Clinical Gestalt for Early Prediction of Delayed Functional and Symptomatic Recovery From Mild Traumatic Brain Injury Is Inadequate

Consensus paper on the assessment of adult patients with traumatic brain injury with Glasgow Coma Scale 13-15 at the emergency department: A multidisciplinary overview

Traumatic brain injury (TBI) is a common reason for presenting to emergency departments (EDs). The assessment of these patients is frequently hampered by various confounders, and diagnostics is still often based on nonspecific clinical signs. Throughout Europe, there is wide variation in clinical practices, including the follow-up of those discharged from the ED. The objective is to present a practical recommendation for the assessment of adult patients with an acute TBI, focusing on milder cases not requiring in-hospital care. The aim is to advise on and harmonize practices for European settings. A multiprofessional expert panel, giving consensus recommendations based on recent scientific literature and clinical practices, is employed. The focus is on patients with a preserved consciousness (Glasgow Coma Scale 13-15) not requiring in-hospital care after ED assessment. The main results of this paper contain practical, clinically usable recommendations for acute clinical assessment, decision-making on acute head computerized tomography (CT), use of biomarkers, discharge options, and needs for follow-up, as well as a discussion of the main features and risk factors for prolonged recovery. In conclusion, this consensus paper provides a practical stepwise approach for the clinical assessment of patients with an acute TBI at the ED. Recommendations are given for the performance of acute head CT, use of brain biomarkers and disposition after ED care including careful patient information and organization of follow-up for those discharged.

Fluid-Based Protein Biomarkers in Traumatic Brain Injury: The View from the Bedside

There has been an explosion of research into biofluid (blood, cerebrospinal fluid, CSF)-based protein biomarkers in traumatic brain injury (TBI) over the past decade. The availability of very large datasets, such as CENTRE-TBI and TRACK-TBI, allows for correlation of blood- and CSF-based molecular (protein), radiological (structural) and clinical (physiological) marker data to adverse clinical outcomes. The quality of a given biomarker has often been framed in relation to the predictive power on the outcome quantified from the area under the Receiver Operating Characteristic (ROC) curve. However, this does not in itself provide clinical utility but reflects a statistical association in any given population between one or more variables and clinical outcome. It is not currently established how to incorporate and integrate biofluid-based biomarker data into patient management because there is no standardized role for such data in clinical decision making. We review the current status of biomarker research and discuss how we can integrate existing markers into current clinical practice and what additional biomarkers do we need to improve diagnoses and to guide therapy and to assess treatment efficacy. Furthermore, we argue for employing machine learning (ML) capabilities to integrate the protein biomarker data with other established, routinely used clinical diagnostic tools, to provide the clinician with actionable information to guide medical intervention.

Early Shared Decision-Making for Older Adults with Traumatic Brain Injury: Using Time-Limited Trials and Understanding Their Limitations

Older adults account for a disproportionate share of the morbidity and mortality after traumatic brain injury (TBI). Predicting functional and cognitive outcomes for individual older adults after TBI is challenging in the acute phase of injury. Given that neurologic recovery is possible and uncertain, life-sustaining therapy may be pursued initially, even if for some, there is a risk of survival to an undesired level of disability or dependence. Experts recommend early conversations about goals of care after TBI, but evidence-based guidelines for these discussions or for the optimal method for communicating prognosis are limited. The time-limited trial (TLT) model may be an effective strategy for managing prognostic uncertainty after TBI. TLTs can provide a framework for early management: specific treatments or procedures are used for a defined period of time while monitoring for an agreed-upon outcome. Outcome measures, including signs of worsening and improvement, are defined at the outset of the trial. In this Viewpoint article, we discuss the use of TLTs for older adults with TBI, their potential benefits, and current challenges to their application. Three main barriers limit the implementation of TLTs in these scenarios: inadequate models for prognostication; cognitive biases faced by clinicians and surrogate decision-makers, which may contribute to prognostic discordance; and ambiguity regarding appropriate endpoints for the TLT. Further study is needed to understand clinician behaviors and surrogate preferences for prognostic communication and how to optimally integrate TLTs into the care of older adults with TBI.

Fluid biomarkers and neuroimaging in mild traumatic brain injury: current uses and potential future directions for clinical use in emergency medicine

Mild traumatic brain injury is a common presentation to the emergency department, with current management often focusing on determining whether a patient requires a CT head scan and/or neurosurgical intervention. There is a growing appreciation that approximately 20%-40% of patients, including those with a negative (normal) CT, will develop ongoing symptoms for months to years, often termed post-concussion syndrome. Owing to the requirement for improved diagnostic and prognostic mechanisms, there has been increasing evidence concerning the utility of both imaging and blood biomarkers.Blood biomarkers offer the potential to better risk stratify patients for requirement of neuroimaging than current clinical decisions rules. However, improved assessment of the clinical utility is required prior to wide adoption. MRI, using clinical sequences and advanced quantitative methods, can detect lesions not visible on CT in up to 30% of patients that may explain, at least in part, some of the ongoing problems. The ability of an acute biomarker (be it imaging, blood or other) to highlight those patients at greater risk of ongoing deficits would allow for greater personalisation of follow-up care and resource allocation.We discuss here both the current evidence and the future potential clinical usage of blood biomarkers and advanced MRI to improve diagnostic pathways and outcome prediction following mild traumatic brain injury.

Post-Concussion Symptoms Rule: Derivation and Validation of a Clinical Decision Rule for Early Prediction of Persistent Symptoms after a Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) is a common problem. Depending on diagnostic criteria, 13 to 62% of those patients develop persistent post-concussion symptoms (PPCS). The main objective of this prospective multi-center study is to derive and validate a clinical decision rule (CDR) for the early prediction of PPCS. Patients aged ≥14 years were included if they presented to one of our seven participating emergency departments (EDs) within 24 h of an mTBI. Clinical data were collected in the ED, and symptom evolution was assessed at 7, 30 and 90 days post-injury using the Rivermead Post-Concussion Questionnaire (RPQ). The primary outcome was PPCS at 90 days after mTBI. A predictive model called the Post-Concussion Symptoms Rule (PoCS Rule) was developed using the methodological standards for CDR. Of the 1083 analyzed patients (471 and 612 for the derivation and validation cohorts, respectively), 15.6% had PPCS. The final model included the following factors assessed in the ED: age, sex, history of prior TBI or mental health disorder, headache in ED, cervical sprain and hemorrhage on computed tomography. The 7-day follow-up identified additional risk factors: headaches, sleep disturbance, fatigue, sensitivity to light, and RPQ ≥21. The PoCS Rule had a sensitivity of 91.4% and 89.6%, a specificity of 53.8% and 44.7% and a negative predictive value of 97.2% and 95.8% in the derivation and validation cohorts, respectively. The PoCS Rule will help emergency physicians quickly stratify the risk of PPCS in mTBI patients and better plan post-discharge resources.

Defining Acute Traumatic Encephalopathy: Methods of the "HEAD Injury Serum Markers and Multi-Modalities for Assessing Response to Trauma" (HeadSMART II) Study

Despite an estimated 2.8 million annual ED visits, traumatic brain injury (TBI) is a syndromic diagnosis largely based on report of loss of consciousness, post-traumatic amnesia, and/or confusion, without readily available objective diagnostic tests at the time of presentation, nor an ability to identify a patient's prognosis at the time of injury. The recognition that “mild” forms of TBI and even sub-clinical impacts can result in persistent neuropsychiatric consequences, particularly when repetitive, highlights the need for objective assessments that can complement the clinical diagnosis and provide prognostic information about long-term outcomes. Biomarkers and neurocognitive testing can identify brain injured patients and those likely to have post-concussive symptoms, regardless of imaging testing results, thus providing a physiologic basis for a diagnosis of acute traumatic encephalopathy (ATE). The goal of the HeadSMART II (HEAD injury Serum markers and Multi-modalities for Assessing Response to Trauma) clinical study is to develop an in-vitro diagnostic test for ATE. The BRAINBox TBI Test will be developed in the current clinical study to serve as an aid in evaluation of patients with ATE by incorporating blood protein biomarkers, clinical assessments, and tools to measure, identify, and define associated pathologic evidence and neurocognitive impairments. This protocol proposes to collect data on TBI subjects by a multi-modality approach that includes serum biomarkers, clinical assessments, neurocognitive performance, and neuropsychological characteristics, to determine the accuracy of the BRAINBox TBI test as an aid to the diagnosis of ATE, defined herein, and to objectively determine a patient's risk of developing post-concussive symptoms.

A Prognostic Model for Predicting One-Month Outcomes among Emergency Department Patients with Mild Traumatic Brain Injury and a Presenting Glasgow Coma Scale of Fifteen

The lack of well-performing prognostic models for early prognostication of outcomes remains a major barrier to improving the clinical care of patients with mild traumatic brain injury (mTBI). We aimed to derive a prognostic model for predicting incomplete recovery at 1-month in emergency department (ED) patients with mTBI and a presenting Glasgow Coma Scale (GCS) score of 15 who were enrolled in the HeadSMART (Head Injury Serum Markers for Assessing Response to Trauma) study. The derivation cohort included 355 participants with complete baseline (day-of-injury) and follow-up data. The primary outcome measure was the Glasgow Outcome Scale Extended (GOSE) at 1-month and incomplete recovery was defined as a GOSE <8. At 1-month post-injury, incomplete recovery was present in 58% (n = 205) of participants. The final multi-variable logistic regression model included six variables: age in years (odds ratio [OR] = 0.98; 95% confidence interval [CI]: 0.97-1.00), positive head CT (OR = 4.42; 95% CI: 2.21-9.33), history of depression (OR = 2.59; 95% CI: 1.47-4.69), and self-report of moderate or severe headache (OR = 2.49; 95% CI: 1.49-4.18), difficulty concentrating (OR = 3.17; 95% CI: 1.53-7.04), and photophobia (OR = 4.17; 95% CI: 2.08-8.92) on the day-of-injury. The model was validated internally using bootstrap resampling (1000 resamples), which revealed a mean over-optimism value of 0.01 and an optimism-corrected area under the curve (AUC) of 0.79 (95% CI: 0.75-0.85). A prognostic model for predicting incomplete recovery among ED patients with mTBI and a presenting GCS of 15 using easily obtainable clinical and demographic variables has acceptable discriminative accuracy. External validation of this model is warranted.

Neuroanatomical Substrates and Symptoms Associated With Magnetic Resonance Imaging of Patients With Mild Traumatic Brain Injury

Importance

Persistent symptoms after mild traumatic brain injury (mTBI) represent a major public health problem.

Objective

To identify neuroanatomical substrates of mTBI and the optimal timing for magnetic resonance imaging (MRI).

Design, Setting, and Participants

This prospective multicenter cohort study encompassed all eligible patients from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study (December 19, 2014, to December 17, 2017) and a local cohort (November 20, 2012, to December 19, 2013). Patients presented to the hospital within 24 hours of an mTBI (Glasgow Coma Score, 13-15), satisfied local criteria for computed tomographic scanning, and underwent MRI scanning less than 72 hours (MR1) and 2 to 3 weeks (MR2) after injury. In addition, 104 control participants were enrolled across all sites. Data were analyzed from January 1, 2019, to December 31, 2020.

Exposure

Mild TBI.

Main Outcomes and Measures

Volumes and diffusion parameters were extracted via automated bespoke pipelines. Symptoms were measured using the Rivermead Post Concussion Symptoms Questionnaire in the short term and the extended Glasgow Outcome Scale at 3 months.

Results

Among the 81 patients included in the analysis (73 CENTER-TBI and 8 local), the median age was 45 (interquartile range [IQR], 24-59; range, 14-85) years, and 57 (70.4%) were male. Structural sequences were available for all scans; diffusion data, for 73 MR1 and 79 MR2 scans. After adjustment for multiple comparisons between scans, visible lesions did not differ significantly, but cerebral white matter volume decreased (MR2:MR1 ratio, 0.98; 95% CI, 0.96-0.99) and ventricular volume increased (MR2:MR1 ratio, 1.06; 95% CI, 1.02-1.10). White matter volume was within reference limits on MR1 scans (patient to control ratio, 0.99; 95% CI, 0.97-1.01) and reduced on MR2 scans (patient to control ratio, 0.97; 95% CI, 0.95-0.99). Diffusion parameters changed significantly between scans in 13 tracts, following 1 of 3 trajectories. Symptoms measured by Rivermead Post Concussion Symptoms Questionnaire scores worsened in the progressive injury phenotype (median, +5.00; IQR, +2.00 to +5.00]), improved in the minimal change phenotype (median, -4.50; IQR, -9.25 to +1.75), and were variable in the pseudonormalization phenotype (median, 0.00; IQR, -6.25 to +9.00) (P = .02). Recovery was favorable for 33 of 65 patients (51%) and was more closely associated with MR1 than MR2 (area under the curve, 0.87 [95% CI, 0.78-0.96] vs 0.75 [95% CI, 0.62-0.87]; P = .009).

Conclusions and Relevance

These findings suggest that advanced MRI reveals potential neuroanatomical substrates of mTBI in white matter and is most strongly associated with odds of recovery if performed within 72 hours, although future validation is required.

Predictive Value of Subacute Heart Rate Variability for Determining Outcome Following Adolescent Concussion

Objective assessments of concussion recovery are crucial for facilitating effective clinical management. However, predictive tools for determining adolescent concussion outcomes are currently limited. Research suggests that heart rate variability (HRV) represents an indirect and objective marker of central and peripheral nervous system integration. Therefore, it may effectively identify underlying deficits and reliably predict the symptomology following concussion. Thus, the present study sought to evaluate the relationship between HRV and adolescent concussion outcomes. Furthermore, we sought to examine its predictive value for assessing outcomes. Fifty-five concussed adolescents (12–17 years old) recruited from a local sports medicine clinic were assessed during the initial subacute evaluation (within 15 days postinjury) and instructed to follow up for a post-acute evaluation. Self-reported clinical and depressive symptoms, neurobehavioral function, and cognitive performance were collected at each timepoint. Short-term HRV metrics via photoplethysmography were obtained under resting conditions and physiological stress. Regression analyses demonstrated significant associations between HRV metrics, clinical symptoms, neurobehavioral function, and cognitive performance at the subacute evaluation. Importantly, the analyses illustrated that subacute HRV metrics significantly predicted diminished post-acute neurobehavioral function and cognitive performance. These findings indicate that subacute HRV metrics may serve as a viable predictive biomarker for identifying underlying neurological dysfunction following concussion and predict late cognitive outcomes.