Predicting outcome after traumatic brain injury

Settlement Is at the End-Common Trauma Scores Require a Critical Reassessment Due to the Possible Dynamics of Traumatic Brain Injuries in Patients' Clinical Course

Background: Scientific studies on severely injured patients commonly utilize the Abbreviated Injury Scale (AIS) and the Injury Severity Score (ISS) for injury assessment and to characterize trauma cohorts. However, due to potential deterioration (e.g., in the case of an increasing hemorrhage) during the clinical course, the assessment of injury severity in traumatic brain injury (TBI) can be challenging. Therefore, the aim of this study was to investigate whether and to what extent the worsening of TBI affects the AIS and ISS. Methods: We retrospectively evaluated 80 polytrauma patients admitted to the trauma room of our level I trauma center with computed-tomography-confirmed TBI. The initial AIS, ISS, and Trauma and Injury Severity Score (TRISS) values were reevaluated after follow-up imaging. Results: A total of 37.5% of the patients showed a significant increase in AIShead (3.7 vs. 4.1; p = 0.002) and the ISS (22.9 vs. 26.7, p = 0.0497). These changes resulted in an eight percent reduction in their TRISS-predicted survival probability (74.82% vs. 66.25%, p = 0.1835). Conclusions: The dynamic nature of intracranial hemorrhage complicates accurate injury severity assessment using the AIS and ISS, necessitating consideration in clinical studies and registries to prevent systematic bias in patient selection and subsequent data analysis.

Patient-report and caregiver-report measures of rehabilitation service use following acquired brain injury: a systematic review

OBJECTIVE

To review patient-report/caregiver-report measures of rehabilitation service use following acquired brain injury (ABI).

DATA SOURCES

Medline, APA PsycINFO, Embase and CINAHL were searched on November 2021 and November 2022. Authors were contacted if measures were not included in manuscripts/appendices.

STUDY SELECTION

Included articles were empirical research or a research protocol, available in English and described measures of patient report/caregiver report of rehabilitation service use post-ABI via quantitative or qualitative methods. Two reviewers independently screened 5290 records using DistillerSR. Discrepancies were resolved by team adjudication.

DATA EXTRACTION

Data extraction was piloted with high levels of agreement (k=.94). Data were extracted by a single member with team meetings to seek guidance as needed. Data included administration characteristics (reporter, mode of administration, recall period), psychometric evidence and dimensions assessed (types of services, setting, frequency, duration, intensity, qualitative aspects).

DATA SYNTHESIS

One hundred and fifty-two measures were identified from 85 quantitative, 56 qualitative and 3 psychometric studies. Psychometric properties were reported for four measures, all of which focused on satisfaction. Most measures inquired about the type of rehabilitation services used, with more than half assessing functional (eg, physical therapy) and behavioural health rehabilitation services, but fewer than half assessing community and academic reintegration (eg, special education, vocational rehabilitation) or cognitive (eg, neuropsychology) services. Fewer than half assessed qualitative aspects (eg, satisfaction). Recall periods ranged from 1 month to 'since the ABI event' or focused on current use. Of measures that could be accessed (n=71), many included a limited checklist of types of services used. Very few measures assessed setting, frequency, intensity or duration.

CONCLUSIONS

Despite widespread interest, the vast majority of measures have not been validated and are limited in scope. Use of gold-standard psychometric methods to develop and validate a comprehensive patient-report/caregiver-report measure of rehabilitation service use would have wide-ranging implications for improving rehabilitation research in ABI.

Pediatric Traumatic Brain Injury: Impact on the Developing Brain

Traumatic brain injury (TBI) is a serious public health concern impacting millions of children and adolescents each year. Experiencing a brain injury during key critical periods of brain development can affect the normal formation of brain networks that are responsible for a range of complex neurocognitive outcomes. In addition, there are multiple pre- and postinjury factors that influence the trajectory of recovery and outcomes. In this review, we will focus on the current state of the literature within pediatric TBI; systematically review the available research on developmental aspects of TBI in children, focusing on the pathophysiology of the injury and its impact on the developing brain; and highlight knowledge gaps for further exploration.

Communication and Psychosocial Outcomes 2-Years After Severe Traumatic Brain Injury: Development of a Prognostic Model

OBJECTIVE

To examine predictive factors underlying communication and psychosocial outcomes at 2 years post-injury. Prognosis of communication and psychosocial outcomes after severe traumatic brain injury (TBI) is largely unknown yet is relevant for clinical service provision, resource allocation, and managing patient and family expectations for recovery.

DESIGN

A prospective longitudinal inception design was employed with assessments at 3 months, 6 months, and 2 years.

PARTICIPANTS

The cohort included 57 participants with severe TBI (N=57).

SETTING

Subacute and post-acute rehabilitation.

MAIN OUTCOME MEASURES

Preinjury/injury measures included age, sex, education years, Glasgow Coma Scale, and PTA. The 3-month and 6-month data points included speech, language, and communication measures across the ICF domains and measures of cognition. The 2-year outcome measures included conversation, perceived communication skills, and psychosocial functioning. Predictors were examined using multiple regression.

INTERVENTIONS

Not applicable.

RESULTS

The cognitive and communication measures at 6 months significantly predicted conversation measures at 2 years and psychosocial functioning as reported by others at 2 years. At 6 months, 69% of participants presented with a cognitive-communication disorder (Functional Assessment of Verbal Reasoning and Executive Strategies [FAVRES]). The unique variance accounted for by the FAVRES measure was 7% for conversation measures and 9% for psychosocial functioning. Psychosocial functioning at 2 years was also predicted by pre-injury/injury factors and 3-month communication measures. Pre-injury education level was a unique predictor, accounting for 17% of the variance, and processing speed/memory at 3 months uniquely accounted for 14% of the variance.

CONCLUSION

Cognitive-communication skills at 6 months are a potent predictor of persisting communication challenges and poor psychosocial outcomes up to 2 years after a severe TBI. Findings emphasize the importance of addressing modifiable cognitive and communication outcomes variables during the first 2 years after severe TBI to maximize functional patient outcomes.

Outcomes and associated factors of traumatic brain injury among adult patients treated in Amhara regional state comprehensive specialized hospitals

BACKGROUND

Globally, traumatic brain injury is the leading cause of death and disability which affects more than 69 million individuals a year.

OBJECTIVE

This study aimed to assess the outcome and associated factors of traumatic brain injury among adult patients treated in Amhara regional state comprehensive specialized hospitals.

METHOD

Institutional-based cross-sectional study design was conducted from January 1, 2018, to December 30, 2020. A simple random sampling technique was used and a checklist was used to extract data between March 15 and April 15, 2021. The data were entered into Epi-data version 4.2 and exported to SPSS version 25 for analysis after being checked for consistency. Associated variables with outcomes of traumatic brain injury were determined by a binary logistic regression model. The degree of association was interpreted by using AOR and a 95% confidence interval with a p-value less than or equal to 0.05 at 95% CI was considered statistically significant.

RESULT

In this study road traffic injury was the most frequent cause of traumatic brain injuries among adult patients, accounting for 181 (37.5%), followed by assault, accounting for 117 (24.2%) which affects adult age groups. One-third of the participant had a moderate Glasgow coma scale of 174(36%). Only 128(26.8%) patients arrived within one hour. One hundred sixty, 160 (33.1%) of patients had a mild traumatic brain injury, whereas, 149(36%) of patients had a severe traumatic brain injury. Regarding computerized tomography scans findings, the hematoma was the most common (n = 163, 33.7%). Ninety-one, 91(18.8%) of participants had cerebrospinal fluid otorrhea, and, 92(19%) were diagnosed with a positive battle sign. The overall prevalence of unfavorable outcomes after traumatic brain injury was found to be 35.2% (95%CI (30.8-39.1). Having additional Injury, hypoxia, time to hospital presentation after 24 h, severe Glasgow Coma Scale, moderate Glasgow Coma Scale, tachypnea, bradypnea, and cerebrospinal fluid Othorrhea, were factors associated with unfavorable outcomes.

CONCLUSION AND RECOMMENDATION

In this study, the overall unfavorable outcome was experienced by about four out of every 10 victims of traumatic brain injury. Time of arrival > 24 h, low Glasgow coma scale, additional injury, Cerebrospinal fluid otorrhea, abnormal respiration, and hypoxia were significant predictors of unfavorable outcomes. To reduce the adverse effects of traumatic brain injury in adults, it is therefore desirable to guarantee safe road traffic flow and improve health care services.

PREdiction and Diagnosis using Imaging and Clinical biomarkers Trial in Traumatic Brain Injury (PREDICT-TBI) study protocol: an observational, prospective, multicentre cohort study for the prediction of outcome in moderate-to-severe TBI

INTRODUCTION

Traumatic brain injury (TBI) is a heterogeneous condition with a broad spectrum of injury severity, pathophysiological processes and variable outcomes. For moderate-to-severe TBI survivors, recovery is often protracted and outcomes can range from total dependence to full recovery. Despite advances in medical treatment options, prognosis remains largely unchanged. The objective of this study is to develop a machine learning predictive model for neurological outcomes at 6 months in patients with a moderate-to-severe TBI, incorporating longitudinal clinical, multimodal neuroimaging and blood biomarker predictor variables.

METHODS AND ANALYSIS

A prospective, observational, cohort study will enrol 300 patients with moderate-to-severe TBI from seven Australian hospitals over 3 years. Candidate predictors including demographic and general health variables, and longitudinal clinical, neuroimaging (CT and MRI), blood biomarker and patient-reported outcome measures will be collected at multiple time points within the acute phase of injury. The predictor variables will populate novel machine learning models to predict the Glasgow Outcome Scale Extended 6 months after injury. The study will also expand on current prognostic models by including novel blood biomarkers (circulating cell-free DNA), and the results of quantitative neuroimaging such as Quantitative Susceptibility Mapping and Dynamic Contrast Enhanced MRI as predictor variables.

ETHICS AND DISSEMINATION

Ethical approval has been obtained by the Royal Brisbane and Women's Hospital Human Research Ethics Committee, Queensland. Participants or their substitute decision-maker/s will receive oral and written information about the study before providing written informed consent. Study findings will be disseminated by peer-review publications and presented at national and international conferences and clinical networks.

TRIAL REGISTRATION NUMBER

ACTRN12620001360909.

Predicting Outcome in Patients with Brain Injury: Differences between Machine Learning versus Conventional Statistics

Defining reliable tools for early prediction of outcome is the main target for physicians to guide care decisions in patients with brain injury. The application of machine learning (ML) is rapidly increasing in this field of study, but with a poor translation to clinical practice. This is basically dependent on the uncertainty about the advantages of this novel technique with respect to traditional approaches. In this review we address the main differences between ML techniques and traditional statistics (such as logistic regression, LR) applied for predicting outcome in patients with stroke and traumatic brain injury (TBI). Thirteen papers directly addressing the different performance among ML and LR methods were included in this review. Basically, ML algorithms do not outperform traditional regression approaches for outcome prediction in brain injury. Better performance of specific ML algorithms (such as Artificial neural networks) was mainly described in the stroke domain, but the high heterogeneity in features extracted from low-dimensional clinical data reduces the enthusiasm for applying this powerful method in clinical practice. To better capture and predict the dynamic changes in patients with brain injury during intensive care courses ML algorithms should be extended to high-dimensional data extracted from neuroimaging (structural and fMRI), EEG and genetics.

Prognostic value of day-of-injury plasma GFAP and UCH-L1 concentrations for predicting functional recovery after traumatic brain injury in patients from the US TRACK-TBI cohort: an observational cohort study

BACKGROUND

The prognostic value of glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase L1 (UCH-L1) as day-of-injury predictors of functional outcome after traumatic brain injury is not well understood. GFAP is a protein found in glial cells and UCH-L1 is found in neurons, and these biomarkers have been cleared to aid in decision making regarding whether brain CT should be performed after traumatic brain injury. We aimed to quantify their prognostic accuracy and investigate whether these biomarkers contribute novel prognostic information to existing clinical models.

METHODS

We enrolled patients from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) observational cohort study. TRACK-TBI includes patients 17 years and older who are evaluated for TBI at 18 US level 1 trauma centres. All patients receive head CT at evaluation, have adequate visual acuity and hearing preinjury, and are fluent in either English or Spanish. In our analysis, we included participants aged 17-90 years who had day-of-injury plasma samples for measurement of GFAP and UCH-L1 and completed 6-month assessments for outcome due to traumatic brain injury with the Glasgow Outcome Scale-Extended (GOSE-TBI). Biomarkers were analysed as continuous variables and in quintiles. This study is registered with ClinicalTrials.gov, NCT02119182.

FINDINGS

We enrolled 2552 patients from Feb 26, 2014, to Aug 8, 2018. Of the 1696 participants with brain injury and data available at baseline and at 6 months who were included in the analysis, 120 (7·1%) died (GOSE-TBI=1), 235 (13·9%) had an unfavourable outcome (ie, GOSE-TBI ≤4), 1135 (66·9%) had incomplete recovery (ie, GOSE-TBI <8), and 561 (33·1%) recovered fully (ie, GOSE-TBI=8). The area under the curve (AUC) of GFAP for predicting death at 6 months in all patients was 0·87 (95% CI 0·83-0·91), for unfavourable outcome was 0·86 (0·83-0·89), and for incomplete recovery was 0·62 (0·59-0·64). The corresponding AUCs for UCH-L1 were 0·89 (95% CI 0·86-0·92) for predicting death, 0·86 (0·84-0·89) for unfavourable outcome, and 0·61 (0·59-0·64) for incomplete recovery at 6 months. AUCs were higher for participants with traumatic brain injury and Glasgow Coma Scale (GCS) score of 3-12 than for those with GCS score of 13-15. Among participants with GCS score of 3-12 (n=353), adding GFAP and UCH-L1 (alone or combined) to each of the three International Mission for Prognosis and Analysis of Clinical Trials in traumatic brain injury models significantly increased their AUCs for predicting death (AUC range 0·90-0·94) and unfavourable outcome (AUC range 0·83-0·89). However, among participants with GCS score of 13-15 (n=1297), adding GFAP and UCH-L1 to the UPFRONT study model modestly increased the AUC for predicting incomplete recovery (AUC range 0·69-0·69, p=0·025).

INTERPRETATION

In addition to their known diagnostic value, day-of-injury GFAP and UCH-L1 plasma concentrations have good to excellent prognostic value for predicting death and unfavourable outcome, but not for predicting incomplete recovery at 6 months. These biomarkers contribute the most prognostic information for participants presenting with a GCS score of 3-12.

FUNDING

US National Institutes of Health, National Institute of Neurologic Disorders and Stroke, US Department of Defense, One Mind, US Army Medical Research and Development Command.

Dynamic prediction of mortality after traumatic brain injury using a machine learning algorithm

Intensive care for patients with traumatic brain injury (TBI) aims to optimize intracranial pressure (ICP) and cerebral perfusion pressure (CPP). The transformation of ICP and CPP time-series data into a dynamic prediction model could aid clinicians to make more data-driven treatment decisions. We retrained and externally validated a machine learning model to dynamically predict the risk of mortality in patients with TBI. Retraining was done in 686 patients with 62,000 h of data and validation was done in two international cohorts including 638 patients with 60,000 h of data. The area under the receiver operating characteristic curve increased with time to 0.79 and 0.73 and the precision recall curve increased with time to 0.57 and 0.64 in the Swedish and American validation cohorts, respectively. The rate of false positives decreased to ≤2.5%. The algorithm provides dynamic mortality predictions during intensive care that improved with increasing data and may have a role as a clinical decision support tool.

Serum metabolome associated with severity of acute traumatic brain injury

Complex metabolic disruption is a crucial aspect of the pathophysiology of traumatic brain injury (TBI). Associations between this and systemic metabolism and their potential prognostic value are poorly understood. Here, we aimed to describe the serum metabolome (including lipidome) associated with acute TBI within 24 h post-injury, and its relationship to severity of injury and patient outcome. We performed a comprehensive metabolomics study in a cohort of 716 patients with TBI and non-TBI reference patients (orthopedic, internal medicine, and other neurological patients) from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) cohort. We identified panels of metabolites specifically associated with TBI severity and patient outcomes. Choline phospholipids (lysophosphatidylcholines, ether phosphatidylcholines and sphingomyelins) were inversely associated with TBI severity and were among the strongest predictors of TBI patient outcomes, which was further confirmed in a separate validation dataset of 558 patients. The observed metabolic patterns may reflect different pathophysiological mechanisms, including protective changes of systemic lipid metabolism aiming to maintain lipid homeostasis in the brain.

Development and Validation of a Functionally Relevant Comorbid Health Index in Adults Admitted to Inpatient Rehabilitation for Traumatic Brain Injury

Several studies have characterized comorbidities among individuals with traumatic brain injury (TBI); however, there are few validated TBI comorbidity indices. Widely used indices (e.g., Elixhauser Comorbidity Index [ECI]) were developed in other patient populations and anchor to mortality or healthcare utilization, not functioning, and notably exclude conditions known to co-occur with TBI. The objectives of this study were to develop and validate a functionally relevant TBI comorbidity index (Fx-TBI-CI) and to compare prognostication of the Fx-TBI-CI with the ECI. We used data from the eRehabData database to divide the sample randomly into a training sample (N = 21,292) and an internal validation sample (N = 9166). We used data from the TBI Model Systems National Database as an external validation sample (N = 1925). We used least absolute shrinkage and selection operator (LASSO) regression to narrow the list of functionally relevant conditions from 39 to 12. In internal validation, the Fx-TBI-CI explained 14.1% incremental variance over an age and sex model predicting the Functional Independence Measure (FIM) Motor subscale at inpatient rehabilitation discharge, compared with 2.4% explained by the ECI. In external validation, the Fx-TBI-CI explained 4.9% incremental variance over age and sex and 3.8% over age, sex, and Glasgow Coma Scale score,compared with 2.1% and 1.6% incremental variance, respectively, explained by the ECI. An unweighted Sum Condition Score including the same conditions as the Fx-TBI-CI conferred similar prognostication. Although the Fx-TBI-CI had only modest incremental variance over demographics and injury severity in predicting functioning in external validation, the Fx-TBI-CI outperformed the ECI in predicting post-TBI function.

Moderators of gene-outcome associations following traumatic brain injury

The field of genomics is the principal avenue in the ongoing development of precision/personalised medicine for a variety of health conditions. However, relating genes to outcomes is notoriously complex, especially when considering that other variables can change, or moderate, gene-outcome associations. Here, we comprehensively discuss moderation of gene-outcome associations in the context of traumatic brain injury (TBI), a common, chronically debilitating, and costly neurological condition that is under complex polygenic influence. We focus our narrative review on single nucleotide polymorphisms (SNPs) of three of the most studied genes (apolipoprotein E, brain-derived neurotrophic factor, and catechol-O-methyltransferase) and on three demographic variables believed to moderate associations between these SNPs and TBI outcomes (age, biological sex, and ethnicity). We speculate on the mechanisms which may underlie these moderating effects, drawing widely from biomolecular and behavioural research (n = 175 scientific reports) within the TBI population (n = 72) and other neurological, healthy, ageing, and psychiatric populations (n = 103). We conclude with methodological recommendations for improved exploration of moderators in future genetics research in TBI and other populations.

Acute Brain-Derived Neurotrophic Factor DNA Methylation Trajectories in Cerebrospinal Fluid and Associations With Outcomes Following Severe Traumatic Brain Injury in Adults

Background. Epigenetic biomarkers have the potential to explain outcome heterogeneity following traumatic brain injury (TBI) but are largely unexplored. Objective. This exploratory pilot study characterized brain-derived neurotrophic factor (BDNF) DNA methylation trajectories following severe TBI. Methods. Brain-derived neurotrophic factor DNA methylation trajectories in cerebrospinal fluid (CSF) over the first 5 days following severe TBI in 112 adults were examined in association with 3- and 12-month outcomes. Results. Group-based trajectory analysis revealed low and high DNA methylation groups at two BDNF cytosine-phosphate-guanine (CpG) targets that showed suggestive associations (P < .05) with outcomes. Membership in the high DNA methylation groups was associated with better outcomes after controlling for age, sex, and injury severity. Associations of age × trajectory group interactions with outcomes at a third CpG site revealed a pattern of the same or better outcomes with higher ages in the high DNA methylation group and worse outcomes with higher ages in the low DNA methylation group. Conclusions. Although no observed associations met the empirical significance threshold after correcting for multiple comparisons, suggestive associations of the main effect models were consistent in their direction of effect and were observed across two CpG sites and two outcome time points. Results suggest that higher acute CSF BDNF DNA methylation may promote recovery following severe TBI in adults, and this effect may be more robust with higher age. While the results require replication in larger and racially diverse independent samples, BDNF DNA methylation may serve as an early postinjury biomarker helping to explain outcome heterogeneity following TBI.

Epidemiology of Traumatic Brain Injury in Europe: A Living Systematic Review

This systematic review provides a comprehensive, up-to-date summary of traumatic brain injury (TBI) epidemiology in Europe, describing incidence, mortality, age, and sex distribution, plus severity, mechanism of injury, and time trends. PubMed, CINAHL, EMBASE, and Web of Science were searched in January 2015 for observational, descriptive, English language studies reporting incidence, mortality, or case fatality of TBI in Europe. There were no limitations according to date, age, or TBI severity. Methodological quality was assessed using the Methodological Evaluation of Observational Research checklist. Data were presented narratively. Sixty-six studies were included in the review. Country-level data were provided in 22 studies, regional population or treatment center catchment area data were reported by 44 studies. Crude incidence rates varied widely. For all ages and TBI severities, crude incidence rates ranged from 47.3 per 100,000, to 694 per 100,000 population per year (country-level studies) and 83.3 per 100,000, to 849 per 100,000 population per year (regional-level studies). Crude mortality rates ranged from 9 to 28.10 per 100,000 population per year (country-level studies), and 3.3 to 24.4 per 100,000 population per year (regional-level studies.) The most common mechanisms of injury were traffic accidents and falls. Over time, the contribution of traffic accidents to total TBI events may be reducing. Case ascertainment and definitions of TBI are variable. Improved standardization would enable more accurate comparisons.

Disability Rating Scale in the First Few Weeks After a Severe Traumatic Brain Injury as a Predictor of 6-Month Functional Outcome

BACKGROUND

An early acute marker of long-term neurological outcome would be useful to help guide clinical decision making and therapeutic effectiveness after severe traumatic brain injury (TBI). We investigated the utility of the Disability Rating Scale (DRS) as early as 1 wk after TBI as a predictor of favorable 6-mo Glasgow Outcome Scale extended (GOS-E).

OBJECTIVE

To determine the predictability of a favorable 6-mo GOS-E using the DRS measured during weeks 1 to 4 of injury.

METHODS

The study is a sub analysis of patients enrolled in the Epo Severe TBI Trial (n = 200) to train and validate L1-regularized logistic regression models. DRS was collected at weeks 1 to 4 and GOS-E at 6 mo.

RESULTS

The average area under the receiver operating characteristic curve was 0.82 for the model with baseline demographic and injury severity variables and week 1 DRS and increased to 0.88 when including weekly DRS until week 4.

CONCLUSION

This study suggests that week 1 to 4 DRS may be predictors of favorable 6-mo outcome in severe TBI patients and thus useful both for clinical prognostication as well as surrogate endpoints for adaptive clinical trials.

Assessing the Severity of Traumatic Brain Injury-Time for a Change?

Traumatic brain injury (TBI) has been described to be man's most complex disease, in man's most complex organ. Despite this vast complexity, variability, and individuality, we still classify the severity of TBI based on non-specific, often unreliable, and pathophysiologically poorly understood measures. Current classifications are primarily based on clinical evaluations, which are non-specific and poorly predictive of long-term disability. Brain imaging results have also been used, yet there are multiple ways of doing brain imaging, at different timepoints in this very dynamic injury. Severity itself is a vague concept. All prediction models based on combining variables that can be assessed during the acute phase have reached only modest predictive values for later outcome. Yet, these early labels of severity often determine how the patient is treated by the healthcare system at large. This opinion paper examines the problems and provides caveats regarding the use of current severity labels and the many practical and scientific issues that arise from doing so. The objective of this paper is to show the causes and consequences of current practice and propose a new approach based on risk classification. A new approach based on multimodal quantifiable data (including imaging and biomarkers) and risk-labels would be of benefit both for the patients and for TBI clinical research and should be a priority for international efforts in the field.

Antibodies against the pituitary and hypothalamus in boxers

Traumatic brain injury (TBI), a growing public health problem worldwide, has recently been recognized as one of the leading causes of hypopituitarism. The main causes of TBI-induced pituitary dysfunction are car accidents, falls, violence, sports-related brain injury, and war accidents, including blast-related brain injuries. Car accidents and falls are the most common causes of TBI and pituitary dysfunction among the younger generation and elderly population, respectively. The prevalence of hypopituitarism after TBI is about 30%. GH is the most common hormone lost. The mechanisms underlying hypopituitarism are still unclear; however, recent studies have demonstrated that hypoxic insult, increased intracranial pressure, axonal injury, genetic predisposition, neuroinflammation, and autoimmunity may be responsible for the development of pituitary dysfunction. Neuroendocrine abnormalities are recently described in athletes dealing with contact sports, including boxing and kickboxing, which are characterized by chronic repetitive head trauma. Mild TBI and concussion are accepted in boxing and kickboxing. The positivity of antipituitary and antihypothalamic antibodies is also a significant risk factor in the development of neuroendocrine abnormalities. Autoimmune reaction may also be responsible for the reduction in pituitary volume in boxers with hypopituitarism. In this chapter, the role of autoimmunity in the occurrence of pituitary dysfunction among boxers is discussed.

Circulating neutrophil-to-lymphocyte ratio at admission predicts the long-term outcome in acute traumatic cervical spinal cord injury patients

Background

The prognostic value of Neutrophil-to-Lymphocyte Ratio (NLR) for the outcome of acute cervical traumatic spinal cord injury (tSCI) patients has rarely been studied by now throughout the world.

Methods

We performed a single-center retrospective cohort study to evaluate the prognostic value of NLR from peripheral whole blood count in patients with acute cervical tSCI. Patients within 6 h of acute cervical tSCI treated between Dec 2008 and May 2018 in Huashan Hospital of Fudan University were enrolled. Outcomes of patients with tSCI were assessed using American spinal injury association Impairment Scale (AIS). 6-month outcomes were dichotomized into poor outcome group (AIS A to C) and good outcome group (AIS D and E). Uni- and multivariate analyses were performed to assess the independent predictors of 6-month outcome. Two prediction models based on admission characteristics were built to evaluate the prognostic value of NLR. The discriminative ability of predictive models was evaluated using the area under the curve (AUC).

Results

A total of 377 patients were identified from our single center in China PR. Multivariate analysis showed that age, AIS grade at admission, NLR (p < 0.001) and coagulopathy (p = 0.003) were independent predictors of the 6-months outcome for acute cervical tSCI patients. The model combing NLR and standard variables (AUC = 0.944; 95% CI, 0.923–0.964) showed a more favorable prognostic value than that without NLR (AUC = 0.841; 95% CI, 0.798–0.885) in terms of 6-month outcome.

Conclusions

NLR is firstly identified as an independent predictor of the 6-month outcome in acute cervical tSCI patients worldwide. The prognostic value of NLR is favorable, and a high NLR is associated with poor outcome in patients with acute cervical tSCI.

Cognitive recovery of children and adolescents with moderate to severe TBI during inpatient rehabilitation

OBJECTIVE

Traumatic brain injury (TBI) is the leading cause of morbidity and mortality in children and adolescents. This study examines the early cognitive-linguistic recovery of pediatric patients who sustained TBI and required inpatient rehabilitation and investigates the contribution of various demographic, clinical, and preinjury factors to recovery.

METHODS

A retrospective chart review of children and adolescents, ages 3-20 years, admitted to an inpatient rehabilitation unit. Acute outcomes were assessed at admission and discharge using the WeeFIM and CALS. Premorbid measures of behavioral and emotional functioning were also collected.

RESULTS

One hundred and one children and adolescents (mean age = 12.31, SD = 4.46) diagnosed with TBI requiring inpatient rehabilitation were included. Patients displayed significant improvements on cognitive-linguistic skills and functional independence between admission and discharge, with medium to large effect sizes. Premorbid behavioral-emotional functioning was not found to be associated with early cognitive recovery.

CONCLUSION

Results suggest that significant functional improvements can be expected for pediatric patients with TBI during inpatient rehabilitation. Consistent with previous literature, injury severity was significantly related to acute outcomes. In conjunction with the WeeFIM, the CALS appears to be a meaningful complement for assessing and monitoring cognitive-linguistic skills during inpatient rehabilitation.Implications for RehabiliationOur study provides support for the utility of the CALS to assess cognitive recovery during inpatient rehabilitation following moderate to severe TBI.Injury severity and not pre-injury functioning or demographic variables was related to worse scores on the CALS at discharge.Using a measure sensitive to change over admission, such as the CALS, can inform treatment planning.

Cumulative Influence of Inflammatory Response Genetic Variation on Long-Term Neurobehavioral Outcomes after Pediatric Traumatic Brain Injury Relative to Orthopedic Injury: An Exploratory Polygenic Risk Score

The addition of genetic factors to prognostic models of neurobehavioral recovery following pediatric traumatic brain injury (TBI) may account for unexplained heterogeneity in outcomes. The present study examined the cumulative influence of candidate genes involved in the inflammatory response on long-term neurobehavioral recovery in children with early childhood TBI relative to children with orthopedic injuries (OI). Participants were drawn from a prospective, longitudinal study evaluating outcomes of children who sustained TBI (n = 67) or OI (n = 68) between the ages of 3 and 7 years. Parents completed ratings of child executive function and behavior at an average of 6.8 years after injury. Exploratory unweighted and weighted polygenic risk scores (PRS) were constructed from single nucleotide polymorphisms (SNPs) across candidate inflammatory response genes (i.e., angiotensin converting enzyme [ACE], brain-derived neurotrophic factor [BDNF], interleukin-1 receptor antagonist [IL1RN], and 5'-ectonucleotidase [NT5E]) that showed nominal (p ≤ 0.20) associations with outcomes in the TBI group. Linear regression models tested the PRS × injury group (TBI vs. OI) interaction term and post-hoc analyses examined the effect of PRS within each injury group. Higher inflammatory response PRS were associated with more executive dysfunction and behavior problems in children with TBI but not in children with OI. The cumulative influence of inflammatory response genes as measured by PRS explained additional variance in long-term neurobehavioral outcomes, over and above well-established predictors and single candidate SNPs tested individually. The results suggest that some of the unexplained heterogeneity in long-term neurobehavioral outcomes following pediatric TBI may be attributable to a child's genetic predisposition to a greater or lesser inflammatory response to TBI.

Epigenetic Effects on Pediatric Traumatic Brain Injury Recovery (EETR): An Observational, Prospective, Longitudinal Concurrent Cohort Study Protocol

Introduction: Unexplained heterogeneity in outcomes following pediatric traumatic brain injury (TBI) is one of the most critical barriers to the development of effective prognostic tools and therapeutics. The addition of personal biological factors to our prediction models may account for a significant portion of unexplained variance and advance the field toward precision rehabilitation medicine. The overarching goal of the Epigenetic Effects on Pediatric Traumatic Brain Injury Recovery (EETR) study is to investigate an epigenetic biomarker involved in both childhood adversity and postinjury neuroplasticity to better understand heterogeneity in neurobehavioral outcomes following pediatric TBI. Our primary hypothesis is that childhood adversity will be associated with worse neurobehavioral recovery in part through an epigenetically mediated reduction in brain-derived neurotrophic factor (BDNF) expression in response to TBI. Methods and analysis: EETR is an observational, prospective, longitudinal concurrent cohort study of children aged 3-18 years with either TBI (n = 200) or orthopedic injury (n = 100), recruited from the UPMC Children's Hospital of Pittsburgh. Participants complete study visits acutely and at 6 and 12 months postinjury. Blood and saliva biosamples are collected at all time points-and cerebrospinal fluid (CSF) when available acutely-for epigenetic and proteomic analysis of BDNF. Additional measures assess injury characteristics, pre- and postinjury child neurobehavioral functioning, childhood adversity, and potential covariates/confounders. Recruitment began in July 2017 and will occur for ~6 years, with data collection complete by mid-2023. Analyses will characterize BDNF DNA methylation and protein levels over the recovery period and investigate this novel biomarker as a potential biological mechanism underlying the known association between childhood adversity and worse neurobehavioral outcomes following pediatric TBI. Ethics and dissemination: The study received ethics approval from the University of Pittsburgh Institutional Review Board. Participants and their parents provide informed consent/assent. Research findings will be disseminated via local and international conference presentations and manuscripts submitted to peer-reviewed journals. Trial Registration: The study is registered with clinicaltrials.org (ClinicalTrials.gov Identifier: NCT04186429).

Signal Information Prediction of Mortality Identifies Unique Patient Subsets after Severe Traumatic Brain Injury: A Decision-Tree Analysis Approach

Nonlinear physiological signal features that reveal information content and causal flow have recently been shown to be predictors of mortality after severe traumatic brain injury (TBI). The extent to which these features interact together, and with traditional measures to describe patients in a clinically meaningful way remains unclear. In this study, we incorporated basic demographics (age and initial Glasgow Coma Scale [GCS]) with linear and non-linear signal information based features (approximate entropy [ApEn], and multivariate conditional Granger causality [GC]) to evaluate their relative contributions to mortality using cardio-cerebral monitoring data from 171 severe TBI patients admitted to a single neurocritical care center over a 10 year period. Beyond linear modelling, we employed a decision tree analysis approach to define a predictive hierarchy of features. We found ApEn (p = 0.009) and GC (p = 0.004) based features to be independent predictors of mortality at a time when mean intracranial pressure (ICP) was not. Our combined model with both signal information-based features performed the strongest (area under curve = 0.86 vs. 0.77 for linear features only). Although low "intracranial" complexity (ApEn-ICP) outranked both age and GCS as crucial drivers of mortality (fivefold increase in mortality where ApEn-ICP <1.56, 36.2% vs. 7.8%), decision tree analysis revealed clear subsets of patient populations using all three predictors. Patients with lower ApEn-ICP who were >60 years of age died, whereas those with higher ApEn-ICP and GCS ≥5 all survived. Yet, even with low initial intracranial complexity, as long as patients maintained robust GC and "extracranial" complexity (ApEn of mean arterial pressure), they all survived. Incorporating traditional linear and novel, non-linear signal information features, particularly in a framework such as decision trees, may provide better insight into "health" status. However, caution is required when interpreting these results in a clinical setting prior to external validation.

Integrative Analysis of Circulating Metabolite Profiles and Magnetic Resonance Imaging Metrics in Patients with Traumatic Brain Injury

Recent evidence suggests that patients with traumatic brain injuries (TBIs) have a distinct circulating metabolic profile. However, it is unclear if this metabolomic profile corresponds to changes in brain morphology as observed by magnetic resonance imaging (MRI). The aim of this study was to explore how circulating serum metabolites, following TBI, relate to structural MRI (sMRI) findings. Serum samples were collected upon admission to the emergency department from patients suffering from acute TBI and metabolites were measured using mass spectrometry-based metabolomics. Most of these patients sustained a mild TBI. In the same patients, sMRIs were taken and volumetric data were extracted (138 metrics). From a pool of 203 eligible screened patients, 96 met the inclusion criteria for this study. Metabolites were summarized as eight clusters and sMRI data were reduced to 15 independent components (ICs). Partial correlation analysis showed that four metabolite clusters had significant associations with specific ICs, reflecting both the grey and white matter brain injury. Multiple machine learning approaches were then applied in order to investigate if circulating metabolites could distinguish between positive and negative sMRI findings. A logistic regression model was developed, comprised of two metabolic predictors (erythronic acid and myo-inositol), which, together with neurofilament light polypeptide (NF-L), discriminated positive and negative sMRI findings with an area under the curve of the receiver-operating characteristic of 0.85 (specificity = 0.89, sensitivity = 0.65). The results of this study show that metabolomic analysis of blood samples upon admission, either alone or in combination with protein biomarkers, can provide valuable information about the impact of TBI on brain structural changes.

IMPACT and CRASH prognostic models for traumatic brain injury: external validation in a South-American cohort

OBJECTIVE

To develop a robust prognostic model, the more diverse the settings in which the system is tested and found to be accurate, the more likely it will be generalisable to untested settings. This study aimed to externally validate the International Mission for Prognosis and Clinical Trials in Traumatic Brain Injury (IMPACT) and Corticosteroid Randomization after Significant Head Injury (CRASH) models for low-income and middle-income countries using a dataset of patients with severe traumatic brain injury (TBI) from the Benchmark Evidence from South American Trials: Treatment of Intracranial Pressure study and a simultaneously conducted observational study.

METHOD

A total of 550 patients with severe TBI were enrolled in the study, and 466 of those were included in the analysis. Patient admission characteristics were extracted to predict unfavourable outcome (Glasgow Outcome Scale: GOS<3) and mortality (GOS 1) at 14 days or 6 months.

RESULTS

There were 48% of the participants who had unfavourable outcome at 6 months and these included 38% who had died. The area under the receiver operating characteristic curve (AUC) values were 0.683-0.775 and 0.640-0.731 for the IMPACT and CRASH models respectively. The IMPACT CT model had the highest AUC for predicting unfavourable outcomes, and the IMPACT Lab model had the best discrimination for predicting 6-month mortality. The discrimination for both the IMPACT and CRASH models improved with increasing complexity of the models. Calibration revealed that there were disagreement between observed and predicted outcomes in the IMPACT and CRASH models.

CONCLUSION

The overall performance of all IMPACT and CRASH models was adequate when used to predict outcomes in the dataset. However, some disagreement in calibration suggests the necessity for updating prognostic models to maintain currency and generalisability.

The Use of Rotterdam CT Score for Prediction of Outcomes in Pediatric Traumatic Brain Injury Patients Admitted to Emergency Service

INTRODUCTION

Rotterdam CT score for prediction of outcome in traumatic brain injury is widely used for patient evaluation. The data on the assessment of pediatric traumatic brain injury patients with the Rotterdam scale in our country are still limited. In this study, we aimed to evaluate the use of the Rotterdam scale on pediatric trauma patients in our country and assess its relationship with lesion type, location and severity, trauma type, and need for surgery.

METHODS

A total of 229 pediatric patients admitted to the emergency service due to head trauma were included in our study. Patients were evaluated in terms of age, gender, Glasgow Coma Scale (GCS), initial and follow-up Rotterdam scale scores, length of stay, presence of other traumas, seizures, antiepileptic drug use, need for surgical necessity, and final outcome.

RESULTS

A total of 229 patients were included in the study, and the mean age of the patients was 95.8 months. Of the patients, 87 (38%) were girls and 142 (62%) were boys. Regarding GCS at the time of admission, 59% (n = 135) of the patients had mild (GCS = 13-15), 30.6% (n = 70) had moderate (GCS = 9-12), and 10.5% (n = 24) had severe (GCS < 9) head trauma. The mean Rotterdam scale score was calculated as 1.51 (ranging from 1 to 3) for mild, 2.22 (ranging from 1 to 4) for moderate, and 4.33 (ranging from 2 to 6) for severe head trauma patients. Rotterdam scale score increases significantly as the degree of head injury increases (p < 0.001).

DISCUSSION

With the adequate use of GCS and cerebral computed tomography imaging, pediatric patients with a higher risk of mortality and need for surgery can be predicted. We recommend the follow-up of pediatric traumatic brain injury patients with repeated CT scans to observe alterations in Rotterdam CT scores, which may be predictive for the need for surgery and intensive care.

Comparison between traumatic brain injury with and without concomitant injuries: an analysis based on a national trauma registry 2008-2016

Objective: To compare demographic, injury and hospitalization characteristics and mortality between Isolated and Non-Isolated traumatic brain injury.Methods: A retrospective study based on the Israeli National Trauma Registry of patients hospitalized for traumatic brain injury (TBI) between 2008 and 2016. Isolated TBI was defined as no other anatomic region was having concomitant injury with AIS ≥2. X² test and multivariate logistic regression analysis were used for data analysis.Results: Of the 23566-study population, 40.4% were admitted for isolated TBI. Isolated TBI was significantly more frequent in elderly aged ≥65 years, female, Jews, and injuries sustained at home or in residential institution. The Non-isolated TBI was greater in road traffic injuries, particularly among pedestrians and motor cyclists, and in violence injuries. The Non-isolated TBI group had greater injury severity and hospital resource utilization. In-hospital mortality was higher in the patients with Non-isolated TBI [OR: 1.56(95% CI: 1.33-1.83)], particularly in patients with GCS 13-15; elderly aged 65+ years; and patients with concomitant injuries to abdomen, spine or external body regions.Conclusion: In a patient with TBI, concomitant injuries with AIS ≥2 matter, and awareness of the identified factors has relevance for guiding injury prevention efforts and indeed for potentially improving care and outcome.

Serum Amyloid A1 as a Potential Intracranial and Extracranial Clinical Severity Biomarker in Traumatic Brain Injury

Extracranial injury is frequently present in patients with traumatic brain injury (TBI). However, no reliable biomarker exists nowadays to evaluate the magnitude and extension of extracranial injury as well as the identification of patients who are at risk of developing secondary injuries. The purpose of this study was to identify new possible peptide biomarkers by mass spectrometry analysis in patients with TBI and ascertain whether the novel biomarker discovered by peptide mass fingerprinting, serum amyloid A1 (SAA1), is capable of reflecting the condition of the patient and both intracranial and extracranial injury extension. Demographic characteristics, clinical data, and serum samples were prospectively collected from 120 patients with TBI (Glasgow Coma Scale [GCS] score 3-15) on admission. Biomarkers were quantified by enzyme-linked immunosorbent assay. Intracranial lesion volume was measured from the semiautomatic segmentation of hematoma on computed tomography (CT) using Analyze software. Functional outcome was evaluated using the Glasgow Outcome Scale (GOS) at hospital discharge and GOS extended scores at 6 months. The SAA1 levels were significantly associated with intracranial (GCS score at admission, lesion load measured with cranial CT, and pupil responsiveness) and extracranial clinical severity (all Abbreviated Injury Scale regions, Injury Severity Score, major extracranial injury, polytrauma, and orthopedic fractures presence), along with systemic secondary insults and functional outcome. SAA1 was is associated with the volume of traumatic intracranial lesions. The SAA1 levels were correlated with astroglial S100β and glial fibrillary acidic protein (GFAP), neuronal neuron-specific enolase (NSE), and axonal total tau (T-tau) and phosphorylated neurofilament heavy chain (pNF-H) injury markers. SAA1 predicts unfavorable outcome and mortality at hospital discharge (area under the curve [AUC] = 0.90, 0.82) and 6 months (AUC = 0.89). SAA1 can be established as a marker for the overall patient condition due to its involvement in the neuroendocrine axis of the systemic response to craniocerebral trauma.

Prognostic Value of Neutrophil-to-Lymphocyte Ratio in Predicting the 6-Month Outcome of Patients with Traumatic Brain Injury: A Retrospective Study

BACKGROUND

Peripheral white blood cells are regularly analyzed on admission for patients with traumatic brain injury (TBI). The prognostic value of the neutrophil-to-lymphocyte ratio (NLR) in predicting the 6-month outcome of patients with TBI is unclear.

METHODS

We designed a single-center retrospective cohort study. Patients admitted to Fudan University Huashan Hospital within 6 hours after TBI were identified between December 2004 and December 2017. The primary outcome was 6-month Glasgow Outcome Scale score. Independent predictors of 6-month outcome were assessed using uni- and multivariate analyses. Three models based on admission characteristics were built to evaluate the prognostic value of the NLR in predicting the outcome of patients with TBI. The discriminative ability of predictive models was evaluated by the area under the curve (AUC).

RESULTS

A total of 1291 patients with TBI were included. Multivariate analysis showed age, Glasgow Coma Scale scores at admission, subdural hematoma, intraparenchymal hemorrhage, traumatic subarachnoid hemorrhage, NLR (P < 0.001), and coagulopathy (P = 0.028) were independent predictors of 6-month outcome. The model combining the NLR and standard variables (AUC = 0.936; 95% confidence interval [CI], 0.923-0.949) was more favorable in predicting 6-month outcome of patients with TBI than the model without the NLR (AUC = 0.901; 95% CI, 0.883-0.919) and the model based only on the NLR (AUC = 0.827; 95% CI, 0.802-0.852).

CONCLUSIONS

NLR is an independent prognostic factor of predicting 6-month outcome of patients with TBI. A high NLR in patients with TBI is associated with poor outcome. The prognostic value of the NLR in predicting 6-month outcome of patients with TBI is favorable.

Variation in Candidate Traumatic Brain Injury Biomarker Genes Are Associated with Gross Neurological Outcomes after Severe Traumatic Brain Injury

Diagnostic and prognostic biomarkers of traumatic brain injury (TBI) are actively being pursued; potential candidates include glial fibrillary acid protein (GFAP), S100 calcium-binding protein B (S100B), and ubiquitin C-terminal hydrolase L1 (UCHL1), two of which the United States Food and Drug Administration (FDA) recently approved for marketing of blood tests for adult concussion. The relationship between biomarker-encoding genes and TBI outcomes remains unknown. This pilot study explores variation in 18 single nucleotide polymorphisms (SNPs) in biomarker-encoding genes as predictors of neurological outcome in a population of adults with severe TBI. Participants (n = 305) were assessed using the Glasgow Outcome Scale (GOS) at 3, 6, 12, and 24 months post-injury. Multivariate logistical regression was used to calculate the odds ratio (OR) and determine the odds of having a lower score on the GOS ( = 1-2 vs. 3-5) based on variant allele presence, while controlling for confounders. Possession of the variant allele of one S100B SNP (rs1051169) was associated with higher scores on the GOS at 3 months (OR = 0.39; p = 0.04), 6 months (OR = 0.34; p = 0.02), 12 months (OR = 0.32; p = 0.02), and 24 months (OR = 0.30; p = 0.02) post-severe TBI. The relationship among these polymorphisms, protein levels, and biomarker utility, merits examination. These findings represent a novel contribution to the evidence that can inform future studies aimed at enhancing interpretation of biomarker data, identifying novel biomarkers, and ultimately harnessing this information to improve clinical outcomes and personalize care.

Isolated subdural hematomas in mild traumatic brain injury. Part 1: the association between radiographic characteristics and neurosurgical intervention

OBJECTIVE

Isolated subdural hematomas (iSDHs) are one of the most common intracranial hemorrhage (ICH) types in the population with mild traumatic brain injury (mTBI; Glasgow Coma Scale score 13-15), account for 66%-75% of all neurosurgical procedures, and have one of the highest neurosurgical intervention rates. The objective of this study was to examine how quantitative hemorrhage characteristics of iSDHs in patients with mTBI at admission are associated with subsequent neurosurgical intervention.

METHODS

This was a 3.5-year, retrospective observational cohort study at a Level I trauma center. All adult trauma patients with mTBI and iSDHs were included in the study. Maximum length and thickness (in mm) of acute SDHs, the presence of acute-on-chronic SDH, mass effect, and other hemorrhage-related variables were double-data entered; discrepant results were adjudicated after a maximum of 4 reviews. Patients with coagulopathy, skull fractures, no acute hemorrhage, a non-SDH ICH, or who did not undergo imaging on admission were excluded. The primary outcome was neurosurgical intervention (craniotomy, burr hole, catheter drainage of SDH, placement of intracranial pressure monitor, shunt, or ventriculostomy). Multivariate stepwise logistic regression was used to identify significant covariates and to assess interactions.

RESULTS

A total of 176 patients were included in our study: 28 patients did and 148 patients did not receive a neurosurgical intervention. Increasing head Abbreviated Injury Scale score was significantly associated with neurosurgical interventions. There was a strong correlation between the first 3 reviews on maximum hemorrhage length (R2 = 0.82) and maximum hemorrhage thickness (R2 = 0.80). The neurosurgical intervention group had a mean maximum SDH length and thickness that were 61 mm longer and 13 mm thicker than those of the nonneurosurgical intervention group (p < 0.001 for both). After adjusting for the presence of an acute-on-chronic hemorrhage, for every 1-mm increase in the thickness of an iSDH, the odds of a neurosurgical intervention increase by 32% (95% CI 1.16-1.50). There were no interventions for any SDH with a maximum thickness ≤ 5 mm on initial presenting scan.

CONCLUSIONS

This is the first study to quantify the odds of a neurosurgical intervention based on hemorrhage characteristics in patients with an iSDH and mTBI. Once validated in a second population, these data can be used to better inform patients and families of the risk of future neurosurgical intervention, and to evaluate the necessity of interhospital transfers.

Isolated subdural hematomas in mild traumatic brain injury. Part 2: a preliminary clinical decision support tool for neurosurgical intervention

OBJECTIVE

A paucity of studies have examined neurosurgical interventions in the mild traumatic brain injury (mTBI) population with intracranial hemorrhage (ICH). Furthermore, it is not understood how the dimensions of an ICH relate to the risk of a neurosurgical intervention. These limitations contribute to a lack of treatment guidelines. Isolated subdural hematomas (iSDHs) are the most prevalent ICH in mTBI, carry the highest neurosurgical intervention rate, and account for an overwhelming majority of all neurosurgical interventions. Decision criteria in this population could benefit from understanding the risk of requiring neurosurgical intervention. The aim of this study was to quantify the risk of neurosurgical intervention based on the dimensions of an iSDH in the setting of mTBI.

METHODS

This was a 3.5-year, retrospective observational cohort study at a Level I trauma center. All adult (≥ 18 years) trauma patients with mTBI and iSDH were included in the study. Maximum length and thickness (in mm) of acute SDHs, the presence of acute-on-chronic (AOC) SDH, mass effect, and other hemorrhage-related variables were double-data entered; discrepant results were adjudicated after a maximum of 4 reviews. Patients with coagulopathy, skull fractures, no acute hemorrhage, a non-SDH ICH, or who did not undergo imaging on admission were excluded. Tentorial SDHs were not measured. The primary outcome was neurosurgical intervention (craniotomy, burr holes, intracranial pressure monitor placement, shunt, ventriculostomy, or SDH evacuation). Multivariate stepwise logistic regression was used to identify significant covariates, to assess interactions, and to create the scoring system.

RESULTS

There were a total of 176 patients included in our study: 28 patients did and 148 did not receive a neurosurgical intervention. There were no significant differences between neurosurgical intervention groups in 11 demographic and 22 comorbid variables. Patients with neurosurgical intervention had significantly longer and thicker SDHs than nonsurgical controls. Logistic regression identified thickness and AOC hemorrhage as being the most important variables in predicting neurosurgical intervention; SDH length was not. Risk of neurosurgical intervention was calculated based on the SDH thickness and presence of an AOC hemorrhage from a multivariable logistic regression model (area under the receiver operating characteristic curve 0.94, 95% CI 0.90-0.97; p < 0.001). With a decision point of 2.35% risk, we predicted neurosurgical intervention with 100% sensitivity, 100% negative predictive value, and 53% specificity.

CONCLUSIONS

This is the first study to quantify the risk of neurosurgical intervention based on hemorrhage characteristics in patients with mTBI and iSDH. Once validated in a second population, these data can be used to inform the necessity of interhospital transfers and neurosurgical consultations.

The Dynamics of Concussion: Mapping Pathophysiology, Persistence, and Recovery With Causal-Loop Diagramming

Despite increasing public awareness and a growing body of literature on the subject of concussion, or mild traumatic brain injury, an urgent need still exists for reliable diagnostic measures, clinical care guidelines, and effective treatments for the condition. Complexity and heterogeneity complicate research efforts and indicate the need for innovative approaches to synthesize current knowledge in order to improve clinical outcomes. Methods from the interdisciplinary field of systems science, including models of complex systems, have been increasingly applied to biomedical applications and show promise for generating insight for traumatic brain injury. The current study uses causal-loop diagramming to visualize relationships between factors influencing the pathophysiology and recovery trajectories of concussive injury, including persistence of symptoms and deficits. The primary output is a series of preliminary systems maps detailing feedback loops, intrinsic dynamics, exogenous drivers, and hubs across several scales, from micro-level cellular processes to social influences. Key system features, such as the role of specific restorative feedback processes and cross-scale connections, are examined and discussed in the context of recovery trajectories. This systems approach integrates research findings across disciplines and allows components to be considered in relation to larger system influences, which enables the identification of research gaps, supports classification efforts, and provides a framework for interdisciplinary collaboration and communication-all strides that would benefit diagnosis, prognosis, and treatment in the clinic.

Prognostic Value of S-100β Protein for Prediction of Post-Concussion Symptoms after a Mild Traumatic Brain Injury: Systematic Review and Meta-Analysis

This systematic review and meta-analysis aimed to determine the prognostic value of S-100β protein to identify patients with post-concussion symptoms after a mild traumatic brain injury (mTBI). A search strategy was submitted to seven databases from their inception to October 2016. Individual patient data were requested. Cohort studies evaluating the association between S-100β protein level and post-concussion symptoms assessed at least seven days after the mTBI were considered. Outcomes were dichotomized as persistent (≥3 months) or early (≥7 days <3 months). Our search strategy yielded 23,298 citations of which 29 studies including between seven and 223 patients (n = 2505) were included. Post-concussion syndrome (PCS) (16 studies) and neuropsychological symptoms (9 studies) were the most frequently assessed outcomes. The odds of having persistent PCS (odds ratio [OR] 0.62, 95% confidence interval [CI]: 0.34-1.12, p = 0.11, I² 0% [n = five studies]) in patients with an elevated S-100β protein serum level were not significantly different from those of patients with normal values while the odds of having early PCS (OR 1.67, 95% CI: 0.98-2.85, p = 0.06, I² 38% [n = five studies]) were close to statistical significance. Similarly, having an elevated S-100β protein serum level was not associated with the odds of returning to work at six months (OR 2.31, 95% CI: 0.50-10.64, p = 0.28, I² 22% [n = two studies]). Overall risk of bias was considered moderate. Results suggest that the prognostic biomarker S-100β protein has a low clinical value to identify patients at risk of persistent post-concussion symptoms. Variability in injury to S-100ß protein sample time, mTBI populations, and outcomes assessed could potentially explain the lack of association and needs further evaluation.

Prognostic value of coagulation tests for in-hospital mortality in patients with traumatic brain injury

BACKGROUND

Coagulopathy is commonly observed after traumatic brain injury (TBI). However, it is not known whether using the standard independent predictors in conjunction with coagulation tests would improve their prognostic value. We determined the incidence of TBI-associated coagulopathy in patients with isolated TBI (iTBI), evaluated the prognostic value of coagulation tests for in-hospital mortality, and tested their predictive power for in-hospital mortality in patients with iTBI.

METHODS

We conducted a retrospective, observational database study on 2319 consecutive patients with iTBI who attended the Huashan Hospital Department of the Neurosurgery Neurotrauma Center at Fudan University in China between December 2004 and June 2015. Two models based on the admission characteristics were developed: model A included predictors such as age, Glasgow Coma Scale (GCS) score, pupil reactivity, type of injury, and hemoglobin and glucose levels, while model B included the predictors from model A as well as coagulation test results. A total of 1643 patients enrolled between December 2004 and December 2011 were used to derive the prognostic models, and 676 patients enrolled between January 2012 and June 2015 were used to validate the models.

RESULTS

Overall, 18.6% (n = 432) of the patients developed coagulopathy after iTBI. The prevalence of acute traumatic coagulopathy is associated with the severity of brain injury. The percentage of platelet count <100 × 109/L, international normalized ratio (INR) > 1.25, the prothrombin time (PT) > 14 s, activated partial thromboplastin time (APTT) > 36 s, D-dimer >5 mg/L and fibrinogen (FIB) < 1.5 g/L was also closely related to the severity of brain injury, significance being found among three groups. Age, pupillary reactivity, GCS score, epidural hematoma (EDH), and glucose levels were independent prognostic factors for in-hospital mortality in model A, whereas age, pupillary reactivity, GCS score, EDH, glucose levels, INR >1.25, and APTT >36 s exhibited strong prognostic effects in model B. Discrimination and calibration were good for the development group in both prediction models. However, the external validation test showed that calibration was better in model B than in model A for patients from the validation population (Hosmer-Lemeshow test, p = 0.152 vs. p = 0.046, respectively).

CONCLUSIONS

Coagulation tests can improve the predictive power of the standard model for in-hospital mortality after TBI.

Prognostic value of neuron-specific enolase (NSE) for prediction of post-concussion symptoms following a mild traumatic brain injury: a systematic review

BACKGROUND

This systematic review aimed to determine the prognostic value of neuron-specific enolase (NSE) to predict post-concussion symptoms following mild traumatic brain injury (TBI).

METHODS

Seven databases were searched for studies evaluating the association between NSE levels and post-concussion symptoms assessed ≥ 3 months (persistent) or ≥ 7 days < 3 months (early) after mild TBI. Two researchers independently screened studies for inclusion, extracted data and appraised quality using the Quality in Prognostic Studies (QUIPS) tool.

RESULTS

The search strategy yielded a total of 23,298 citations from which 8 cohorts presented in 10 studies were included. Studies included between 45 and 141 patients (total 608 patients). The outcomes most frequently assessed were post-concussion syndrome (PCS, 12 assessments) and neuropsychological performance deficits (10 assessments). No association was found between an elevated NSE serum level and PCS. Only one study reported a statistically significant association between a higher NSE serum level and alteration of at least three cognitive domains at 2 weeks but this association was no longer significant at 6 weeks. Overall, risk of bias of the included studies was considered moderate.

CONCLUSIONS

Early NSE serum level is not a strong independent predictor of post-concussion symptoms following mild TBI.

White matter microstructure is associated with functional, cognitive and emotional symptoms 12 months after mild traumatic brain injury

Identifying patients at risk of poor outcome after mild traumatic brain injury (MTBI) is essential to aid prognostics and treatment. Diffuse axonal injury (DAI) may be the primary pathologic feature of MTBI but is normally not detectable by conventional imaging technology. This lack of sensitivity of clinical imaging techniques has impeded a pathophysiologic understanding of the long-term cognitive and emotional consequences of MTBI, which often remain unnoticed and are attributed to factors other than the injury. Diffusion tensor imaging (DTI) is sensitive to microstructural properties of brain tissue and has been suggested to be a promising candidate for the detection of DAI in vivo. In this study, we report strong associations between brain white matter DTI and self-reported cognitive, somatic and emotional symptoms at 12 months post-injury in 134 MTBI patients. The anatomical distribution suggested global associations, in line with the diffuse symptomatology, although the strongest effects were found in frontal regions including the genu of the corpus callosum and the forceps minor. These findings support the hypothesis that DTI may provide increased sensitivity to the diffuse pathophysiology of MTBI and suggest an important role of advanced Magnetic Resonance Imaging (MRI) in trauma care.

Concussion As a Multi-Scale Complex System: An Interdisciplinary Synthesis of Current Knowledge

Traumatic brain injury (TBI) has been called "the most complicated disease of the most complex organ of the body" and is an increasingly high-profile public health issue. Many patients report long-term impairments following even "mild" injuries, but reliable criteria for diagnosis and prognosis are lacking. Every clinical trial for TBI treatment to date has failed to demonstrate reliable and safe improvement in outcomes, and the existing body of literature is insufficient to support the creation of a new classification system. Concussion, or mild TBI, is a highly heterogeneous phenomenon, and numerous factors interact dynamically to influence an individual's recovery trajectory. Many of the obstacles faced in research and clinical practice related to TBI and concussion, including observed heterogeneity, arguably stem from the complexity of the condition itself. To improve understanding of this complexity, we review the current state of research through the lens provided by the interdisciplinary field of systems science, which has been increasingly applied to biomedical issues. The review was conducted iteratively, through multiple phases of literature review, expert interviews, and systems diagramming and represents the first phase in an effort to develop systems models of concussion. The primary focus of this work was to examine concepts and ways of thinking about concussion that currently impede research design and block advancements in care of TBI. Results are presented in the form of a multi-scale conceptual framework intended to synthesize knowledge across disciplines, improve research design, and provide a broader, multi-scale model for understanding concussion pathophysiology, classification, and treatment.

Clinical characteristics and temporal profile of recovery in patients with favorable outcomes at 6 months after severe traumatic brain injury

OBJECTIVE Early withdrawal of life-sustaining treatment due to expected poor prognosis is responsible for the majority of in-house deaths in severe traumatic brain injury (TBI). With increased focus on the decision and timing of withdrawal of care in patients with severe TBI, data on early neurological recovery in patients with a favorable outcome is needed to guide physicians and families. METHODS The authors reviewed prospectively collected data obtained in 1241 patients with head injury who were treated between 1986 and 2012. Patients with severe TBI, motor Glasgow Coma Scale (mGCS) score < 6 on admission, and those who had favorable outcomes (Glasgow Outcome Scale [GOS] score of 4 or 5, indicating moderate disability or good recovery) at 6 months were selected. Baseline demographic, clinical, and imaging data were analyzed. The time from injury to the first record of following commands (mGCS score of 6) after injury was recorded. The temporal profile of GOS scores from discharge to 6 months after the injury was also assessed. RESULTS The authors studied 218 patients (183 male and 35 female) with a mean age of 28.9 ± 11.2 years. The majority of patients were able to follow commands (mGCS score of 6) within the 1st week after injury (71.4%), with the highest percentage of patients in this group recovering on Day 1 (28.6%). Recovery to the point of following commands beyond 2 weeks after the injury was seen in 14.8% of patients, who experienced significantly longer durations of intracranial pressure monitoring (p = 0.001) and neuromuscular blockade (p < 0.001). In comparison with patients with moderate disability, patients with good recovery had a higher initial GCS score (p = 0.01), lower incidence of anisocoria at admission (p = 0.048), and a shorter ICU stay (p < 0.001) and total hospital stay (p < 0.001). There was considerable improvement in GOS scores from discharge to follow-up at 6 months. CONCLUSIONS Up to 15% of patients with a favorable outcome after severe TBI may begin to follow commands beyond 2 weeks after the injury. These data caution against early withdrawal of life-sustaining treatment in patients with severe TBI.

The aggressiveness of neurotrauma practitioners and the influence of the IMPACT prognostic calculator

Published guidelines have helped to standardize the care of patients with traumatic brain injury; however, there remains substantial variation in the decision to pursue or withhold aggressive care. The International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) prognostic calculator offers the opportunity to study and decrease variability in physician aggressiveness. The authors wish to understand how IMPACT’s prognostic calculations currently influence patient care and to better understand physician aggressiveness. The authors conducted an anonymous international, multidisciplinary survey of practitioners who provide care to patients with traumatic brain injury. Questions were designed to determine current use rates of the IMPACT prognostic calculator and thresholds of age and risk for death or poor outcome that might cause practitioners to consider withholding aggressive care. Correlations between physician aggressiveness, putative predictors of aggressiveness, and demographics were examined. One hundred fifty-four responses were received, half of which were from physicians who were familiar with the IMPACT calculator. The most frequent use of the calculator was to improve communication with patients and their families. On average, respondents indicated that in patients older than 76 years or those with a >85% chance of death or poor outcome it might be reasonable to pursue non-aggressive care. These thresholds were robust and were not influenced by provider or institutional characteristics. This study demonstrates the need to educate physicians about the IMPACT prognostic calculator. The consensus values for age and prognosis identified in our study may be explored in future studies aimed at reducing variability in physician aggressiveness and should not serve as a basis for withdrawing care.

Predicting Outcome 12 Months after Mild Traumatic Brain Injury in Patients Admitted to a Neurosurgery Service

Objective

Accurate outcome prediction models for patients with mild traumatic brain injury (MTBI) are key for prognostic assessment and clinical decision-making. Using multivariate machine learning, we tested the unique and added predictive value of (1) magnetic resonance imaging (MRI)-based brain morphometric and volumetric characterization at 4-week postinjury and (2) demographic, preinjury, injury-related, and postinjury variables on 12-month outcomes, including global functioning level, postconcussion symptoms, and mental health in patients with MTBI.

Methods

A prospective, cohort study of patients (n = 147) aged 16–65 years with a 12-month follow-up. T1-weighted 3 T MRI data were processed in FreeSurfer, yielding accurate cortical reconstructions for surface-based analyses of cortical thickness, area, and volume, and brain segmentation for subcortical and global brain volumes. The 12-month outcome was defined as a composite score using a principal component analysis including the Glasgow Outcome Scale Extended, Rivermead Postconcussion Questionnaire, and Patient Health Questionnaire-9. Using leave-one-out cross-validation and permutation testing, we tested and compared three prediction models: (1) MRI model, (2) clinical model, and (3) MRI and clinical combined.

Results

We found a strong correlation between observed and predicted outcomes for the clinical model (r = 0.55, p < 0.001). The MRI model performed at the chance level (r = 0.03, p = 0.80) and the combined model (r = 0.45, p < 0.002) were slightly weaker than the clinical model. Univariate correlation analyses revealed the strongest association with outcome for postinjury factors of posttraumatic stress (Posttraumatic Symptom Scale-10, r = 0.61), psychological distress (Hospital Anxiety and Depression Scale, r = 0.52), and widespread pain (r = 0.43) assessed at 8 weeks.

Conclusion

We found no added predictive value of MRI-based measures of brain cortical morphometry and subcortical volumes over and above demographic and clinical features.

Influence of Dopamine-Related Genes on Neurobehavioral Recovery after Traumatic Brain Injury during Early Childhood

The present study examined the association of dopamine-related genes with short- and long-term neurobehavioral recovery, as well as neurobehavioral recovery trajectories over time, in children who had sustained early childhood traumatic brain injuries (TBI) relative to children who had sustained orthopedic injuries (OI). Participants were recruited from a prospective, longitudinal study evaluating outcomes of children who sustained a TBI (n = 68) or OI (n = 72) between the ages of 3 and 7 years. Parents completed ratings of child executive function and behavior at the immediate post-acute period (0-3 months after injury); 6, 12, and 18 months after injury; and an average of 3.5 and 7 years after injury. Thirty-two single nucleotide polymorphisms (SNPs) in dopamine-related genes (dopamine receptor D2 [DRD2], solute carrier family 6 member 3 [SLC6A3], solute carrier family 18 member A2 [SLC18A2], catechol-o-methyltransferase [COMT], and ankyrin repeat and kinase domain containing 1 [ANKK1]) were examined in association with short- and long-term executive function and behavioral adjustment, as well as their trajectories over time. After controlling for premorbid child functioning, genetic variation within the SLC6A3 (rs464049 and rs460000) gene was differentially associated with neurobehavioral recovery trajectories over time following TBI relative to OI, with rs464049 surviving multiple testing corrections. In addition, genetic variation within the ANKK1 (rs1800497 and rs2734849) and SLC6A3 (rs464049, rs460000, and rs1042098) genes was differentially associated with short- and long-term neurobehavioral recovery following TBI, with rs460000 and rs464049 surviving multiple testing corrections. The findings provide preliminary evidence that genetic variation in genes involved in DRD2 expression and density (ANKK1) and dopamine transport (SLC6A3) plays a role in neurobehavioral recovery following pediatric TBI.

The application of adult traumatic brain injury models in a pediatric cohort

OBJECTIVE There is increasing interest in the use of predictive models of outcome in adult head injury. Two international models have been identified to be reliable modalities for predicting outcome: the Corticosteroid Randomisation After Significant Head Injury (CRASH) model, and the International Mission on Prognosis and Analysis of randomized Controlled Trials in TBI (IMPACT) model. However, these models are designed only to identify outcomes in adult populations. METHODS A retrospective analysis was performed on pediatric patients with severe traumatic brain injury (TBI) admitted to the pediatric intensive care unit (PICU) of Addenbrooke's Hospital between January 2009 and December 2013. The individual risk of 14-day mortality was calculated using the CRASH-Basic and -CT models, and the risk of 6-month mortality calculated using the IMPACT-Core and -Extended (including CT findings) models. Model accuracy was determined by standardized mortality ratio (SMtR; observed/expected deaths), discrimination was evaluated as the area under the receiver operating curve (AUROC), and calibration assessed using the Hosmer-Lemeshow χ² test. RESULTS Ninety-four patients with an average age of 7.3 years were admitted to the PICU with a TBI. The mortality rate was 12.7% at 14 days and at 6 months. For the CRASH-Basic model, the SMtR was 1.42 and both calibration (χ² = 6.1, p = 0.64) and discrimination (AUROC = 0.92) were good. For the IMPACT-Core model, the SMtR was 1.03 and the model was also well calibrated (χ² = 8.99, p = 0.34) and had good discrimination (AUROC = 0.85). Poor outcome was observed in 17% of the cohort and identified with the CRASH-Basic and IMPACT-Core models to varying degrees: standardized morbidity ratio = 0.89 vs 0.67, respectively; calibration = 6.5 (χ²) and 0.59 (p value) versus 8.52 (χ²) and 0.38 (p value), respectively; and discrimination (AUROC) = 0.92 versus 0.83, respectively. CONCLUSIONS Adult head injury models may be applied with sufficient accuracy to identify predictors of morbidity and mortality in pediatric TBI.

Past, Present, and Future of Traumatic Brain Injury Research

Traumatic brain injury (TBI) is the greatest cause of death and severe disability in young adults; its incidence is increasing in the elderly and in the developing world. Outcome from severe TBI has improved dramatically as a result of advancements in trauma systems and supportive critical care, however we remain without a therapeutic which acts directly to attenuate brain injury. Recognition of secondary injury and its molecular mediators has raised hopes for such targeted treatments. Unfortunately, over 30 late-phase clinical trials investigating promising agents have failed to translate a therapeutic for clinical use. Numerous explanations for this failure have been postulated and are reviewed here. With this historical context we review ongoing research and anticipated future trends which are armed with lessons from past trials, new scientific advances, as well as improved research infrastructure and funding. There is great hope that these new efforts will finally lead to an effective therapeutic for TBI as well as better clinical management strategies.

Effect of angiotensin-converting enzyme tag single nucleotide polymorphisms on the outcome of patients with traumatic brain injury

BACKGROUND

Genetic variants appear to influence, at least to some degree, the extent of brain injury and the clinical outcome of patients who have sustained a traumatic brain injury (TBI). Angiotensin-converting enzyme (ACE) is a zinc metallopeptidase that is implicated in the regulation of blood pressure and cerebral circulation. ACE gene polymorphisms were found to regulate serum ACE enzyme activity.

OBJECTIVE

The present study aimed to investigate possible influence of ACE gene region variants on patients' outcome after TBI.

PATIENTS AND METHODS

In total, 363 TBI patients prospectively enrolled in the study were genotyped for five tag single nucleotide polymorphisms (SNPs) across the ACE gene. Using logistic regression analyses, tag SNPs and their constructed haplotypes were tested for associations with 6-month Glasgow Outcome Scale scores, after adjustment for age, sex, Glasgow Coma Scale scores at admission, and the presence of a hemorrhagic event in the initial computed tomography scan.

RESULTS

Significant effects on TBI outcome were found for three neighboring tag SNPs in the codominant (genotypic) model of inheritance [rs4461142: odds ratio (OR) 0.26, 95% confidence interval (CI) 0.12-0.57, P = 0.0001; rs7221780: OR 2.67, 95% CI 1.25-5.72, P = 0.0003; and rs8066276: OR 3.82, 95% CI 1.80-8.13, P = 0.0002; for the heterozygous variants compared with the common alleles]. None of the constructed common tag SNPs haplotypes was associated with TBI outcome.

CONCLUSION

The present study provides evidence of the possible influence of genetic variations in a specific region of the ACE gene on the outcome of TBI patients. This association may have pharmacogenetic implications in identifying those TBI patients who may benefit from ACE inhibition.