Traumatic brain injury in the elderly with high Glasgow coma scale and low injury severity scores: Factors influencing outcomes.

BACKGROUND: Current trauma activation guidelines do not clearly address age as a risk factor when leveling trauma patients. Glasgow coma scale (GCS) and mode of injury play a major role in leveling trauma patients. We studied the above relationship in our elderly patients presenting with traumatic head injury. METHODS: This study was a retrospective analysis of patients who presented to the emergency department with traumatic brain injuries. We classified the 270 patients into two groups. Group A was 64 years and younger, and group B was 65 years and older. Their GCS, ISS, age, sex, comorbidities, and anticoagulant use were abstracted. The primary outcome was mortality and length of stay. The groups were compared using an independent student's t-test and Chi-square analysis. The Cox regression analysis was used to analyze differences in the outcome while adjusting for the above factors. RESULTS: There were 140 patients in group A, and 130 patients in group B who presented to the ED with a GCS of 14-15 and an ISS of below 15. The mean ISS significantly differed between group A (6.2 ± 6.8) vs (7.9 ± 3.2) in group B (p < 0.0001). The most common diagnosis in group A was concussion (57.3%), while in group B was subdural and subarachnoid hemorrhage (55%). In group B, 13.8% presented as a level one or level two trauma activation. The mean hospital and intensive care stay for group A was 2.1 (±1.9) days and 0.9 (±1.32) days, respectively, versus 4.2 (±3.04) days and 2.4 (±2.02 days) for the elderly group B. Mortality in group A was zero and in group B was 3.8%. Cox regression analysis showed age as an independent predictor of death as well as length of stay. CONCLUSION: Elderly traumatic brain injury patients presenting to the ED with minor trauma and high GCS should be triaged at a higher level in most cases.

Trajectories of Fatigue, Psychological Distress, and Coping Styles After Mild Traumatic Brain Injury: A 6-Month Prospective Cohort Study.

OBJECTIVE: To analyze fatigue after mild traumatic brain injury (TBI) with latent class growth analysis (LCGA) to determine distinct recovery trajectories and investigate influencing factors, including emotional distress and coping styles. DESIGN: An observational cohort study design with validated questionnaires assessing fatigue, anxiety, depression, posttraumatic stress, and coping at 2 weeks and 3 and 6 months postinjury. SETTING: Three level 1 trauma centers. PARTICIPANTS: Patients with mild TBI (N=456). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Fatigue was measured with the fatigue severity subscale of the Checklist Individual Strength, including 8 items (sum score, 8-56). Subsequently, 3 clinical categories were created: high (score, 40-56), moderate (score, 26-38), and low (score, 8-25). RESULTS: From the entire mild TBI group, 4 patient clusters with distinct patterns for fatigue, emotional distress, and coping styles were found with LCGA. Clusters 1 and 2 showed favorable recovery from fatigue over time, with low emotional distress and the predominant use of active coping in cluster 1 (30%) and low emotional distress and decreasing passive coping in cluster 2 (25%). Clusters 3 and 4 showed unfavorable recovery, with persistent high fatigue and increasing passive coping together with low emotional distress in cluster 3 (27%) and high emotional distress in cluster 4 (18%). Patients with adverse trajectories were more often women and more often experiencing sleep disturbances and pain. CONCLUSIONS: The prognosis for recovery from posttraumatic fatigue is favorable for 55% of mild TBI patients. Patients at risk for chronic fatigue can be signaled in the acute phase postinjury based on the presence of high fatigue, high passive coping, and, for a subgroup of patients, high emotional distress. LCGA proved to be a highly valuable and multipurpose statistical method to map distinct courses of disease-related processes over time.

Association of clinically important traumatic brain injury and Glasgow Coma Scale scores in children with head injury.

OBJECTIVE: Head injury (HI) is a common presentation to emergency departments (EDs). The risk of clinically important traumatic brain injury (ciTBI) is low. We describe the relationship between Glasgow Coma Scale (GCS) scores at presentation and risk of ciTBI. METHODS: Planned secondary analysis of a prospective observational study of children<18 years who presented with HIs of any severity at 10 Australian/New Zealand centres. We reviewed all cases of ciTBI, with ORs (Odds Ratio) and their 95% CIs (Confidence Interval) calculated for risk of ciTBI based on GCS score. We used receiver operating characteristic (ROC) curves to determine the ability of total GCS score to discriminate ciTBI, mortality and need for neurosurgery. RESULTS: Of 20 137 evaluable patients with HI, 280 (1.3%) sustained a ciTBI. 82 (29.3%) patients underwent neurosurgery and 13 (4.6%) died. The odds of ciTBI increased steadily with falling GCS. Compared with GCS 15, odds of ciTBI was 17.5 (95% CI 12.4 to 24.6) times higher for GCS 14, and 484.5 (95% CI 289.8 to 809.7) times higher for GCS 3. The area under the ROC curve for the association between GCS and ciTBI was 0.79 (95% CI 0.77 to 0.82), for GCS and mortality 0.91 (95% CI 0.82 to 0.99) and for GCS and neurosurgery 0.88 (95% CI 0.83 to 0.92). CONCLUSIONS: Outside clinical decision rules, decreasing levels of GCS are an important indicator for increasing risk of ciTBI, neurosurgery and death. The level of GCS should drive clinician decision-making in terms of urgency of neurosurgical consultation and possible transfer to a higher level of care.

Classification of Non-Severe Traumatic Brain Injury from Resting-State EEG Signal Using LSTM Network with ECOC-SVM.

Traumatic brain injury (TBI) is one of the common injuries when the human head receives an impact due to an accident or fall and is one of the most frequently submitted insurance claims. However, it is often always misused when individuals attempt an insurance fraud claim by providing false medical conditions. Therefore, there is a need for an instant brain condition classification system. This study presents a novel classification architecture that can classify non-severe TBI patients and healthy subjects employing resting-state electroencephalogram (EEG) as the input, solving the immobility issue of the computed tomography (CT) scan and magnetic resonance imaging (MRI). The proposed architecture makes use of long short term memory (LSTM) and error-correcting output coding support vector machine (ECOC-SVM) to perform multiclass classification. The pre-processed EEG time series are supplied to the network by each time step, where important information from the previous time step will be remembered by the LSTM cell. Activations from the LSTM cell is used to train an ECOC-SVM. The temporal advantages of the EEG were amplified and able to achieve a classification accuracy of 100%. The proposed method was compared to existing works in the literature, and it is shown that the proposed method is superior in terms of classification accuracy, sensitivity, specificity, and precision.

Mild, moderate and severe: terminology implications for clinical and experimental traumatic brain injury.

PURPOSE OF REVIEW: When describing clinical or experimental traumatic brain injury (TBI), the adjectives 'mild,' 'moderate' and 'severe' are misleading. 'Mild' clinical TBI frequently results in long-term disability. 'Severe' rodent TBI actually resembles mild or complicated mild clinical TBI. RECENT FINDINGS: Many mild TBI patients appear to have recovered completely but have postconcussive symptoms, deficits in cognitive and executive function and reduced cerebral blood flow. After moderate TBI, 31.8% of patients died or were discharged to skilled nursing or hospice. Among survivors of moderate and severe TBI, 44% were unable to return to work. On MRI, 88% of mild TBI patients have evidence of white matter damage, based on measurements of fractional anisotropy and mean diffusivity/apparent diffusion coefficient. After sports concussion, clinically recovered patients have abnormalities in functional connectivity on functional MRI. Methylphenidate improved fatigue and cognitive impairment and, combined with cognitive rehabilitation, improved memory and executive functioning. In comparison to clinical TB, because the entire spectrum of experimental rodent TBI, although defined as moderate or severe, more closely resembles mild or complicated mild clinical TBI. SUMMARY: Many patients after mild or moderate TBI suffer long-term sequelae and should be considered a major target for translational research. Treatments that improve outcome in rodent TBI, even when the experimental injuries are defined as severe, might be most applicable to mild or moderate TBI.

Machine-learning analysis outperforms conventional statistical models and CT classification systems in predicting 6-month outcomes in pediatric patients sustaining traumatic brain injury.

OBJECTIVEModern surgical planning and prognostication requires the most accurate outcomes data to practice evidence-based medicine. For clinicians treating children following traumatic brain injury (TBI) these data are severely lacking. The first aim of this study was to assess published CT classification systems in the authors' pediatric cohort. A pediatric-specific machine-learning algorithm called an artificial neural network (ANN) was then created that robustly outperformed traditional CT classification systems in predicting TBI outcomes in children.METHODSThe clinical records of children under the age of 18 who suffered a TBI and underwent head CT within 24 hours after TBI (n = 565) were retrospectively reviewed.RESULTS"Favorable" outcome (alive with Glasgow Outcome Scale [GOS] score ≥ 4 at 6 months postinjury, n = 533) and "unfavorable" outcome (death at 6 months or GOS score ≤ 3 at 6 months postinjury, n = 32) were used as the primary outcomes. The area under the receiver operating characteristic (ROC) curve (AUC) was used to delineate the strength of each CT grading system in predicting survival (Helsinki, 0.814; Rotterdam, 0.838; and Marshall, 0.781). The AUC for CT score in predicting GOS score ≤ 3, a measure of overall functionality, was similarly predictive (Helsinki, 0.717; Rotterdam, 0.748; and Marshall, 0.663). An ANN was then constructed that was able to predict 6-month outcomes with profound accuracy (AUC = 0.9462 ± 0.0422).CONCLUSIONSThis study showed that machine-learning can be leveraged to more accurately predict TBI outcomes in children.

A new hybrid classification system for traumatic brain injury which helps predict long-term consciousness: a single-center retrospective study.

BACKGROUND: To develop and validate a refined traumatic brain injury (TBI) classification system to supplement the existing systems which have limited accuracy for predicting long-term consciousness recovery. METHODS: The refined classification system was developed using medical records of 527 patients according to clinical presentations within 12-24 hrs after injury. Multiple linear regression was applied to identify protective and risk factors for Glasgow Coma Scale (GCS) and Glasgow Outcome Scale (GOS) score at 12-month follow-up. The TBI severity was moved to a less or more severe level when more than half of the protective or risk factors were present. The capability and reliability of each system for predicting 12 month GCS and GOS scores, and mortality were assessed using ROC curve analysis and Cronbach's Alpha reliability coefficient. RESULTS: One protective factor and four risk factors were identified for predicting long-term outcomes. The refined system had higher sensitivity and specificity in predicting 12-month GCS and GOS scores, and mortality than the other two systems. The refined system had lower reliability than the GCS system and higher reliability than the Chinese system. CONCLUSIONS: The refined system incorporates the advantages of both GCS and Chinese systems and provides a better prediction of long-term consciousness outcome.

The value of the identification of predisposing factors for post-traumatic amnesia in management of mild traumatic brain injury.

OBJECT: To identify the risk factors for post-traumatic amnesia (PTA) and to document the incidence of PTA after mild traumatic brain injuries. METHODS: This was a prospective study, affecting mild TBI (mTBI) (Glasgow Coma Scale 14-15) cases attending to the Emergency Department between January 2009 and April 2012 (40 months duration). Patients were divided into two groups (Group A: without PTA, and Group B: with PTA, and they were assessed according to the risk factors. RESULTS: A total of 1762 patients (males: 1002, 56.8%) were meeting study inclusion criteria [Group A: n = 1678 (83.8%), Group B: n = 84 (4.2%)]. Age, CT findings: (traumatic focal HCs in the frontal and temporal lobes or more diffuse punctate HCs, and skull base fractures), anticoagulation therapy and seizures were independent factors of PTA. There was no statistically significant correlation between PTA and sex, convexity fractures, stroke event, mechanism of mTBI (fall +/or beating), hypertension, coronary heart disease, chronic smokers and diabetes (p > 0.005). CONCLUSION: CT findings: (traumatic focal HCs in the frontal and temporal lobes or more diffuse punctate HCs and skull base fractures), age, seizures and anticoagulation/antiplatelet therapy, were independent factors of PTA and could be used as predictive factors after mTBI.

Abusive Head Trauma and Mortality-An Analysis From an International Comparative Effectiveness Study of Children With Severe Traumatic Brain Injury.

OBJECTIVES: Small series have suggested that outcomes after abusive head trauma are less favorable than after other injury mechanisms. We sought to determine the impact of abusive head trauma on mortality and identify factors that differentiate children with abusive head trauma from those with traumatic brain injury from other mechanisms. DESIGN: First 200 subjects from the Approaches and Decisions in Acute Pediatric Traumatic Brain Injury Trial-a comparative effectiveness study using an observational, cohort study design. SETTING: PICUs in tertiary children's hospitals in United States and abroad. PATIENTS: Consecutive children (age < 18 yr) with severe traumatic brain injury (Glasgow Coma Scale ≤ 8; intracranial pressure monitoring). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Demographics, injury-related scores, prehospital, and resuscitation events were analyzed. Children were dichotomized based on likelihood of abusive head trauma. A total of 190 children were included (n = 35 with abusive head trauma). Abusive head trauma subjects were younger (1.87 ± 0.32 vs 9.23 ± 0.39 yr; p < 0.001) and a greater proportion were female (54.3% vs 34.8%; p = 0.032). Abusive head trauma were more likely to 1) be transported from home (60.0% vs 33.5%; p < 0.001), 2) have apnea (34.3% vs 12.3%; p = 0.002), and 3) have seizures (28.6% vs 7.7%; p < 0.001) during prehospital care. Abusive head trauma had a higher prevalence of seizures during resuscitation (31.4 vs 9.7%; p = 0.002). After adjusting for covariates, there was no difference in mortality (abusive head trauma, 25.7% vs nonabusive head trauma, 18.7%; hazard ratio, 1.758; p = 0.60). A similar proportion died due to refractory intracranial hypertension in each group (abusive head trauma, 66.7% vs nonabusive head trauma, 69.0%). CONCLUSIONS: In this large, multicenter series, children with abusive head trauma had differences in prehospital and in-hospital secondary injuries which could have therapeutic implications. Unlike other traumatic brain injury populations in children, female predominance was seen in abusive head trauma in our cohort. Similar mortality rates and refractory intracranial pressure deaths suggest that children with severe abusive head trauma may benefit from therapies including invasive monitoring and adherence to evidence-based guidelines.

Development and Prospective Validation of Tools to Accurately Identify Neurosurgical and Critical Care Events in Children With Traumatic Brain Injury.

OBJECTIVE: To develop and validate case definitions (computable phenotypes) to accurately identify neurosurgical and critical care events in children with traumatic brain injury. DESIGN: Prospective observational cohort study, May 2013 to September 2015. SETTING: Two large U.S. children's hospitals with level 1 Pediatric Trauma Centers. PATIENTS: One hundred seventy-four children less than 18 years old admitted to an ICU after traumatic brain injury. MEASUREMENTS AND MAIN RESULTS: Prospective data were linked to database codes for each patient. The outcomes were prospectively identified acute traumatic brain injury, intracranial pressure monitor placement, craniotomy or craniectomy, vascular catheter placement, invasive mechanical ventilation, and new gastrostomy tube or tracheostomy placement. Candidate predictors were database codes present in administrative, billing, or trauma registry data. For each clinical event, we developed and validated penalized regression and Boolean classifiers (models to identify clinical events that take database codes as predictors). We externally validated the best model for each clinical event. The primary model performance measure was accuracy, the percent of test patients correctly classified. The cohort included 174 children who required ICU admission after traumatic brain injury. Simple Boolean classifiers were greater than or equal to 94% accurate for seven of nine clinical diagnoses and events. For central venous catheter placement, no classifier achieved 90% accuracy. Classifier accuracy was dependent on available data fields. Five of nine classifiers were acceptably accurate using only administrative data but three required trauma registry fields and two required billing data. CONCLUSIONS: In children with traumatic brain injury, computable phenotypes based on simple Boolean classifiers were highly accurate for most neurosurgical and critical care diagnoses and events. The computable phenotypes we developed and validated can be used in any observational study of children with traumatic brain injury and can reasonably be applied in studies of these interventions in other patient populations.

Cross-Validation of a Classification System for Persons With Traumatic Brain Injury in the Posthospital Period.

OBJECTIVE: To (1) identify groupings of persons with traumatic brain injury (TBI) in the posthospital period in a cohort recruited in Australia; (2) compare groupings from the Australian cohort to groupings previously developed for a US cohort. SETTING: Rehabilitation centers in the US and Australia. PARTICIPANTS: A total of 170 persons with TBI from Australia and 504 persons with TBI from the United States. Participants were aged 18 to 64 years, greater than 6 months postinjury, had capacity to give consent, and had definitive contemporaneous medical evidence of TBI. DESIGN: Observational study. MAIN MEASURES: Cognitive tests-Wechsler Letter-Number Sequencing and Coding, Rey Auditory Verbal Learning Test, Trail Making Test, Verbal Fluency. Questionnaires-9 scales from the Traumatic Brain Injury Quality-of-Life system; Neurobehavioral Symptom Inventory; Economic Quality of Life, Family Assessment Device-General Functioning. Performance validity-Word Memory Test. RESULTS: Agreement in classification for the 2 samples was only moderate with 63.5% correctly classified and Cohen's κ = 0.53. A post hoc analysis placing all persons showing poor performance validity in the same group improved classification to 73% and Cohen's κ = 0.65 indicating substantial agreement. CONCLUSION: Results provided support for the patient groups developed for the US sample and indicate that these groupings largely replicated in a new cohort.

Groupings of Persons With Traumatic Brain Injury: A New Approach to Classifying Traumatic Brain Injury in the Post-Acute Period.

OBJECTIVE: To (1) identify groups of persons with traumatic brain injury (TBI) who differ on 12 dimensions of cognitive function: cognitive, emotional, and physical symptoms; personal strengths; physical functioning; environmental supports; and performance validity; and (2) describe patterns of differences among the groups on these dimensions and on participation outcome. SETTING: Three centers for rehabilitation of persons with TBI. PARTICIPANTS: A total of 504 persons with TBI living in the community who were an average (standard deviation) of 6.3 (6.8) years postinjury and who had capacity to give consent, could be interviewed and tested in English, and were able to participate in an assessment lasting up to 4 hours. DESIGN: Observational study of a convenience sample of persons with TBI. MAIN MEASURES: Selected scales from the Traumatic Brain Injury Quality of Life measures, Neurobehavioral Symptom Inventory, Economic Quality of Life Scale, Family Assessment Device General Functioning Scale, measures of cognitive function, Word Memory Test, and Participation Assessment with Recombined Tools-Objective (PART-O) scale. RESULTS: Cluster analysis identified 5 groups of persons with TBI who differed in clinically meaningful ways on the 12 dimension scores and the PART-O scale. CONCLUSION: Cluster groupings identified in this study could assist clinicians with case conceptualization and treatment planning.

Brain Injury Vision Symptom Survey (BIVSS) Questionnaire.

PURPOSE: Validation of the Brain Injury Vision Symptom Survey (BIVSS), a self-administered survey for vision symptoms related to traumatic brain injury (TBI). METHODS: A 28-item vision symptom questionnaire was completed by 107 adult subjects (mean age 42.1, 16.2 SD, range 18-75) who self-reported as having sustained mild-to-moderate TBI and two groups of reference adult subjects (first-year optometry students: mean age 23.2, 2.8 SD, range 20-39; and 71 third-year optometry students: mean age 26.0, 2.9 SD, range 22-42) without TBI. Both a Likert-style method of analysis with factor analysis and a Rasch analysis were used. Logistic regression was used to determine sensitivity and specificity. RESULTS: At least 27 of 28 questions were completed by 93.5% of TBI subjects, and all 28 items were completed by all of the 157 reference subjects. BIVSS sensitivity was 82.2% for correctly predicting TBI and 90.4% for correctly predicting the optometry students. Factor analysis identified eight latent variables; six factors were positive in their risk for TBI. Other than dry eye and double vision, the TBI patients were significantly more symptomatic than either cohort of optometry students by at least one standard deviation (p < 0.001). Twenty-five of 28 questions were within limits for creating a single-dimension Rasch scale. CONCLUSIONS: Nearly all of the adult TBI subjects were able to self-complete the BIVSS, and there was significant mean score separation between TBI and non-TBI groups. The Rasch analysis revealed a single dimension associated with TBI. Using the Likert method with the BIVSS, it may be possible to identify different vision symptom profiles with TBI patients. The BIVSS seems to be a promising tool for better understanding the complex and diverse nature of vision symptoms that are associated with brain injury.

[Pathophysiology of intracranial injuries]. / Pathophysiologie intrakranieller Verletzungen.

Traumatic brain injury (TBI) constitutes a heterogeneous condition that affects the most complex organ of the human body. It is commonly classified by its location as focal injury (e.g. epidural hematoma) and diffuse injury (e.g. diffuse axonal shearing injury) as well as by primary and secondary tissue injury. Accordingly, direct mechanical force causes the primary insult. The tissue damage occurring afterwards is subsumed under the term secondary brain damage. Some of these processes are overlapping and include in the early phase local cerebral ischemia resulting in excitotoxicity, which together with the triggered neuroinflammatory cascade causes the formation of cerebral edema and ultimately increased intracranial pressure once the intracranial compliance is exhausted. In survivors the long-term sequelae of the late stage include seizures caused by synaptic reorganization (incidence depending on the severity of TBI), persistent neuroinflammation promoting further neurodegeneration and increased risk for Alzheimer's disease probably because of TBI-related protein misfolding (tauopathy). Acute phase biomarkers of TBI should ideally originate from the injured brain. They should help distinguish disease severity and predict morbidity and mortality; however, the most commonly used biomarkers (S-100ß and neurone-specific enolase) show a low specificity. In theory their successors (i. e. GFAP, pNF-H) seem more specific; however, these "new kids on the block" still need to be thoroughly investigated in large scale studies.

Moderate Traumatic Brain Injury: The Grey Zone of Neurotrauma.

Moderate traumatic brain injury (MTBI) is poorly defined in the literature and the nomenclature "moderate" is misleading, because up to 15 % of such patients may die. MTBI is a heterogeneous entity that shares many aspects of its pathophysiology and management with severe traumatic brain injury. Many patients who ''talk and died'' are MTBI. The role of neuroimaging is essential for the proper management of these patients. To analyze all aspects of the pathophysiology and management of MTBI, proposing a new way to categorize it considering the clinical picture and neuroimaging findings. We proposed a different approach to the group of patients with Glasgow Coma Scale (GCS) ranging from 9 through 13 and we discuss the rationale for this proposal. Patients with lower GCS scores (9-10), especially those with significant space-occupying lesions on the CT scan, should be managed following the guidelines for severe traumatic brain injury, with ICU observation, frequent serial computed tomography (CT) scanning and ICP monitoring. On the other hand, those with higher range GCS (11-13) can be managed more conservatively with serial neurological examination and CT scans. Given the available evidence, MTBI is an entity that needs reclassification. Large-scale and well-designed studies are urgently needed.

Moderate Traumatic Brain Injury in Adult Population: The Latin American Brain Injury Consortium Consensus for Definition and Categorization.

Moderate traumatic brain injury (TBI) is a diagnosis that describes diverse patients with heterogeneity of primary injuries. Defined by a Glasgow Coma Scale between 9 and 12, this category includes patients who may neurologically worsen and require increasing intensive care resources and/or emergency neurosurgery. Despite the unique characteristics of these patients, there have not been specific guidelines published before this effort to support decision-making in these patients. A Delphi consensus group from the Latin American Brain Injury Consortium was established to generate recommendations related to the definition and categorization of moderate TBI. Before an in-person meeting, a systematic review of the literature was performed identifying evidence relevant to planned topics. Blinded voting assessed support for each recommendation. A priori the threshold for consensus was set at 80% agreement. Nine PICOT questions were generated by the panel, including definition, categorization, grouping, and diagnosis of moderate TBI. Here, we report the results of our work including relevant consensus statements and discussion for each question. Moderate TBI is an entity for which there is little published evidence available supporting definition, diagnosis, and management. Recommendations based on experts' opinion were informed by available evidence and aim to refine the definition and categorization of moderate TBI. Further studies evaluating the impact of these recommendations will be required.

Comparative Performance of Three Eye-Tracking Devices in Detection of Mild Traumatic Brain Injury in Acute Versus Chronic Subject Populations.

INTRODUCTION: Presently, traumatic brain injury (TBI) triage in field settings relies on symptom-based screening tools such as the updated Military Acute Concussion Evaluation. Objective eye-tracking may provide an alternative means of neurotrauma screening due to sensitivity to neurotrauma brain-health changes. Previously, the US Army Medical Research and Development Command Non-Invasive NeuroAssessment Devices (NINAD) Integrated Product Team identified 3 commercially available eye-tracking devices (SyncThink EYE-SYNC, Oculogica EyeBOX, NeuroKinetics IPAS) as meeting criteria toward being operationally effective in the detection of TBI in service members. We compared these devices to assess their relative performance in the classification of mild traumatic brain injury (mTBI) subjects versus normal healthy controls. MATERIALS AND METHODS: Participants 18 to 45 years of age were assigned to Acute mTBI, Chronic mTBI, or Control group per study criteria. Each completed a TBI assessment protocol with all 3 devices counterbalanced across participants. Acute mTBI participants were tested within 72 hours following injury whereas time since last injury for the Chronic mTBI group ranged from months to years. Discriminant analysis was undertaken to determine device classification performance in separating TBI subjects from controls. Area Under the Curves (AUCs) were calculated and used to compare the accuracy of device performance. Device-related factors including data quality, the need to repeat tests, and technical issues experienced were aggregated for reporting. RESULTS: A total of 63 participants were recruited as Acute mTBI subjects, 34 as Chronic mTBI subjects, and 119 participants without history of TBI as controls. To maximize outcomes, poorer quality data were excluded from analysis using specific criteria where possible. Final analysis utilized 49 (43 male/6 female, mean [x̅] age = 24.3 years, SD [s] = 5.1) Acute mTBI subjects, and 34 (33 male/1 female, x̅ age = 38.8 years, s = 3.9) Chronic mTBI subjects were age- and gender-matched as closely as possible with Control subjects. AUCs obtained with 80% of total dataset ranged from 0.690 to 0.950 for the Acute Group and from 0.753 to 0.811 for the Chronic mTBI group. Validation with the remaining 20% of dataset produced AUCs ranging from 0.600 to 0.750 for Acute mTBI group and 0.490 to 0.571 for the Chronic mTBI group. CONCLUSIONS: Potential eye-tracking detection of mTBI, per training model outcomes, ranged from acceptable to excellent for the Acute mTBI group; however, it was less consistent for the Chronic mTBI group. The self-imposed targeted performance (AUC of 0.850) appears achievable, but further device improvements and research are necessary. Discriminant analysis models differed for the Acute versus Chronic mTBI groups, suggesting performance differences in eye-tracking. Although eye-tracking demonstrated sensitivity in the Chronic group, a more rigorous and/or longitudinal study design is required to evaluate this observation. mTBI injuries were not controlled for this study, potentially reducing eye-tracking assessment sensitivity. Overall, these findings indicate that while eye-tracking remains a viable means of mTBI screening, device-specific variability in data quality, length of testing, and ease of use must be addressed to achieve NINAD objectives and DoD implementation.

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.