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

What traditional neuropsychological assessment got wrong about mild traumatic brain injury. IV: clinical applications and future directions

PRIMARY OBJECTIVE

Part IV concludes this four-part review of 'What Traditional Neuropsychological Assessment Got Wrong About Mild Traumatic Brain Injury,' with a focus on clinical applications and future directions.

METHODS AND PROCEDURES

These reviews have highlighted the limitations of traditional neuropsychological assessment methods, particularly in the evaluation of the patient with mild traumatic brain injury (mTBI), and especially within the context of all of the 21st Century advances in neuroimaging, quantification and network neuroscience.

MAIN OUTCOME AND RESULTS

How advanced neuroimaging technology and contemporary network neuroscience can be applied to assessing the mTBI patient at this time along with neuroimaging of the future are reviewed. The current status of computerized neuropsychological test (CNT) development is reviewed as it applies to mTBI assessment. Likewise, how the future of various types of virtual reality (VR), artificial intelligence (AI), wearable sensors, and markerless gaming technology could enhance the mTBI CNT assessment tool box of the future is reviewed.

CONCLUSIONS

The review concludes with some aspirational statements about how improvements along with novel CNT methods could be developed and integrated with advanced neuroimaging technologies in the future to be tailored to meet the needs of the mTBI patient.

The Impact of Background Music on Flow, Work Engagement and Task Performance: A Randomized Controlled Study

The widespread adoption of background music in workplaces contrasts with the inconsistent empirical evidence regarding its cognitive effects, particularly concerning how music types influence the sequential pathway from flow states to work engagement and task performance. While prior research identifies flow and engagement as potential mediators, theoretical conflicts persist regarding their temporal dynamics and susceptibility to auditory habituation. This study tested three hypotheses: (1) music type indirectly affects performance through flow-engagement mediation, (2) high-arousal music impairs while structured compositions (e.g., Mozart's K448) enhance this pathway, and (3) repeated exposure diminishes music's efficacy. A two-phase longitudinal experiment with 428 Chinese undergraduates employed structural equation modeling (SEM) to analyze data from randomized groups (control, high-arousal, low-arousal, and Mozart K448), completing Backward Digit Span tasks under controlled auditory conditions. The results confirmed Mozart K448's superior immediate mediation effect (β = 0.118, 95% CI [0.072, 0.181]) compared to high-arousal music's detrimental impact (β = -0.112, 95% CI [-0.182, -0.056]), with flow fully mediating engagement's influence on performance. A longitudinal analysis revealed a 53% attenuation in Mozart's flow-enhancing effect after a 30-day familiarization (B = 0.150 vs. baseline 0.321), though residual benefits persisted. These findings reconcile the cognitive tuning and arousal-mood hypotheses by proposing a hybrid model where music initially operates through a novelty-driven dopamine release before transitioning to schema-based cognitive priming. Practically, the results advocate tiered auditory strategies: deploying structured music during skill acquisition phases while rotating selections to counter habituation. The study highlights the cultural specificity in auditory processing, challenging universal prescriptions and underscoring the need for localized music policies. By integrating flow theory with neurocognitive habituation models, this research advances evidence-based guidelines for optimizing workplace auditory environments.

How Are TBI Symptoms Interconnected? A Network Analysis Approach

BACKGROUND

Many patients with traumatic brain injury (TBI) across all levels of severity experience persistent psycho-emotional, cognitive, and somatic symptoms. Psychological network theory views disorders as intricate systems rather than discrete diseases. This study employs an exploratory network analysis method to uncover potential causal links among long-term TBI symptoms.

METHODS

We examined persistent symptoms using secondary data from 250 TBI patients undergoing an inpatient "brain check" procedure. We constructed two partial correlation networks: one for the entire sample and another for a mild TBI subgroup, each consisting of 14 symptoms and three covariates. The symptoms and their connections were visualized in network graphs to identify potential causal, and structural indicators and centrality indices were calculated.

RESULTS

The analysis revealed two dense networks characterized by multiple complex connections. In the overall network, symptoms are clustered into psycho-emotional and cognitive communities, with attention deficits serving as a crucial link between them. One finding was that self-reported cognitive impairments do not align with objectively measured deficits. Within the mild TBI subgroup, PTSD emerges as a central node in the network.

CONCLUSION

Network analysis reveals the multidimensional and reciprocal nature of long-term TBI symptoms. Attention deficits bridge cognitive and psycho-emotional areas, whereas psycho-emotional symptoms influence self-perceived performance. Self-reported cognitive impairments should be emphasized in therapy as they are linked rather to sleep, visual disturbances, and anxiety than to objective deficits. Network analysis is valuable for understanding TBI symptom complexity and exploring treatment options. Future research should utilize longitudinal designs to validate our findings.

Neurobehavioral Symptoms Partially Mediate the Effects of Depression and PTSD on Participation for Veterans With Mild Traumatic Brain Injury: A Cross-Sectional Study

OBJECTIVE

To examine whether neurobehavioral symptoms mediate the relationship between comorbid mental health conditions (major depressive disorder [MDD] and/or posttraumatic stress disorder [PTSD]) and participation restriction among Veterans with mild traumatic brain injury (mTBI).

SETTING

Veterans Health Administration (VHA).

PARTICIPANTS

National sample of Veterans with mTBI who received VHA outpatient care between 2012 and 2020.

DESIGN

Secondary data analysis of VHA clinical data. We specified a latent variable path model to estimate relationships between: (1) comorbid mental health conditions and 3 latent indicators of neurobehavioral symptoms (vestibular-sensory; mood-behavioral; cognitive); (2) latent indicators of neurobehavioral symptoms and 2 latent indicators of participation restriction (social and community participation; productivity); and (3) comorbid mental health conditions and participation restriction.

MAIN MEASURES

International Classification of Diseases codes, Neurobehavioral Symptom Inventory, and Mayo-Portland Adaptability Inventory Participation Index to measure mental health conditions, neurobehavioral symptoms, and participation restrictions, respectively.

RESULTS

Indirect effect estimates indicated that comorbid MDD and/or PTSD was associated with greater social and community participation restrictions, as mediated by mood-behavioral (β = .22-.33; 99% CI 0.18-0.4; small to medium effect) and cognitive symptoms (β = .08-.13; 99% CI 0.05-0.18; small effect), and with greater productivity restrictions, as mediated by vestibular-sensory (β = .06-.11; 99% CI 0.04-0.15; small effect) and cognitive symptoms (β = .08-.13; 99% CI 0.05-0.18; small effect). Direct effect estimates indicated that comorbid MDD and/or PTSD was associated with greater challenges with both social and community participation (β = .19-.40; 99% CI 0.12-0.49; small to medium effect) and productivity (β = .08-.44; 99% CI -0.02 to 0.55; small to medium effect).

CONCLUSION

Neurobehavioral symptoms partially mediated the impact of MDD and/or PTSD on participation restrictions among Veterans with mTBI. These findings advance the understanding of explanatory mechanisms underlying participation challenges among Veterans with comorbid mTBI and mental health challenges, thereby informing the development of tailored intervention strategies.

Longitudinal changes following the introduction of socially assistive robots in nursing homes: a qualitative study with ICF framework and causal loop diagramming

BACKGROUND

Socially assistive robots introduced in nursing care settings have multidimensional psychological impacts on care recipients and caregivers. This study aims to explore the longitudinal changes induced by socially assistive robots, focusing on a chain of human behaviors.

METHODS

In this qualitative study, nine participants from two nursing homes who had experience in manipulating socially assistive robots were interviewed in a semi-structured focus group using a topic guide to explore the changes in care recipients and caregivers. Following the framework analysis method, the transcripts were coded using the International Classification of Functioning, Disability, and Health (ICF). The identified codes were charted for each side-care recipients and caregivers sides- using a causal loop diagram, a tool used to visualize nonlinear dynamics in complex systems.

RESULTS

Three and seven kinds of codes in the domains of "body functions" and "activities and participation", respectively, were identified on the care recipients' side; whereas on the caregivers' side, one and five kinds of codes in the domains of "body functions" and "activities and participation", respectively, were found. The codes obtained from the facility with longer experience were represented graphically as a reinforcing feedback loop, in which favorable changes were amplified in a chain of events. Robot use directly changed the mental functions of care recipients, and the caregivers' perceptions of these positive changes led to their own emotional and behavioral changes, which would reduce the burden of care. Moreover, the findings suggest that sharing information regarding these changes and objectively recognizing the effectiveness of robots among staff members can be the key to continuous robot use in nursing care settings. Conversely, the figure obtained from the novice facility shows fragmented chain relationships of the codes, indicating that all the effects of robot use are recognizable and form a chain reaction after continuous robot use for more than several months.

CONCLUSIONS

This study revealed important aspects regarding the longitudinal effects of socially assistive robots in nursing care settings. These implications should be broadly implemented for effective robot use and reduction of the burden of care in nursing care settings.

CLINICAL TRIAL NUMBER

Not applicable.

If things were simple, word would have gotten around. Can complexity science help us improve pediatric research?

Complexity science is a discipline which explores how complex systems behave and how we interact with them. Though it is widely implemented outside medicine, particularly in the sciences involving human behavior, but also in the natural sciences such as physics and biology, there are only a few applications within medical research. We propose that complexity science can provide new and helpful perspectives on complex pediatric medical problems. It can help us better understand complex systems and develop ways to cope with their inherent unpredictabilities. In this article, we provide a brief introduction of complexity science, explore why many medical problems can be considered 'complex', and discuss how we can apply this perspective to pediatric research. IMPACT: Current methods in pediatric research often focus on single mechanisms or interventions instead of systems, and tend to simplify complexity. This may not be appropriate. Complexity science provides a framework and a toolbox to better address complex problems. This review provides a starting point for the application of complexity science in pediatric research.

An Objective Assessment of Neuromotor Control Using a Smartphone App After Repeated Subconcussive Blast Exposure

Subconcussive blast exposure has been shown to alter neurological functioning. However, the extent to which neurological dysfunction persists after blast exposure is unknown. This longitudinal study examined the potential short- and long-term effects of repeated subconcussive blast exposure on neuromotor performance from heavy weapons training in military personnel. A total of 214 participants were assessed; 137 were exposed to repeated subconcussive blasts and 77 were not exposed to blasts (controls). Participants completed a short stepping-in-place task while an Android smartphone app placed on their thigh recorded movement kinematics. We showed acute suppression of neuromotor variability 6 h after subconcussive blast exposure, followed by a rebound to levels not different from baseline at the 72 h, 2-week, and 3-month post-tests. It is postulated that this suppression of neuromotor variability results from a reduction in the functional degrees of freedom from the subconcussive neurological insult. It is important to note that this change in behavior is short-lived, with a return to pre-blast exposure movement kinematics within 72 h.

Persistent MRI Findings Unique to Blast and Repetitive Mild TBI: Analysis of the CENC/LIMBIC Cohort Injury Characteristics

INTRODUCTION

MRI represents one of the clinical tools at the forefront of research efforts aimed at identifying diagnostic and prognostic biomarkers following traumatic brain injury (TBI). Both volumetric and diffusion MRI findings in mild TBI (mTBI) are mixed, making the findings difficult to interpret. As such, additional research is needed to continue to elucidate the relationship between the clinical features of mTBI and quantitative MRI measurements.

MATERIAL AND METHODS

Volumetric and diffusion imaging data in a sample of 976 veterans and service members from the Chronic Effects of Neurotrauma Consortium and now the Long-Term Impact of Military-Relevant Brain Injury Consortium observational study of the late effects of mTBI in combat with and without a history of mTBI were examined. A series of regression models with link functions appropriate for the model outcome were used to evaluate the relationships among imaging measures and clinical features of mTBI. Each model included acquisition site, participant sex, and age as covariates. Separate regression models were fit for each region of interest where said region was a predictor.

RESULTS

After controlling for multiple comparisons, no significant main effect was noted for comparisons between veterans and service members with and without a history of mTBI. However, blast-related mTBI were associated with volumetric reductions of several subregions of the corpus callosum compared to non-blast-related mTBI. Several volumetric (i.e., hippocampal subfields, etc.) and diffusion (i.e., corona radiata, superior longitudinal fasciculus, etc.) MRI findings were noted to be associated with an increased number of repetitive mTBIs versus.

CONCLUSIONS

In deployment-related mTBI, significant findings in this cohort were only observed when considering mTBI sub-groups (blast mechanism and total number/dose). Simply comparing healthy controls and those with a positive mTBI history is likely an oversimplification that may lead to non-significant findings, even in consortium analyses.

ボバースフレームワーク:をむのにするシステマチックサイエンスのアプローチ

現在、発達領域で推奨されているボバース臨床推論フレームワーク(Bobath Clinical Reasoning Framework: BCRF)によるボバース実践を、システム科学のレンズによって概念化し、小児期発症の障害に関連する様々な変数の相互関係・相関依存に対する全人的観点を提供する。BCRFはICFの各領域間の関係性を理解し、それぞれがどのように影響を与え、どのように影響を受けるのかを理解する助けとなる臨床推論の詳細なフレームワークである。BCRFは介入計画へとつながる観察に基づく学際的なシステムであり、実践的な推論のアプローチである。BCRFにより脳性麻痺(Cerebral Palsy: CP)などの障害における複雑な状況を全人的に理解し、神経学的障害がある人々の生涯にわたるマネジメントおよびハビリテーションの基盤を持つことができる。BCRFが用いる臨床推論は、個々人およびその社会的環境、とくに家族単位で見られる重要な文脈的要因を重視している。定型発達・非定型発達、病態生理(感覚運動・認知・行動)、神経科学の相互関連性、および、心身機能・身体構造レベルの構成要素がどのように活動・参加レベルに影響を与えるのか、BCRFはその理解に根差している。BCRFにとって不可欠なシステム科学system science※1)のモデルはCPの複雑性を理解および対応を進める有用な方法であり、何よりも大切な目標とはあらゆる文脈であらゆる個々人の生きた経験を最適化することである。.

Le cadre de raisonnement clinique Bobath: un modèle de science des systèmes pour aborder la complexité des troubles neurodéveloppementaux, y compris la paralysie cérébrale

La pratique Bobath actuelle telle qu'elle est recommandée dans le cadre du Bobath Clinical Reasoning Framework (BCRF) se base sur une application clinique de la science des systèmes. Elle offre une perspective holistique des relations entre les variables qui sont associées à l'apparition d'un handicap chez l'enfant. Le BCRF est un cadre de raisonnement clinique qui peut aider à comprendre les relations entre les domaines de la Classification Internationale du Fonctionnement, du Handicap et de la Santé. C'est un système d'observation transdisciplinaire de raisonnement pratique qui vise à proposer un plan d'intervention. Plus généralement, le BCRF permet une compréhension holistique de la complexité des situations associées à des troubles tels que la paralysie cérébrale et indique des choix d'adaptation et de prise en charge tout au long de la vie des personnes vivant avec des troubles neurologiques. Ce raisonnement clinique se base sur les facteurs contextuels importants de l'individu et de son environnement social, principalement la cellule familiale, et sur une compréhension des relations entre le développement typique et atypique, la physiopathologie (sensorimotrice, cognitive, comportementale) et les neurosciences, ainsi que sur l'impact des fonctions et des structures corporelles sur les activités et la participation. Le modèle de la science des systèmes du BCRF permet d'aborder la complexité de la paralysie cérébrale, avec l'objectif global d'optimiser l'expérience vécue par chaque individu dans chaque contexte.

El marco de razonamiento clínico de Bobath: Un modelo de ciencia de sistemas para abordar la complejidad de los trastornos del neurodesarrollo incluida la parálisis cerebral

La actual práctica de desarrollo Bobath recomendada dentro del Marco de Razonamiento Clínico Bobath (BCRF) puede conceptualizarse utilizando la visión de la ciencia de los sistemas. Proporciona, así, una perspectiva holística de la interrelación e interconexión de las variables asociadas con la discapacidad aparecida durante la infancia. El BCRF se define como un marco exhaustivo de razonamiento clínico que puede aplicarse para ayudar a comprender las relaciones entre los dominios de la Clasificación Internacional del Funcionamiento, de la Discapacidad y de la Salud, cómo se puede influir en esos dominios y cómo influyen entre sí. El BCRF es un sistema de observación transdisciplinario y de razonamiento práctico que da lugar a un plan de intervención. Esto proporciona una comprensión holística de la complexidad de las situaciones asociadas a trastornos como la parálisis cerebral (PC) y la base para la gestión y habilitación a lo largo de la vida de personas que viven con trastornos neurológicos. El razonamiento clínico utilizado por el BCRF se basa en los importantes factores contextuales del individuo y su entorno social, principalmente la unidad familiar. Se basa en la comprensión de las interrelaciones entre el desarrollo típico y atípico, la fisiopatología (sensoriomotora, cognitiva, conductual) y la neurociencia, así como el impacto de funciones y estructuras corporales sobre la actividad y la participación. El modelo de ciencia de sistemas del BCRF es una forma útil de comprender y responder a la complejidad de la parálisis cerebral, con el objetivo global de optimizar la experiencia vivida de todo individuo en cualquier contexto.

O Quadro de Raciocínio Clínico Bobath: Uma abordagem de ciência de sistemas para a complexidade das condições do neurodesenvolvimento, incluindo a paralisia cerebral

Esta revisão descreve um modelo de prática pediátrica recomendada do Bobath, o Quadro de Raciocínio Clínico Bobath (QRCB), e explica como esse conhecimento contribui para a área de habilitação em distúrbios pediátricos. A ciência de sistemas proporciona uma nova maneira de concetualizar a paralisia cerebral como uma condição complexa. Ela foi aplicada ao QRCB para ilustrar uma perspetiva holística sobre a inter-relação e interconexão das variáveis associadas à PC. O modelo de ciência de sistemas adotado pelo QRCB é uma forma promissora de construir uma estrutura abrangente que engloba a complexidade da PC e possibilitará pesquisas mais robustas.

Bobath Klinik Gerekçelendirme Çerçevesi: Serebral palsi dahil nörogelişimsel durumların karmaşıklığında sistemler bilimi yaklaşımı

Bobath Klinik Gerekçelendirme Çerçevesi (BKGÇ) içerisindeki önerilen güncel gelişimsel Bobath uygulaması sistemler bilimi merceği kullanılarak kavramsallaştırılabilir ve bunu çocukluk çağı engelliliği ile ilişkilendirilen değişkenlerin birbirine bağlılığı ve etkileşimine bütüncül bir bakış açısıyla sağlar. BKGÇ, İşlevsellik, Yetiyitimi ve Sağlığın Uluslararası Sınıflandırması (ICF)’nın alt boyutları arasındaki ilişkiyi ve bu alt boyutların birbirini nasıl etkilediğini anlamak için uygulanabilen derinlemesine bir klinik gerekçelendirme çerçevesi olarak tanımlanmaktadır. BKGÇ, bir tedavi planı ile sonuçlanan klinik gerekçelendirme ve transdisipliner gözlemsel bir sistemdir. Bu sistem ise, serebral palsi (SP) gibi bozuklukların karmaşıklığını anlamak için bütüncül bir anlayış sunar ve nörolojik bozukluğu olan bireylerin yaşam boyu tedavisi ve rehabilitasyonu için temel oluşturur. BKGÇ tarafından kullanılan klinik gerekçelendirme, başta aile birimi olmak üzere bireyin ve sosyal çevresinin önemli bağlamsal faktörlerine dayanmaktadır. Tipik ve atipik gelişim, patofizyoloji (sensorimotor, bilişsel, davranışsal) ve sinirbilim arasındaki karşılıklı ilişkilerin ve bu vücut yapı ve fonksiyonlarının aktivite ve katılım üzerindeki etkisinin anlaşılmasına dayanır. BKGÇ'nin ayrılmaz bir parçası olan sistemler bilimi modeli, SP'nin karmaşıklığını anlamak ve buna yanıt vermek için yararlı bir yoldur; kapsayıcı hedef, herhangi bir bağlamda herhangi bir bireyin yaşadığı deneyimi optimize etmektir.

Mapping complex public health problems with causal loop diagrams

This paper presents causal loop diagrams (CLDs) as tools for studying complex public health problems like health inequality. These problems often involve feedback loops-a characteristic of complex systems not fully integrated into mainstream epidemiology. CLDs are conceptual models that visualize connections between system variables. They are commonly developed through literature reviews or participatory methods with stakeholder groups. These diagrams often uncover feedback loops among variables across scales (e.g. biological, psychological and social), facilitating cross-disciplinary insights. We illustrate their use through a case example involving the feedback loop between sleep problems and depressive symptoms. We outline a typical step-by-step process for developing CLDs in epidemiology. These steps are defining a specific problem, identifying the key system variables involved, mapping these variables and analysing the CLD to find new insights and possible intervention targets. Throughout this process, we suggest triangulating between diverse sources of evidence, including domain knowledge, scientific literature and empirical data. CLDs can also be evaluated to guide policy changes and future research by revealing knowledge gaps. Finally, CLDs may be iteratively refined as new evidence emerges. We advocate for more widespread use of complex systems tools, like CLDs, in epidemiology to better understand and address complex public health problems.

The Bobath Clinical Reasoning Framework: A systems science approach to the complexity of neurodevelopmental conditions, including cerebral palsy

The current recommended developmental Bobath practice within the Bobath Clinical Reasoning Framework (BCRF) can be conceptualized using the lens of systems science, thereby providing a holistic perspective on the interrelatedness and interconnectedness of the variables associated with childhood-onset disability. The BCRF is defined as an in-depth clinical reasoning framework that can be applied to help understand the relationships between the domains of the International Classification of Functioning, Disability and Health, how those domains can be influenced, and how they impact each other. The BCRF is a transdisciplinary observational system and practical reasoning approach that results in an intervention plan. This provides a holistic understanding of the complexity of situations associated with disorders such as cerebral palsy (CP) and the basis for the lifelong management and habilitation of people living with neurological disorders. The clinical reasoning used by the BCRF draws on the important contextual factors of the individual and their social environment, primarily the family unit. It is rooted in an understanding of the interrelationships between typical and atypical development, pathophysiology (sensorimotor, cognitive, behavioural), and neuroscience, and the impact of these body structure and function constructs on activity and participation. The systems science model integral to the BCRF is a useful way forward in understanding and responding to the complexity of CP, the overarching goal being to optimize the lived experience of any individual in any context.

The need for systems thinking to advance Alzheimer's disease research

Despite extensive research efforts to mechanistically understand late-onset Alzheimer's disease (LOAD) and other complex mental health disorders, curative treatments remain elusive. We emphasize the multiscale multicausality inherent to LOAD, highlighting the interplay between interconnected pathophysiological processes and risk factors. Systems thinking methods, such as causal loop diagrams and systems dynamic models, offer powerful means to capture and study this complexity. Recent studies developed and validated a causal loop diagram and system dynamics model using multiple longitudinal data sets, enabling the simulation of personalized interventions on various modifiable risk factors in LOAD. The results indicate that targeting factors like sleep disturbance and depressive symptoms could be promising and yield synergistic benefits. Furthermore, personalized interventions showed significant potential, with top-ranked intervention strategies differing significantly across individuals. We argue that systems thinking approaches can open new prospects for multifactorial precision medicine. In future research, systems thinking may also guide structured, model-driven data collection on the multiple interactions in LOAD's complex multicausality, facilitating theory development and possibly resulting in effective prevention and treatment options.

Using network analysis to identify leverage points based on causal loop diagrams leads to false inference

Network analysis is gaining momentum as an accepted practice to identify which factors in causal loop diagrams (CLDs)-mental models that graphically represent causal relationships between a system's factors-are most likely to shift system-level behaviour, known as leverage points. This application of network analysis, employed to quantitatively identify leverage points without having to use computational modelling approaches that translate CLDs into sets of mathematical equations, has however not been duly reflected upon. We evaluate whether using commonly applied network analysis metrics to identify leverage points is justified, focusing on betweenness- and closeness centrality. First, we assess whether the metrics identify the same leverage points based on CLDs that represent the same system but differ in inferred causal structure-finding that they provide unreliable results. Second, we consider conflicts between assumptions underlying the metrics and CLDs. We recognise six conflicts suggesting that the metrics are not equipped to take key information captured in CLDs into account. In conclusion, using betweenness- and closeness centrality to identify leverage points based on CLDs is at best premature and at worst incorrect-possibly causing erroneous identification of leverage points. This is problematic as, in current practice, the results can inform policy recommendations. Other quantitative or qualitative approaches that better correspond with the system dynamics perspective must be explored.

Astrocytes in human central nervous system diseases: a frontier for new therapies

Astroglia are a broad class of neural parenchymal cells primarily dedicated to homoeostasis and defence of the central nervous system (CNS). Astroglia contribute to the pathophysiology of all neurological and neuropsychiatric disorders in ways that can be either beneficial or detrimental to disorder outcome. Pathophysiological changes in astroglia can be primary or secondary and can result in gain or loss of functions. Astroglia respond to external, non-cell autonomous signals associated with any form of CNS pathology by undergoing complex and variable changes in their structure, molecular expression, and function. In addition, internally driven, cell autonomous changes of astroglial innate properties can lead to CNS pathologies. Astroglial pathophysiology is complex, with different pathophysiological cell states and cell phenotypes that are context-specific and vary with disorder, disorder-stage, comorbidities, age, and sex. Here, we classify astroglial pathophysiology into (i) reactive astrogliosis, (ii) astroglial atrophy with loss of function, (iii) astroglial degeneration and death, and (iv) astrocytopathies characterised by aberrant forms that drive disease. We review astroglial pathophysiology across the spectrum of human CNS diseases and disorders, including neurotrauma, stroke, neuroinfection, autoimmune attack and epilepsy, as well as neurodevelopmental, neurodegenerative, metabolic and neuropsychiatric disorders. Characterising cellular and molecular mechanisms of astroglial pathophysiology represents a new frontier to identify novel therapeutic strategies.

Improving outcome after paediatric concussion: challenges and possibilities

The term concussion has permeated mainstream media and household vocabulary mainly due to awareness regarding the risks of concussion in professional contact sports, yet it occurs across a variety of settings and ages. Concussion is prevalent in infants, preschoolers, children, and adolescents, and is a common presentation or reason for referral to primary care providers, emergency departments, and specialised trauma clinics. Its broad range of symptoms and sequelae vary according to multiple individual, environmental, and clinical factors and can lead to health and economic burden. More than 20 years of research into risk factors and consequences of paediatric concussion has revealed as many questions as answers, and scientific work and clinical cases continue to expose its complexity and heterogeneity. In this Review, we present empirical evidence for improving outcome after paediatric concussion. We consider work pertaining to both sports and other injury mechanisms to provide a perspective that should be viewed as complementary to publications focused specifically on sports concussion. Contemporary challenges in prevention, diagnosis, prognosis, and intervention are discussed alongside pathways and future directions for improving outcome.

Quantifying Fear Avoidance Behaviors in People With Concussion: A COSMIN-Informed Systematic Review

OBJECTIVE: The validity of existing fear avoidance behavior patient-reported outcome measures (PROMs) for concussion is unknown. This study aims to (1) identify PROMs that assess fear avoidance behavior in individuals with concussion and (2) assess the measurement properties of these PROMs. DESIGN: A systematic review of outcome measurement instruments using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist. LITERATURE SEARCH: We performed a systematic search of 7 databases. STUDY SELECTION CRITERIA: Studies were included if they assessed fear avoidance behavior (eg, kinesiophobia or cogniphobia) in participants with concussion, occurring in all settings (eg, sport, falls, assaults). DATA SYNTHESIS: Methodological quality of the PROMs was assessed using the COSMIN checklist, and the certainty of the evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. RESULTS: We identified 40 studies assessing fear avoidance. Four studies (n = 875 participants, representing 3 PROMs) were eligible for COSMIN assessment. Content validity for all PROMs was insufficient due to extreme risk of bias. The Fear Avoidance Short Form Scale demonstrated the greatest validity: moderate-certainty evidence for sufficient structural validity and internal consistency, and low-certainty evidence for measurement invariance. CONCLUSION: Current PROMs for measuring fear avoidance behaviors in people with concussion have insufficient content validity and should be used with caution in research and clinical practice. J Orthop Sports Phys Ther 2023;53(9):540-565. Epub: 10 August 2023. doi:10.2519/jospt.2023.11685.

Exploring the potential impact of multi-factor precision interventions in Alzheimer's disease with system dynamics

Numerous clinical trials based on a single-cause paradigm have not resulted in efficacious treatments for Alzheimer's disease (AD). Recently, prevention trials that simultaneously intervened on multiple risk factors have shown mixed results, suggesting that careful design is necessary. Moreover, intensive pilot precision medicine (PM) trial results have been promising but may not generalize to a broader population. These observations suggest that a model-based approach to multi-factor precision medicine (PM) is warranted. We systematically developed a system dynamics model (SDM) of AD for PM using data from two longitudinal studies (N=3660). This method involved a model selection procedure in identifying interaction terms between the SDM components and estimating individualized parameters. We used the SDM to explore simulated single- and double-factor interventions on 14 modifiable risk factors. We quantified the potential impact of double-factor interventions over single-factor interventions as 1.5 [95% CI: 1.5-2.6] and of SDM-based PM over a one-size-fits-all approach as 3.5 [3.1, 3.8] ADAS-cog-13 points in 12 years. Although the model remains to be validated, we tentatively conclude that multi-factor PM could come to play an important role in AD prevention.

Examining the interdisciplinary approach for treatment of persistent post-concussion symptoms in adults: a systematic review

BACKGROUND

The objective of this review is to examine the evidence for the interdisciplinary approach in treatment of persistent post-concussion symptoms in adults.

METHODS

This systematic literature search was undertaken according to the Preferred Reporting Items for Systematic and Meta-Analysis (PRISMA) guidelines. Five electronic databases were searched: CINAHL, Informit, ProQuest, PubMed and Scopus. After screening and quality assessment, the review included six studies published in English and peer-reviewed journals, between 2011 and 2021 to return contemporary evidence.

RESULTS

The results revealed that there was significant variation between measures used and the timing of the pre- and post-treatment assessment. The studies found an interdisciplinary approach to be beneficial, however, the challenges of inherent heterogeneity, lack of clarity for definitions and diagnosis, and mixed results were apparent. The interdisciplinary interventions applied in all identified studies were found to reduce post-concussion symptoms across the symptom subtypes: headache/migraine, vestibular, cognitive, ocular motor and anxiety/mood.

CONCLUSIONS

The results demonstrated evidence for a reduction in persistent post-concussion symptoms following interdisciplinary intervention. This evidence will inform health services, clinicians, sports administrators and researchers with regard to concussion clinic and rehabilitation team design and service delivery.

Towards the Development of a System Dynamics Model for the Prediction of Lower Extremity Injuries

Acute noncontact Lower Extremity (LE) injuries constitute a significant problem in team sports. Despite extensive research, current knowledge on the risk factors of LE injuries is limited to static simplistic models of instantaneous cause and effect relationships ignoring the time dimension and the embedded complexity of LE injuries. Even though complex systems approaches have been used in various cases to improve policy and intervention effectiveness, there is limited research on predicting and managing LE injuries. This creates an opportunity to fill the gap in the current literature by applying the System Dynamics (SD) methodology to model LE injuries. The proposed approach allows for synthesizing risk factors and examining their interaction. This paper makes the first step towards such an approach by developing a causal loop model revealing the etiology of LE injuries. A causal loop model for LE injuries is developed via an extensive literature review and brainstorming with experts. In contrast to the traditional static approaches, the proposed model reveals some of the complexity and nonlinear relationships of the various sports injury risk factors. The derived causal loop model may then be used to quantify these interactions and develop a simulation model. This will be achieved by operationalizing and incorporating the main risk factors that impact LE injuries in an integrated sports injury prediction model. In this way, plausible strategies for preventing LE injuries can be tested prior implementation and thereby achieve optimization of intervention programs.

Applying systems thinking to unravel the mechanisms underlying orthostatic hypotension related fall risk

Orthostatic hypotension (OH) is an established and common cardiovascular risk factor for falls. An in-depth understanding of the various interacting pathophysiological pathways contributing to OH-related falls is essential to guide improvements in diagnostic and treatment opportunities. We applied systems thinking to multidisciplinary map out causal mechanisms and risk factors. For this, we used group model building (GMB) to develop a causal loop diagram (CLD). The GMB was based on the input of experts from multiple domains related to OH and falls and all proposed mechanisms were supported by scientific literature. Our CLD is a conceptual representation of factors involved in OH-related falls, and their interrelatedness. Network analysis and feedback loops were applied to analyze and interpret the CLD, and quantitatively summarize the function and relative importance of the variables. Our CLD contains 50 variables distributed over three intrinsic domains (cerebral, cardiovascular, and musculoskeletal), and an extrinsic domain (e.g., medications). Between the variables, 181 connections and 65 feedback loops were identified. Decreased cerebral blood flow, low blood pressure, impaired baroreflex activity, and physical inactivity were identified as key factors involved in OH-related falls, based on their high centralities. Our CLD reflects the multifactorial pathophysiology of OH-related falls. It enables us to identify key elements, suggesting their potential for new diagnostic and treatment approaches in fall prevention. The interactive online CLD renders it suitable for both research and educational purposes and this CLD is the first step in the development of a computational model for simulating the effects of risk factors on falls.

Factors related to adverse long-term outcomes after mild traumatic brain injury in children: a scoping review

OBJECTIVE

To identify demographic, premorbid and injury-related factors, or biomarkers associated with long-term (≥3 months) adverse outcomes in children after mild traumatic brain injury (mTBI).

DESIGN

Scoping review of literature.

PATIENTS

Children and adolescents with mTBI.

RISK FACTORS

Any demographic, premorbid and injury-related factors, or biomarkers were included. We excluded genetic and treatment-related factors.

MAIN OUTCOME MEASURES

Postconcussion syndrome (PCS), recovery.

RESULTS

Seventy-three publications were included, reporting 12 long-term adverse outcomes, including PCS in 12 studies and recovery in 29 studies. Additional outcomes studied were symptom scores/severity (n=22), quality of life (n=9) and cognitive function (n=9). Forty-nine risk factors were identified across studies. Risk factors most often assessed were sex (n=28), followed by age (n=23), injury mechanism = (n=22) and prior mTBI (n=18). The influence of these and other risk factors on outcomes of mTBI were inconsistent across the reviewed literature.

CONCLUSIONS

The most researched risk factors are sex, age and mechanism of injury, but their effects have been estimated inconsistently and did not show a clear pattern. The most studied outcomes are recovery patterns and symptom severity. However, these may not be the most important outcomes for clinicians and patients. Future primary studies in this area should focus on patient-important outcomes. Population-based prospective studies are needed that address prespecified hypotheses on the relationship of risk factors with given outcomes to enable reliable prediction of long-term adverse outcomes for childhood mTBI.

Inflammatory cytokines associated with mild traumatic brain injury and clinical outcomes: a systematic review and meta-analysis

Mild traumatic brain injuries (mTBIs) trigger a neuroinflammatory response, which leads to perturbations in the levels of inflammatory cytokines, resulting in a distinctive profile. A systematic review and meta-analysis were conducted to synthesize data related to levels of inflammatory cytokines in patients with mTBI. The electronic databases EMBASE, MEDLINE, and PUBMED were searched from January 2014 to December 12, 2021. A total of 5,138 articles were screened using a systematic approach based on the PRISMA and R-AMSTAR guidelines. Of these articles, 174 were selected for full-text review and 26 were included in the final analysis. The results of this study demonstrate that within 24 hours, patients with mTBI have significantly higher levels of Interleukin-6 (IL-6), Interleukin-1 Receptor Antagonist (IL-1RA), and Interferon-γ (IFN-γ) in blood, compared to healthy controls in majority of the included studies. Similarly one week following the injury, patients with mTBI have higher circulatory levels of Monocyte Chemoattractant Protein-1/C-C Motif Chemokine Ligand 2 (MCP-1/CCL2), compared to healthy controls in majority of the included studies. The results of the meta-analysis also confirmed these findings by demonstrating significantly elevated blood levels of IL-6, MCP-1/CCL2, and Interleukin-1 beta (IL-1β) in the mTBI population compared to healthy controls (p < 0.0001), particularly in the acute stages (<7 days). Furthermore, it was found that IL-6, Tumor Necrosis Factor-alpha (TNF-α), IL-1RA, IL-10, and MCP-1/CCL2 were associated with poor clinical outcomes following the mTBI. Finally, this research highlights the lack of consensus in the methodology of mTBI studies that measure inflammatory cytokines in the blood, and also provides direction for future mTBI research.

Does Sleep Quality Influence Recovery Outcomes After Postconcussive Injury in Children and Adolescents?

OBJECTIVE

To determine whether objective parameters of sleep quality differ throughout recovery between children and adolescents who experienced an early return to school (RTS) and those who had a delayed RTS or did not return at all during the study period.

SETTING

Sleep parameters reflective of sleep quality were evaluated in participants' natural sleeping habitat throughout 9 weeks postinjury.

PARTICIPANTS

Ninety-four children and adolescents (aged 5-18 years) with diagnosed concussion.

DESIGN

Prospective cohort. Participants followed RTS protocols.

MAIN MEASURES

Actigraphy-derived estimates of total sleep time (TST), sleep efficiency (SE), wake after sleep onset (WASO), average arousal length (AAL), and number of arousals (NOAs) per hour were assessed. The length of time from injury until RTS was determined for each participant. Participants were categorized into an early RTS or delayed RTS group based on their time to RTS.

RESULTS

Both TST and SE were significantly greater in the early RTS group. WASO duration, AAL, and NOAs were significantly greater in the delayed RTS group. Differences between RTS groups were most apparent during weeks 1 to 5 postinjury.

CONCLUSIONS AND CLINICAL IMPLICATIONS

Participants who returned to school earlier had significantly better objective sleep quality than participants who experienced a delayed RTS. This study provides evidence in support of a relationship between sleep quality and time to RTS in children and adolescents with concussion. Considering early monitoring of sleep, education regarding sleep hygiene, and access to age-appropriate sleep interventions may be helpful in pediatric concussion recovery.

Simulating the multicausality of Alzheimer's disease with system dynamics

INTRODUCTION

In Alzheimer's disease (AD), cognitive decline is driven by various interlinking causal factors. Systems thinking could help elucidate this multicausality and identify opportune intervention targets.

METHODS

We developed a system dynamics model (SDM) of sporadic AD with 33 factors and 148 causal links calibrated with empirical data from two studies. We tested the SDM's validity by ranking intervention outcomes on 15 modifiable risk factors to two sets of 44 and 9 validation statements based on meta-analyses of observational data and randomized controlled trials, respectively.

RESULTS

The SDM answered 77% and 78% of the validation statements correctly. Sleep quality and depressive symptoms yielded the largest effects on cognitive decline with which they were connected through strong reinforcing feedback loops, including via phosphorylated tau burden.

DISCUSSION

SDMs can be constructed and validated to simulate interventions and gain insight into the relative contribution of mechanistic pathways.

System dynamics modeling for traumatic brain injury: Mini-review of applications

Traumatic brain injury (TBI) is a highly complex phenomenon involving a cascade of disruptions across biomechanical, neurochemical, neurological, cognitive, emotional, and social systems. Researchers and clinicians urgently need a rigorous conceptualization of brain injury that encompasses nonlinear and mutually causal relations among the factors involved, as well as sources of individual variation in recovery trajectories. System dynamics, an approach from systems science, has been used for decades in fields such as management and ecology to model nonlinear feedback dynamics in complex systems. In this mini-review, we summarize some recent uses of this approach to better understand acute injury mechanisms, recovery dynamics, and care delivery for TBI. We conclude that diagram-based approaches like causal-loop diagramming have the potential to support the development of a shared paradigm of TBI that incorporates social support aspects of recovery. When developed using adequate data from large-scale studies, simulation modeling presents opportunities for improving individualized treatment and care delivery.

Subacute and chronic proteomic and phosphoproteomic analyses of a mouse model of traumatic brain injury at two timepoints and comparison with chronic traumatic encephalopathy in human samples

Repetitive mild traumatic brain injury (r-mTBI) is the most widespread type of brain trauma worldwide. The cumulative injury effect triggers long-lasting pathological and molecular changes that may increase risk of chronic neurodegenerative diseases. R-mTBI is also characterized by changes in the brain proteome, where the majority of molecules altered early post-TBI are different from those altered at more chronic phases. This differentiation may contribute to the heterogeneity of available data on potential therapeutic targets and may present an obstacle in developing effective treatments. Here, we aimed to characterize a proteome profile of r-mTBI in a mouse model at two time points – 3 and 24 weeks post last TBI, as this may be a more relevant therapeutic window for individuals suffering negative consequences of r-mTBI. We identified a great number of proteins and phosphoproteins that remain continuously dysregulated from 3 to 24 weeks. These proteins may serve as effective therapeutic targets for sub-acute and chronic stages of post r-mTBI. We also compared canonical pathway activation associated with either total proteins or phosphoproteins and revealed that they both are upregulated at 24 weeks. However, at 3 weeks post-TBI, only pathways associated with total proteins are upregulated, while pathways driven by phosphoproteins are downregulated. Finally, to assess the translatability of our data, we compared proteomic changes in our mouse model with those reported in autopsied human samples of Chronic Traumatic Encephalopathy (CTE) patients compared to controls. We observed 39 common proteins that were upregulated in both species and 24 common pathways associated with these proteins. These findings support the translational relevance of our mouse model of r-mTBI for successful identification and translation of therapeutic targets.

Eye Movements in Mild Traumatic Brain Injury: Clinical Challenges

Mild traumatic brain injury (mTBI), also known as concussion, is a common injury which affects patients of all demographics. There is a global effort to accurately diagnose and identify patients at highest risk of prolonged symptom burden to facilitate appropriate rehabilitation efforts. Underreporting is common with large numbers not engaging with services, in addition to differences in treatment outcomes according to ethnicity, age, and gender. As patients recover, symptomology evolves which challenges rehabilitative efforts with no clear definition of 'recovered'. This review describes key areas in mTBI such as diagnostic challenges, epidemiology, prognosis, and pathophysiology which serves as an introduction to "Eye Movements in Mild Traumatic Brain Injury: Ocular Biomarkers."

Free-living gait does not differentiate chronic mTBI patients compared to healthy controls

Background

Physical function remains a crucial component of mild traumatic brain injury (mTBI) assessment and recovery. Traditional approaches to assess mTBI lack sensitivity to detect subtle deficits post-injury, which can impact a patient’s quality of life, daily function and can lead to chronic issues. Inertial measurement units (IMU) provide an opportunity for objective assessment of physical function and can be used in any environment. A single waist worn IMU has the potential to provide broad/macro quantity characteristics to estimate gait mobility, as well as more high-resolution micro spatial or temporal gait characteristics (herein, we refer to these as measures of quality). Our recent work showed that quantity measures of mobility were less sensitive than measures of turning quality when comparing the free-living physical function of chronic mTBI patients and healthy controls. However, no studies have examined whether measures of gait quality in free-living conditions can differentiate chronic mTBI patients and healthy controls. This study aimed to determine whether measures of free-living gait quality can differentiate chronic mTBI patients from controls.

Methods

Thirty-two patients with chronic self-reported balance symptoms after mTBI (age: 40.88 ± 11.78 years, median days post-injury: 440.68 days) and 23 healthy controls (age: 48.56 ± 22.56 years) were assessed for ~ 7 days using a single IMU at the waist on a belt. Free-living gait quality metrics were evaluated for chronic mTBI patients and controls using multi-variate analysis. Receiver operating characteristics (ROC) and Area Under the Curve (AUC) analysis were used to determine outcome sensitivity to chronic mTBI.

Results

Free-living gait quality metrics were not different between chronic mTBI patients and controls (all p > 0.05) whilst controlling for age and sex. ROC and AUC analysis showed stride length (0.63) was the most sensitive measure for differentiating chronic mTBI patients from controls.

Conclusions

Our results show that gait quality metrics determined through a free-living assessment were not significantly different between chronic mTBI patients and controls. These results suggest that measures of free-living gait quality were not impaired in our chronic mTBI patients, and/or, that the metrics chosen were not sensitive enough to detect subtle impairments in our sample.

Multi-tract multi-symptom relationships in pediatric concussion

Background

The heterogeneity of white matter damage and symptoms in concussion has been identified as a major obstacle to therapeutic innovation. In contrast, most diffusion MRI (dMRI) studies on concussion have traditionally relied on group-comparison approaches that average out heterogeneity. To leverage, rather than average out, concussion heterogeneity, we combined dMRI and multivariate statistics to characterize multi-tract multi-symptom relationships.

Methods

Using cross-sectional data from 306 previously concussed children aged 9-10 from the Adolescent Brain Cognitive Development Study, we built connectomes weighted by classical and emerging diffusion measures. These measures were combined into two informative indices, the first representing microstructural complexity, the second representing axonal density. We deployed pattern-learning algorithms to jointly decompose these connectivity features and 19 symptom measures.

Results

Early multi-tract multi-symptom pairs explained the most covariance and represented broad symptom categories, such as a general problems pair, or a pair representing all cognitive symptoms, and implicated more distributed networks of white matter tracts. Further pairs represented more specific symptom combinations, such as a pair representing attention problems exclusively, and were associated with more localized white matter abnormalities. Symptom representation was not systematically related to tract representation across pairs. Sleep problems were implicated across most pairs, but were related to different connections across these pairs. Expression of multi-tract features was not driven by sociodemographic and injury-related variables, as well as by clinical subgroups defined by the presence of ADHD. Analyses performed on a replication dataset showed consistent results.

Conclusions

Using a double-multivariate approach, we identified clinically-informative, cross-demographic multi-tract multi-symptom relationships. These results suggest that rather than clear one-to-one symptom-connectivity disturbances, concussions may be characterized by subtypes of symptom/connectivity relationships. The symptom/connectivity relationships identified in multi-tract multi-symptom pairs were not apparent in single-tract/single-symptom analyses. Future studies aiming to better understand connectivity/symptom relationships should take into account multi-tract multi-symptom heterogeneity.

Funding

Financial support for this work came from a Vanier Canada Graduate Scholarship from the Canadian Institutes of Health Research (G.I.G.), an Ontario Graduate Scholarship (S.S.), a Restracomp Research Fellowship provided by the Hospital for Sick Children (S.S.), an Institutional Research Chair in Neuroinformatics (M.D.), as well as a Natural Sciences and Engineering Research Council CREATE grant (M.D.).

Sex differences in autonomic recovery following repeated sinusoidal resistance exercise

A simple bodyweight squat is sufficient to cause substantial stress on the autonomic nervous system (ANS) via ~30-50 mmHg blood pressure (BP) oscillations. However, it is unknown to the extent of the ANS is impacted during and immediately following bodyweight and resistance squat-stand maneuvers (SSM) while considering chromosomal sex. Thirteen females and twelve males performed four, 5-minute bouts of squat-stand maneuvers (SSM); two at 0.05 Hz (10-second squat/10-second stand) and two at 0.10 Hz (5-s squat/5-s stand). The SSM were performed using bodyweight resistance and additional external resistance (~20% of bodyweight). Five-minutes of quiet-sitting and quiet-standing were completed immediately following both bodyweight and resistance squats. Heart rate variability (HRV) and baroreceptor sensitivity metrics were extracted from beat-to-beat electrocardiography and systemic BP recordings. Repeated measure Analysis of Variance with generalized eta-squared effect sizes assessed differences between SSM task type and chromosomal sex on ANS metrics. Despite added resistance eliciting greater elevations in blood pressure, no differences in ANS function were noted during competition and recovery between SSM tasks (all p > 0.050; negligible/small effect sizes). During recovery, females had an elevated heart rate (p = 0.017; small effect size), greater time-domain HRV measures (p < 0.047; small effect size), greater high-frequency domain HRV measures (p = 0.002; moderate effect size), and reduced low-frequency domain HRV measures (p = 0.002; moderate effect size). A healthy ANS can modulate repetitive cardiovascular stressors via squat-stand maneuvers in a harmonious manner irrespective of added low-level resistance. Females were more parasympathetically driven following low-level resistance exercise/stress, which may be a cardioprotective trait.

How exposure to chronic stress contributes to the development of type 2 diabetes: A complexity science approach

Chronic stress contributes to the onset of type 2 diabetes (T2D), yet the underlying etiological mechanisms are not fully understood. Responses to stress are influenced by earlier experiences, sex, emotions and cognition, and involve a complex network of neurotransmitters and hormones, that affect multiple biological systems. In addition, the systems activated by stress can be altered by behavioral, metabolic and environmental factors. The impact of stress on metabolic health can thus be considered an emergent process, involving different types of interactions between multiple variables, that are driven by non-linear dynamics at different spatiotemporal scales. To obtain a more comprehensive picture of the links between chronic stress and T2D, we followed a complexity science approach to build a causal loop diagram (CLD) connecting the various mediators and processes involved in stress responses relevant for T2D pathogenesis. This CLD could help develop novel computational models and formulate new hypotheses regarding disease etiology.

Examining the trajectory and predictors of post-concussion sleep quality in children and adolescents

OBJECTIVES

This study aimed to 1) determine if post-concussion sleep quality of children and adolescents differed from healthy sleep estimates; 2) describe the trajectory of parameters of sleep quality; 3) determine factors that predict sleep quality outcomes; and 4) compare sleep parameter outcomes between asymptomatic and symptomatic participants at 4 weeks post-concussion.

METHODS

Nightly actigraphy estimates of sleep in 79 children and adolescents were measured throughout 4 weeks post-concussion. Total sleep time (TST), sleep efficiency (SE), wake after sleep onset (WASO), number of arousals (NOA), and average arousal length (AAL) were measured.

RESULTS

Child and adolescent participants experienced significantly poorer SE and longer WASO duration throughout 4 weeks of recovery and adolescents experienced significantly longer TST. SE significantly improved with time post-injury (p = .047). Older age was associated with longer TST (p = .003) and female sex was associated with longer WASO (p = .025) and AAL duration (p = .044). Week 4 sleep parameter outcomes were not significantly different between asymptomatic and symptomatic participants.

CONCLUSIONS

The sleep quality of youth is adversely affected by concussion, particularly in females. Sleep quality appears to improve with time but may require more than 4 weeks to return to normal.

Personalized Connectome-Based Modeling in Patients with Semi-Acute Phase TBI: Relationship to Acute Neuroimaging and 6 Month Follow-Up

Following traumatic brain injury (TBI), cognitive impairments manifest through interactions between microscopic and macroscopic changes. On the microscale, a neurometabolic cascade alters neurotransmission, while on the macroscale diffuse axonal injury impacts the integrity of long-range connections. Large-scale brain network modeling allows us to make predictions across these spatial scales by integrating neuroimaging data with biophysically based models to investigate how microscale changes invisible to conventional neuroimaging influence large-scale brain dynamics. To this end, we analyzed structural and functional neuroimaging data from a well characterized sample of 44 adult TBI patients recruited from a regional trauma center, scanned at 1–2 weeks postinjury, and with follow-up behavioral outcome assessed 6 months later. Thirty-six age-matched healthy adults served as comparison participants. Using The Virtual Brain, we fit simulations of whole-brain resting-state functional MRI to the empirical static and dynamic functional connectivity of each participant. Multivariate partial least squares (PLS) analysis showed that patients with acute traumatic intracranial lesions had lower cortical regional inhibitory connection strengths than comparison participants, while patients without acute lesions did not differ from the comparison group. Further multivariate PLS analyses found correlations between lower semiacute regional inhibitory connection strengths and more symptoms and lower cognitive performance at a 6 month follow-up. Critically, patients without acute lesions drove this relationship, suggesting clinical relevance of regional inhibitory connection strengths even when traumatic intracranial lesions were not present. Our results suggest that large-scale connectome-based models may be sensitive to pathophysiological changes in semi-acute phase TBI patients and predictive of their chronic outcomes.

Psychological and Social Needs: Athletes’ and Mental Performance Consultants’ Perspectives on a Gap in Concussion Protocols

While research advancements have substantially improved concussion management efforts, consideration for the psychological and social aspects of concussive injuries have remained largely absent from concussion protocols. The present study was undertaken to identify elite athletes’ psychological and social needs during the recovery process. Elite athletes with a history of concussion and mental performance consultants who work with concussed elite athletes participated in focus group interviews to shed light on these needs. A thematic analysis of these focus groups revealed six psychological and social needs: acceptance, normality, confidence, self-efficacy, trust in relationships, and social support. These themes are framed within concussion literature to help initiate a conversation on how psychological and social needs should be addressed as part of multifaceted efforts to improve concussion recovery.

Mild Traumatic Brain Injury/Concussion Initiates an Atypical Astrocyte Response Caused by Blood-Brain Barrier Dysfunction

Mild traumatic brain injury/concussion (mTBI) accounts for 70-90% of all reported TBI cases and causes long-lasting neurological consequences in 10-40% of patients. Recent clinical studies revealed increased blood-brain barrier (BBB) permeability in mTBI patients, which correlated with secondary damage after mTBI. However, the cascade of cellular events initiated by exposure to blood-borne factors resulting in sustained damage is not fully understood. We previously reported that astrocytes respond atypically to mTBI, rapidly losing many proteins essential to their homeostatic function, while classic scar formation does not occur. Here, we tested the hypothesis that mTBI-induced BBB damage causes atypical astrocytes through exposure to blood-borne factors. Using an mTBI mouse model, two-photon imaging, an endothelial cell-specific genetic ablation approach, and serum-free primary astrocyte cultures, we demonstrated that areas with atypical astrocytes coincide with BBB damage and that exposure of astrocytes to plasma proteins is sufficient to initiate loss of astrocyte homeostatic proteins. Although mTBI resulted in frequent impairment of both physical and metabolic BBB properties and leakage of small-sized blood-borne factors, deposition of the coagulation factor fibrinogen or vessel rupture were rare. Surprisingly, even months after mTBI, BBB repair did not occur in areas with atypical astrocytes. Together, these findings implicate that even relatively small BBB disturbances are sustained long term, and render nearby astrocytes dysfunctional, likely at the cost of neuronal health and function.

Sports related concussion: an emerging era in digital sports technology

Sports-related concussion (SRC) is defined as a mild traumatic brain injury (mTBI) leading to complex impairment(s) in neurological function with many seemingly hidden or difficult to measure impairments that can deteriorate rapidly without any prior indication. Growing numbers of SRCs in professional and amateur contact sports have prompted closer dialog regarding player safety and welfare. Greater emphasis on awareness and education has improved SRC management, but also highlighted the difficulties of diagnosing SRC in a timely manner, particularly during matches or immediately after competition. Therefore, challenges exist in off-field assessment and return to play (RTP) protocols, with current traditional (subjective) approaches largely based on infrequent snapshot assessments. Low-cost digital technologies may provide more objective, integrated and personalized SRC assessment to better inform RTP protocols whilst also enhancing the efficiency and precision of healthcare assessment. To fully realize the potential of digital technologies in the diagnosis and management of SRC will require a significant paradigm shift in clinical practice and mindset. Here, we provide insights into SRC clinical assessment methods and the translational utility of digital approaches, with a focus on off-field digital techniques to detect key SRC metrics/biomarkers. We also provide insights and recommendations to the common benefits and challenges facing digital approaches as they aim to transition from novel technologies to an efficient, valid, reliable, and integrated clinical assessment tool for SRC. Finally, we highlight future opportunities that digital approaches have in SRC assessment and management including digital twinning and the "digital athlete".

Machine Learning for Subtyping Concussion Using a Clustering Approach

Background: Concussion subtypes are typically organized into commonly affected symptom areas or a combination of affected systems, an approach that may be flawed by bias in conceptualization or the inherent limitations of interdisciplinary expertise.

Objective: The purpose of this study was to determine whether a bottom-up, unsupervised, machine learning approach, could more accurately support concussion subtyping.

Methods: Initial patient intake data as well as objective outcome measures including, the Patient-Reported Outcomes Measurement Information System (PROMIS), Dizziness Handicap Inventory (DHI), Pain Catastrophizing Scale (PCS), and Immediate Post-Concussion Assessment and Cognitive Testing Tool (ImPACT) were retrospectively extracted from the Advance Concussion Clinic's database. A correlation matrix and principal component analysis (PCA) were used to reduce the dimensionality of the dataset. Sklearn's agglomerative clustering algorithm was then applied, and the optimal number of clusters within the patient database were generated. Between-group comparisons among the formed clusters were performed using a Mann-Whitney U test.

Results: Two hundred seventy-five patients within the clinics database were analyzed. Five distinct clusters emerged from the data when maximizing the Silhouette score (0.36) and minimizing the Davies-Bouldin score (0.83). Concussion subtypes derived demonstrated clinically distinct profiles, with statistically significant differences (p < 0.05) between all five clusters.

Conclusion: This machine learning approach enabled the identification and characterization of five distinct concussion subtypes, which were best understood according to levels of complexity, ranging from Extremely Complex to Minimally Complex. Understanding concussion in terms of Complexity with the utilization of artificial intelligence, could provide a more accurate concussion classification or subtype approach; one that better reflects the true heterogeneity and complex system disruptions associated with mild traumatic brain injury.

Preliminary Evidence for the Clinical Utility of Tactile Somatosensory Assessments of Sport-Related mTBI

OBJECTIVES

To evaluate the clinical utility of tactile somatosensory assessments to assist clinicians in diagnosing sport-related mild traumatic brain injury (SR-mTBI), classifying recovery trajectory based on performance at initial clinical assessment, and determining if neurophysiological recovery coincided with clinical recovery.

RESEARCH DESIGN

Prospective cohort study with normative controls.

METHODS

At admission (n = 79) and discharge (n = 45/79), SR-mTBI patients completed the SCAT-5 symptom scale, along with the following three components from the Cortical Metrics Brain Gauge somatosensory assessment (BG-SA): temporal order judgement (TOJ), TOJ with confounding condition (TOJc), and duration discrimination (DUR). To assist SR-mTBI diagnosis on admission, BG-SA performance was used in logistic regression to discriminate cases belonging to the SR-mTBI sample or a healthy reference sample (pooled BG-SA data for healthy participants in previous studies). Decision trees evaluated how accurately BG-SA performance classified SR-mTBI recovery trajectories.

RESULTS

BG-SA TOJ, TOJc, and DUR poorly discriminated between cases belonging to the SR-mTBI sample or a healthy reference sample (0.54-0.70 AUC, 47.46-64.71 PPV, 48.48-61.11 NPV). The BG-SA evaluated did not accurately classify SR-mTBI recovery trajectories (> 14-day resolution 48%, ≤14-day resolution 54%, lost to referral/follow-up 45%). Mann-Whitney U tests revealed differences in BG-SA TOJc performance between SR-mTBI participants and the healthy reference sample at initial clinical assessment and at clinical recovery (p < 0.05).

CONCLUSIONS

BG-SA TOJ, TOJc, and DUR appear to have limited clinical utility to assist clinicians with diagnosing SR-mTBI or predicting recovery trajectories under ecologically valid conditions. Neurophysiological abnormalities persisted beyond clinical recovery given abnormal BG-SA TOJc performance observed when SR-mTBI patients achieved clinical recovery.

Oculomotor Deficits and Symptom Severity Are Associated With Poorer Dynamic Mobility in Chronic Mild Traumatic Brain Injury

Oculomotor deficits, vestibular impairments, and persistent symptoms are common after a mild traumatic brain injury (mTBI); however, the relationship between visual-vestibular deficits, symptom severity, and dynamic mobility tasks is unclear. Twenty-three individuals (mean age 55.7 ± 9.3 years) with persistent symptoms after mTBI, who were between 3 months to 2 years post-injury were compared with 23 age and sex-matched controls. Oculomotor deficits [depth perception, near-point convergence, baseline visual acuity (BLVA), perception time], vestibular deficits (dynamic visual acuity in the pitch and yaw planes), dynamic mobility measured by the Functional Gait Assessment (FGA), and symptoms measured by the Post-Concussion Symptom Scale (PCSS) and Dizziness Handicap Inventory (DHI) were compared between groups. Participants with mTBI had poorer performance on the FGA (p < 0.001), higher symptom severity on the PCSS (p < 0.001), and higher DHI scores (p < 0.001) compared to controls. Significant differences were seen on specific items of the FGA between individuals with mTBI and controls during walking with horizontal head turns (p = 0.002), walking with vertical head tilts (p < 0.001), walking with eyes closed (p = 0.003), and stair climbing (p = 0.001). FGA performance was correlated with weeks since concussion (r = −0.67, p < 0.001), depth perception (r = −0.5348, p < 0.001), near point convergence (r = −0.4717, p = 0.001), baseline visual acuity (r = −0.4435, p = 0.002); as well as with symptoms on the PCSS (r = −0.668, p < 0.001), and DHI (r = −0.811, p < 0.001). Dynamic balance deficits persist in chronic mTBI and may be addressed using multifaceted rehabilitation strategies to address oculomotor dysfunction, post-concussion symptoms, and perception of handicap due to dizziness.

Editors' Foreword: Knowledge and Skill Competencies for Speech-Language Pathology Management of Concussion

[Figure: see text].

Evolving Science to Inform Emerging Concussion Practices

Purpose This article describes two concussion models built on the current state of science that help illustrate the complicated interactions among the multiple factors that drive concussion symptoms. Consideration of these models remind practitioners, including speech-language pathologists, to attend to factors that increase the risk of patients developing prolonged symptoms, as well as attend to symptoms that result from various interactions and may differentially respond to specific treatments. In particular, the models encourage personalized or precision medicine and the implementation of targeted, coordinated therapies.

Evidence to Support the Use of S-Adenosylmethionine for Treatment of Post-Concussive Sequelae in the Military

INTRODUCTION

Since the year 2000, over 413,000 service members have sustained traumatic brain injury (TBI) and may present with post-concussive sequelae including headaches, fatigue, irritability, cognitive problems, depression, insomnia, and chronic pain. Although the focus of the article is on military TBI, the usefulness of S-adenosylmethionine (SAMe) would extend to both civilian and military populations. This narrative review examines the preclinical and clinical literature of SAMe's metabolism and alterations seen in disease states such as depressive disorders, pain disorders, fatigue, cognition, dementia, use in pregnancy and peripartum, children, adolescents, and adults, to the elderly with and without dementia, stroke, and neurodegeneration, in order to highlight its potential benefit in post-concussive sequelae after TBI.

MATERIALS AND METHODS

A MEDLINE/PubMed and Cochrane Database search was conducted between May 3, 2018 and July 30, 2019 by combining search terms for SAMe with terms for relevant disease states including depression, brain injury, dementia, Alzheimer's disease, Parkinson's disease, cognition, fatigue, and pain. This search retrieved a total of 676 references. 439 were excluded for being over a 10-year publication date, except where clinically relevant. After additional removal of repeated articles, the number of articles were totaled 197. An additional 59 articles were excluded: 10 not in English, 4 duplicates, 4 not original investigations, and 41 outside the scope of this article. The remaining 138 articles were used in this review and included 25 clinical studies, 46 preclinical studies, 63 reviews, and 4 case reports.

RESULTS

This narrative review examined the preclinical and clinical literature of SAMe's metabolism and alterations seen in MDD, pain disorders, fatigue, cognition and memory, dementia, and other disorders to highlight the potential benefit of SAMe in post-concussive sequelae in mTBI. The literature showed potential for improvement, safety, and tolerability in these symptom clusters commonly seen in military mild TBI (mTBI).

CONCLUSION

There is evidence of a potential benefit of SAMe as an intervention to help with symptoms across the range of post-concussive sequelae and syndromes commonly seen in military mTBI. Since the discovery of SAMe in 1952, this pleiotropic molecule has shown the significance of its involvement in several metabolic cascades in such disparate systems as epigenetics, bioenergetics, DNA methylation, neurotransmitter systems, and potential usefulness in military TBI. Significant limitations include disparate presentations seen in patients with mild TBI, those with post-concussive syndrome, as well as those with comorbid depression and posttraumatic stress disorder. Also, over-the-counter medications are not regulated and SAMe products may vary widely in price and quality. Given the potential for mania in patients with bipolar disorder, evaluation and recommendations should be made by a physician able to evaluate the underlying bipolar diathesis. Furthermore, this narrative review serves as the rationale for future open-label and double-blind placebo-controlled trials in military mTBI and SAMe.

Nutritional interventions to improve neurophysiological impairments following traumatic brain injury: A systematic review

Traumatic brain injury (TBI) accounts for significant global health burden. Effects of TBI can become chronic even following mild injury. There is a need to develop effective therapies to attenuate the damaging effects of TBI and improve recovery outcomes. This literature review using a priori criteria (PROSPERO; CRD42018100623) summarized 43 studies between January 1998 and July 2019 that investigated nutritional interventions (NUT) delivered with the objective of altering neurophysiological (NP) outcomes following TBI. Risk of bias was assessed for included studies, and NP outcomes recorded. The systematic search resulted in 43 of 3,748 identified studies met inclusion criteria. No studies evaluated the effect of a NUT on NP outcomes of TBI in humans. Biomarkers of morphological changes and apoptosis, oxidative stress, and plasticity, neurogenesis, and neurotransmission were the most evaluated NP outcomes across the 43 studies that used 2,897 animals. The risk of bias was unclear in all reviewed studies due to poorly detailed methodology sections. Taking these limitations into account, anti-oxidants, branched chain amino acids, and ω-3 polyunsaturated fatty acids have shown the most promising pre-clinical results for altering NP outcomes following TBI. Refinement of pre-clinical methodologies used to evaluate effects of interventions on secondary damage of TBI would improve the likelihood of translation to clinical populations.

Classification of Electroencephalogram in a Mouse Model of Traumatic Brain Injury Using Machine Learning Approaches

Traumatic Brain Injury (TBI) is highly prevalent, affecting ~1% of the U.S. population, with lifetime economic costs estimated to be over $75 billion. In the U.S., there are about 50,000 deaths annually related to TBI, and many others are permanently disabled. However, it is currently unknown which individuals will develop persistent disability following TBI and what brain mechanisms underlie these distinct populations. The pathophysiologic causes for those are most likely multifactorial. Electroencephalogram (EEG) has been used as a promising quantitative measure for TBI diagnosis and prognosis. The recent rise of advanced data science approaches such as machine learning and deep learning holds promise to further analyze EEG data, looking for EEG biomarkers of neurological disease, including TBI. In this work, we investigated various machine learning approaches on our unique 24-hour recording dataset of a mouse TBI model, in order to look for an optimal scheme in classification of TBI and control subjects. The epoch lengths were 1 and 2 minutes. The results were promising with accuracy of ~80-90% when appropriate features and parameters were used using a small number of subjects (5 shams and 4 TBIs). We are thus confident that, with more data and studies, we would be able to detect TBI accurately, not only via long-term recordings but also in practical scenarios, with EEG data obtained from simple wearables in the daily life.

Mapping the multicausality of Alzheimer's disease through group model building

Alzheimer’s disease (AD) is a complex, multicausal disorder involving several spatiotemporal scales and scientific domains. While many studies focus on specific parts of this system, the complexity of AD is rarely studied as a whole. In this work, we apply systems thinking to map out known causal mechanisms and risk factors ranging from intracellular to psychosocial scales in sporadic AD. We report on the first systemic causal loop diagram (CLD) for AD, which is the result of an interdisciplinary group model building (GMB) process. The GMB was based on the input of experts from multiple domains and all proposed mechanisms were supported by scientific literature. The CLD elucidates interaction and feedback mechanisms that contribute to cognitive decline from midlife onward as described by the experts. As an immediate outcome, we observed several non-trivial reinforcing feedback loops involving factors at multiple spatial scales, which are rarely considered within the same theoretical framework. We also observed high centrality for modifiable risk factors such as social relationships and physical activity, which suggests they may be promising leverage points for interventions. This illustrates how a CLD from an interdisciplinary GMB process may lead to novel insights into complex disorders. Furthermore, the CLD is the first step in the development of a computational model for simulating the effects of risk factors on AD.

Physical Therapy Evaluation and Treatment After Concussion/Mild Traumatic Brain Injury

Over the last decade, numerous concussion evidence-based clinical practice guidelines (CPGs), consensus statements, and clinical guidance documents have been published. These documents have typically focused on the diagnosis of concussion and medical management of individuals post concussion, but provide little specific guidance for physical therapy management of concussion and its associated impairments. Further, many of these guidance documents have targeted specific populations in specific care contexts. The primary purpose of this CPG is to provide a set of evidence-based recommendations for physical therapist management of the wide spectrum of patients who have experienced a concussive event. J Orthop Sports Phys Ther 2020;50(4):CPG1-CPG73. doi:10.2519/jospt.2020.0301.