDINGS: Between Dec 6, 2012, and March 20, 2014, 1977 patients were recruited, of whom 1959 had analysable data. 125 (6%) patients had CT-detected intracranial injuries and eight (<1%) had neurosurgically manageable injuries. 1288 (66%) patients had a positive UCH-L1 and GFAP test result and 671 (34%) had a negative test result. For detection of intracranial injury, the test had a sensitivity of 0·976 (95% CI 0·931-0·995) and an NPV of 0·996 (0·987-0·999). In three (<1%) of 1959 patients, the CT scan was positive when the test was negative. INTERPRETATION: These results show the high sensitivity and NPV of the UCH-L1 and GFAP test. This supports its potential clinical role for ruling out the need for a CT scan among patients with TBI presenting at emergency departments in whom a head CT is felt to be clinically indicated. Future studies to determine the value added by this biomarker test to head CT clinical decision rules could be warranted. FUNDING: Banyan Biomarkers and US Army Medical Research and Materiel Command.

Implementation of the 2017 Berlin Concussion in Sport Group Consensus Statement in contact and collision sports: a joint position statement from 11 national and international sports organisations.

The 2017 Berlin Concussion in Sport Group Consensus Statement provides a global summary of best practice in concussion prevention, diagnosis and management, underpinned by systematic reviews and expert consensus. Due to their different settings and rules, individual sports need to adapt concussion guidelines according to their specific regulatory environment. At the same time, consistent application of the Berlin Consensus Statement's themes across sporting codes is likely to facilitate superior and uniform diagnosis and management, improve concussion education and highlight collaborative research opportunities. This document summarises the approaches discussed by medical representatives from the governing bodies of 10 different contact and collision sports in Dublin, Ireland in July 2017. Those sports are: American football, Australian football, basketball, cricket, equestrian sports, football/soccer, ice hockey, rugby league, rugby union and skiing. This document had been endorsed by 11 sport governing bodies/national federations at the time of being published.

A National Study on the Effects of Concussion in Collegiate Athletes and US Military Service Academy Members: The NCAA-DoD Concussion Assessment, Research and Education (CARE) Consortium Structure and Methods.

BACKGROUND: The natural history of mild traumatic brain injury (TBI) or concussion remains poorly defined and no objective biomarker of physiological recovery exists for clinical use. The National Collegiate Athletic Association (NCAA) and the US Department of Defense (DoD) established the Concussion Assessment, Research and Education (CARE) Consortium to study the natural history of clinical and neurobiological recovery after concussion in the service of improved injury prevention, safety and medical care for student-athletes and military personnel. OBJECTIVES: The objectives of this paper were to (i) describe the background and driving rationale for the CARE Consortium; (ii) outline the infrastructure of the Consortium policies, procedures, and governance; (iii) describe the longitudinal 6-month clinical and neurobiological study methodology; and (iv) characterize special considerations in the design and implementation of a multicenter trial. METHODS: Beginning Fall 2014, CARE Consortium institutions have recruited and enrolled 23,533 student-athletes and military service academy students (approximately 90% of eligible student-athletes and cadets; 64.6% male, 35.4% female). A total of 1174 concussions have been diagnosed in participating subjects, with both concussion and baseline cases deposited in the Federal Interagency Traumatic Brain Injury Research (FITBIR) database. CONCLUSIONS: Challenges have included coordinating regulatory issues across civilian and military institutions, operationalizing study procedures, neuroimaging protocol harmonization across sites and platforms, construction and maintenance of a relational database, and data quality and integrity monitoring. The NCAA-DoD CARE Consortium represents a comprehensive investigation of concussion in student-athletes and military service academy students. The richly characterized study sample and multidimensional approach provide an opportunity to advance the field of concussion science, not only among student athletes but in all populations at risk for mild TBI.

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 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.

Emergency Department Triage of Traumatic Head Injury Using a Brain Electrical Activity Biomarker: A Multisite Prospective Observational Validation Trial.

OBJECTIVES: A brain electrical activity biomarker for identifying traumatic brain injury (TBI) in emergency department (ED) patients presenting with high Glasgow Coma Scale (GCS) after sustaining a head injury has shown promise for objective, rapid triage. The main objective of this study was to prospectively evaluate the efficacy of an automated classification algorithm to determine the likelihood of being computed tomography (CT) positive, in high-functioning TBI patients in the acute state. METHODS: Adult patients admitted to the ED for evaluation within 72 hours of sustaining a closed head injury with GCS 12 to 15 were candidates for study. A total of 720 patients (18-85 years) meeting inclusion/exclusion criteria were enrolled in this observational, prospective validation trial, at 11 U.S. EDs. GCS was 15 in 97%, with the first and third quartiles being 15 (interquartile range = 0) in the study population at the time of the evaluation. Standard clinical evaluations were conducted and 5 to 10 minutes of electroencephalogram (EEG) was acquired from frontal and frontal-temporal scalp locations. Using an a priori derived EEG-based classification algorithm developed on an independent population and applied to this validation population prospectively, the likelihood of each subject being CT+ was determined, and performance metrics were computed relative to adjudicated CT findings. RESULTS: Sensitivity of the binary classifier (likely CT+ or CT-) was 92.3% (95% confidence interval [CI] = 87.8%-95.5%) for detection of any intracranial injury visible on CT (CT+), with specificity of 51.6% (95% CI = 48.1%-55.1%) and negative predictive value (NPV) of 96.0% (95% CI = 93.2%-97.9%). Using ternary classification (likely CT+, equivocal, likely CT-) demonstrated enhanced sensitivity to traumatic hematomas (≥1 mL of blood), 98.6% (95% CI = 92.6%-100.0%), and NPV of 98.2% (95% CI = 95.5%-99.5%). CONCLUSION: Using an EEG-based biomarker high accuracy of predicting the likelihood of being CT+ was obtained, with high NPV and sensitivity to any traumatic bleeding and to hematomas. Specificity was significantly higher than standard CT decision rules. The short time to acquire results and the ease of use in the ED environment suggests that EEG-based classifier algorithms have potential to impact triage and clinical management of head-injured patients.

Time Course and Diagnostic Accuracy of Glial and Neuronal Blood Biomarkers GFAP and UCH-L1 in a Large Cohort of Trauma Patients With and Without Mild Traumatic Brain Injury.

IMPORTANCE: Glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase L1 (UCH-L1) have been widely studied and show promise for clinical usefulness in suspected traumatic brain injury (TBI) and concussion. Understanding their diagnostic accuracy over time will help translate them into clinical practice. OBJECTIVES: To evaluate the temporal profiles of GFAP and UCH-L1 in a large cohort of trauma patients seen at the emergency department and to assess their diagnostic accuracy over time, both individually and in combination, for detecting mild to moderate TBI (MMTBI), traumatic intracranial lesions on head computed tomography (CT), and neurosurgical intervention. DESIGN, SETTING, AND PARTICIPANTS: This prospective cohort study enrolled adult trauma patients seen at a level I trauma center from March 1, 2010, to March 5, 2014. All patients underwent rigorous screening to determine whether they had experienced an MMTBI (blunt head trauma with loss of consciousness, amnesia, or disorientation and a Glasgow Coma Scale score of 9-15). Of 3025 trauma patients assessed, 1030 met eligibility criteria for enrollment, and 446 declined participation. Initial blood samples were obtained in 584 patients enrolled within 4 hours of injury. Repeated blood sampling was conducted at 4, 8, 12, 16, 20, 24, 36, 48, 60, 72, 84, 96, 108, 120, 132, 144, 156, 168, and 180 hours after injury. MAIN OUTCOMES AND MEASURES: Diagnosis of MMTBI, presence of traumatic intracranial lesions on head CT scan, and neurosurgical intervention. RESULTS: A total of 1831 blood samples were drawn from 584 patients (mean [SD] age, 40 [16] years; 62.0% [362 of 584] male) over 7 days. Both GFAP and UCH-L1 were detectible within 1 hour of injury. GFAP peaked at 20 hours after injury and slowly declined over 72 hours. UCH-L1 rose rapidly and peaked at 8 hours after injury and declined rapidly over 48 hours. Over the course of 1 week, GFAP demonstrated a diagnostic range of areas under the curve for detecting MMTBI of 0.73 (95% CI, 0.69-0.77) to 0.94 (95% CI, 0.78-1.00), and UCH-L1 demonstrated a diagnostic range of 0.30 (95% CI, 0.02-0.50) to 0.67 (95% CI, 0.53-0.81). For detecting intracranial lesions on CT, the diagnostic ranges of areas under the curve were 0.80 (95% CI, 0.67-0.92) to 0.97 (95% CI, 0.93-1.00)for GFAP and 0.31 (95% CI, 0-0.63) to 0.77 (95% CI, 0.68-0.85) for UCH-L1. For distinguishing patients with and without a neurosurgical intervention, the range for GFAP was 0.91 (95% CI, 0.79-1.00) to 1.00 (95% CI, 1.00-1.00), and the range for UCH-L1 was 0.50 (95% CI, 0-1.00) to 0.92 (95% CI, 0.83-1.00). CONCLUSIONS AND RELEVANCE: GFAP performed consistently in detecting MMTBI, CT lesions, and neurosurgical intervention across 7 days. UCH-L1 performed best in the early postinjury period.

Ability of Serum Glial Fibrillary Acidic Protein, Ubiquitin C-Terminal Hydrolase-L1, and S100B To Differentiate Normal and Abnormal Head Computed Tomography Findings in Patients with Suspected Mild or Moderate Traumatic Brain Injury.

Head computed tomography (CT) imaging is still a commonly obtained diagnostic test for patients with minor head injury despite availability of clinical decision rules to guide imaging use and recommendations to reduce radiation exposure resulting from unnecessary imaging. This prospective multicenter observational study of 251 patients with suspected mild to moderate traumatic brain injury (TBI) evaluated three serum biomarkers' (glial fibrillary acidic protein [GFAP], ubiquitin C-terminal hydrolase-L1 [UCH-L1] and S100B measured within 6 h of injury) ability to differentiate CT negative and CT positive findings. Of the 251 patients, 60.2% were male and 225 (89.6%) had a presenting Glasgow Coma Scale score of 15. A positive head CT (intracranial injury) was found in 36 (14.3%). UCH-L1 was 100% sensitive and 39% specific at a cutoff value >40 pg/mL. To retain 100% sensitivity, GFAP was 0% specific (cutoff value 0 pg/mL) and S100B had a specificity of only 2% (cutoff value 30 pg/mL). All three biomarkers had similar values for areas under the receiver operator characteristic curve: 0.79 (95% confidence interval; 0.70-0.88) for GFAP, 0.80 (0.71-0.89) for UCH-L1, and 0.75 (0.65-0.85) for S100B. Neither GFAP nor UCH-L1 curve values differed significantly from S100B (p = 0.21 and p = 0.77, respectively). In our patient cohort, UCH-L1 outperformed GFAP and S100B when the goal was to reduce CT use without sacrificing sensitivity. UCH-L1 values <40 pg/mL could potentially have aided in eliminating 83 of the 215 negative CT scans. These results require replication in other studies before the test is used in actual clinical practice.

Concussion guidelines step 1: systematic review of prevalent indicators.

BACKGROUND: Currently, there is no evidence-based definition for concussion that is being uniformly applied in clinical and research settings. OBJECTIVE: To conduct a systematic review of the highest-quality literature about concussion and to assemble evidence about the prevalence and associations of key indicators of concussion. The goal was to establish an evidence-based foundation from which to derive, in future work, a definition, diagnostic criteria, and prognostic indicators for concussion. METHODS: Key questions were developed, and an electronic literature search from 1980 to 2012 was conducted to acquire evidence about the prevalence of and associations among signs, symptoms, and neurologic and cognitive deficits in samples of individuals exposed to potential concussive events. Included studies were assessed for potential for bias and confound and rated as high, medium, or low potential for bias and confound. Those rated as high were excluded from the analysis. Studies were further triaged on the basis of whether the definition of a case of concussion was exclusive or inclusive; only those with wide, inclusive case definitions were used in the analysis. Finally, only studies reporting data collected at fixed time points were used. For a study to be included in the conclusions, it was required that the presence of any particular sign, symptom, or deficit be reported in at least 2 independent samples. RESULTS: From 5437 abstracts, 1362 full-text publications were reviewed, of which 231 studies were included in the final library. Twenty-six met all criteria required to be used in the analysis, and of those, 11 independent samples from 8 publications directly contributed data to conclusions. Prevalent and consistent indicators of concussion are (1) observed and documented disorientation or confusion immediately after the event, (2) impaired balance within 1 day after injury, (3) slower reaction time within 2 days after injury, and/or (4) impaired verbal learning and memory within 2 days after injury. CONCLUSION: The results of this systematic review identify the consistent and prevalent indicators of concussion and their associations, derived from the strongest evidence in the published literature. The product is an evidence-based foundation from which to develop diagnostic criteria and prognostic indicators.