Neurofilaments in Sporadic and Familial Amyotrophic Lateral Sclerosis: A Systematic Review and Meta-Analysis.

BACKGROUND: Neurofilament proteins have been implicated to be altered in amyotrophic lateral sclerosis (ALS). The objectives of this study were to assess the diagnostic and prognostic utility of neurofilaments in ALS. METHODS: Studies were conducted in electronic databases (PubMed/MEDLINE, Embase, Web of Science, and Cochrane CENTRAL) from inception to 17 August 2023, and investigated neurofilament light (NfL) or phosphorylated neurofilament heavy chain (pNfH) in ALS. The study design, enrolment criteria, neurofilament concentrations, test accuracy, relationship between neurofilaments in cerebrospinal fluid (CSF) and blood, and clinical outcome were recorded. The protocol was registered with PROSPERO, CRD42022376939. RESULTS: Sixty studies with 8801 participants were included. Both NfL and pNfH measured in CSF showed high sensitivity and specificity in distinguishing ALS from disease mimics. Both NfL and pNfH measured in CSF correlated with their corresponding levels in blood (plasma or serum); however, there were stronger correlations between CSF NfL and blood NfL. NfL measured in blood exhibited high sensitivity and specificity in distinguishing ALS from controls. Both higher levels of NfL and pNfH either measured in blood or CSF were correlated with more severe symptoms as assessed by the ALS Functional Rating Scale Revised score and with a faster disease progression rate; however, only blood NfL levels were associated with shorter survival. DISCUSSION: Both NfL and pNfH measured in CSF or blood show high diagnostic utility and association with ALS functional scores and disease progression, while CSF NfL correlates strongly with blood (either plasma or serum) and is also associated with survival, supporting its use in clinical diagnostics and prognosis. Future work must be conducted in a prospective manner with standardized bio-specimen collection methods and analytical platforms, further improvement in immunoassays for quantification of pNfH in blood, and the identification of cut-offs across the ALS spectrum and controls.

Clinical, Biomarker, and Research Tests Among US Government Personnel and Their Family Members Involved in Anomalous Health Incidents.

Importance: Since 2015, US government and related personnel have reported dizziness, pain, visual problems, and cognitive dysfunction after experiencing intrusive sounds and head pressure. The US government has labeled these anomalous health incidents (AHIs). Objective: To assess whether participants with AHIs differ significantly from US government control participants with respect to clinical, research, and biomarker assessments. Design, Setting, and Participants: Exploratory study conducted between June 2018 and July 2022 at the National Institutes of Health Clinical Center, involving 86 US government staff and family members with AHIs from Cuba, Austria, China, and other locations as well as 30 US government control participants. Exposures: AHIs. Main Outcomes and Measures: Participants were assessed with extensive clinical, auditory, vestibular, balance, visual, neuropsychological, and blood biomarkers (glial fibrillary acidic protein and neurofilament light) testing. The patients were analyzed based on the risk characteristics of the AHI identifying concerning cases as well as geographic location. Results: Eighty-six participants with AHIs (42 women and 44 men; mean [SD] age, 42.1 [9.1] years) and 30 vocationally matched government control participants (11 women and 19 men; mean [SD] age, 43.8 [10.1] years) were included in the analyses. Participants with AHIs were evaluated a median of 76 days (IQR, 30-537) from the most recent incident. In general, there were no significant differences between participants with AHIs and control participants in most tests of auditory, vestibular, cognitive, or visual function as well as levels of the blood biomarkers. Participants with AHIs had significantly increased fatigue, depression, posttraumatic stress, imbalance, and neurobehavioral symptoms compared with the control participants. There were no differences in these findings based on the risk characteristics of the incident or geographic location of the AHIs. Twenty-four patients (28%) with AHI presented with functional neurological disorders. Conclusions and Relevance: In this exploratory study, there were no significant differences between individuals reporting AHIs and matched control participants with respect to most clinical, research, and biomarker measures, except for objective and self-reported measures of imbalance and symptoms of fatigue, posttraumatic stress, and depression. This study did not replicate the findings of previous studies, although differences in the populations included and the timing of assessments limit direct comparisons.

Neuroimaging Findings in US Government Personnel and Their Family Members Involved in Anomalous Health Incidents.

Importance: US government personnel stationed internationally have reported anomalous health incidents (AHIs), with some individuals experiencing persistent debilitating symptoms. Objective: To assess the potential presence of magnetic resonance imaging (MRI)-detectable brain lesions in participants with AHIs, with respect to a well-matched control group. Design, Setting, and Participants: This exploratory study was conducted at the National Institutes of Health (NIH) Clinical Center and the NIH MRI Research Facility between June 2018 and November 2022. Eighty-one participants with AHIs and 48 age- and sex-matched control participants, 29 of whom had similar employment as the AHI group, were assessed with clinical, volumetric, and functional MRI. A high-quality diffusion MRI scan and a second volumetric scan were also acquired during a different session. The structural MRI acquisition protocol was optimized to achieve high reproducibility. Forty-nine participants with AHIs had at least 1 additional imaging session approximately 6 to 12 months from the first visit. Exposure: AHIs. Main Outcomes and Measures: Group-level quantitative metrics obtained from multiple modalities: (1) volumetric measurement, voxel-wise and region of interest (ROI)-wise; (2) diffusion MRI-derived metrics, voxel-wise and ROI-wise; and (3) ROI-wise within-network resting-state functional connectivity using functional MRI. Exploratory data analyses used both standard, nonparametric tests and bayesian multilevel modeling. Results: Among the 81 participants with AHIs, the mean (SD) age was 42 (9) years and 49% were female; among the 48 control participants, the mean (SD) age was 43 (11) years and 42% were female. Imaging scans were performed as early as 14 days after experiencing AHIs with a median delay period of 80 (IQR, 36-544) days. After adjustment for multiple comparisons, no significant differences between participants with AHIs and control participants were found for any MRI modality. At an unadjusted threshold (P < .05), compared with control participants, participants with AHIs had lower intranetwork connectivity in the salience networks, a larger corpus callosum, and diffusion MRI differences in the corpus callosum, superior longitudinal fasciculus, cingulum, inferior cerebellar peduncle, and amygdala. The structural MRI measurements were highly reproducible (median coefficient of variation <1% across all global volumetric ROIs and <1.5% for all white matter ROIs for diffusion metrics). Even individuals with large differences from control participants exhibited stable longitudinal results (typically, <±1% across visits), suggesting the absence of evolving lesions. The relationships between the imaging and clinical variables were weak (median Spearman ρ = 0.10). The study did not replicate the results of a previously published investigation of AHIs. Conclusions and Relevance: In this exploratory neuroimaging study, there were no significant differences in imaging measures of brain structure or function between individuals reporting AHIs and matched control participants after adjustment for multiple comparisons.

Associations between white matter integrity and postural control in adults with traumatic brain injury.

Abnormalities of postural sway have been extensively reported in traumatic brain injury (TBI). However, the underlying neural correlates of balance disturbances in TBI remain to be elucidated. Studies in children with TBI have reported associations between the Sensory Organization Test (SOT) and measures of white matter (WM) integrity with diffusion tensor imaging (DTI) in brain areas responsible for multisensory integration. This study seeks to replicate those associations in adults as well as explore relationships between DTI and the Limits of Stability (LOS) Test. Fifty-six participants (43±17 years old) with a history of TBI were tested 30 days to 5 years post-TBI. This study confirmed results in children for associations between the SOT and the medial lemniscus as well as middle cerebellar peduncle, and revealed additional associations with the posterior thalamic radiation. Additionally, this study found significant correlations between abnormal LOS scores and impaired WM integrity in the cingulum, corpus callosum, corticopontine and corticospinal tracts, fronto-occipital fasciculi, longitudinal fasciculi, medial lemniscus, optic tracts and thalamic radiations. Our findings indicate the involvement of a broad range of WM tracts in the control of posture, and demonstrate the impact of TBI on balance via disruptions to WM integrity.

Headaches in Traumatic Brain Injury: Improvement Over Time, Associations With Quality of Life, and Impact of Migraine-Type Headaches.

OBJECTIVE: To describe headache characteristics over time in patients with traumatic brain injury (TBI). SETTING: Patients enrolled and followed at the National Institutes of Health Clinical Center between 2011 and 2020. PARTICIPANTS: There were 147 patients with TBI, with 74 mild TBI (mTBI), 49 moderate (modTBI), 24 severe (sTBI), and 20 individuals without brain injury (IWBIs). DESIGN: Regular surveys of headache characteristics in patients with TBI were conducted. Patients were enrolled as early as 30 days post-injury and followed up to 5 years, for 419 total visits and 80 patients with multiple return visits. MAIN MEASURES: Surveys of headache characteristics, including headache severity, were measured on a 0- to 10-point Likert scale and headache frequency quantified as headaches per month. Patients with migraine-type headaches ( n = 39) were identified by a clinician-administered tool. Functional outcomes were measured using the Glasgow Outcome Scale-Extended (GOS-E) and quality of life by the Satisfaction with Life Scale (SWLS) and the 36-item Short Form Survey (SF-36). RESULTS: At their initial visit, patients with TBI had more severe and frequent headaches than IWBIs (median 5 vs 2.5, P < .001; median 2 vs 0.2, P < .001), as did patients with mTBI compared with modTBI/sTBI (all P ≤ .01). Migraines were associated with lower SWLS and SF-36 scores. Migraines and young age were associated with higher headache severity and frequency across time points. Longitudinally, time post-injury correlated with improvement in headache severity and frequency without differences by injury severity. However, time post-injury did not correlate with improvement in headache characteristics in a patient subgroup with moderate/severe headaches. CONCLUSION: Our findings suggest that patients with mild, moderate, or severe TBI see improvement in headaches over time. However, patients should be counseled that improvement is modest and seen more in patients with milder headache symptoms. Patients with migraine headaches in particular are at risk for worse headache characteristics with greater impact on quality of life.

Informatics Research on Mental Health Functioning: Decision Support for the Social Security Administration Disability Program.

The disability determination process of the Social Security Administration's (SSA's) disability program requires assessing work-related functioning for individual claimants alleging disability due to mental impairment. This task is particularly challenging because the determination process involves the review of a large file of information, including objective medical evidence and self-reports from claimants, families, and former employers. To improve this decision-making process, SSA entered an interagency agreement with the Rehabilitation Medicine Department, Epidemiology and Biostatistics Section, in the Clinical Center of the National Institutes of Health, intending to use data science and informatics to develop decision support tools. This collaborative effort over the past decade has led to the development of the Work Disability-Functional Assessment Battery and has initiated an approach to applying natural language processing to the review of claimants' files for information on mental health functioning. This informatics research collaboration holds promise for improving the process of disability determination for individuals with mental impairments who make claims at the SSA.

Changes in cardiorespiratory function and fatigue following 12 weeks of exercise training in women with systemic lupus erythematosus: a pilot study.

OBJECTIVE: In patients with systemic lupus erythematosus (SLE), fatigue is a debilitating symptom with poorly understood pathophysiology. Cardiorespiratory dysfunction has been hypothesised as a contributor to SLE-fatigue. The purpose of this exploratory study was to examine changes in cardiorespiratory function, following an exercise training programme in women with SLE, together with patient reported outcomes and other pathophysiological measures that may underlie SLE-fatigue. METHODS: Sixteen women with SLE and fatigue (Fatigue Severity Scale (FSS) ≥3) were enrolled in a supervised aerobic exercise training programme of vigorous intensity. The primary outcome was time to reach anaerobic threshold (AT-Time) during a cardiopulmonary exercise test (CPET). Secondary outcomes included changes in the 10-minute walk test (10MWT), FSS scores and the Patient Reported Outcomes Measurement Information System (PROMIS-57) survey. Mitochondrial function was assessed by the oxygen consumption rate (OCR)/extracellular acidification rate (ECAR) metabolic potential ratio. RESULTS: Following 12 weeks of exercise training, AT-Time increased by 93±82 (mean±SD) s (p<0.001), 10MWT increased by 84±66 m (p<0.001) and peak oxygen uptake (VO2) increased by 1.4±2.0 mL/kg/min (p=0.013). There were improvements in FSS score (-1.4±1.0, p<0.0001) and in most of the PROMIS-57 domains. The decrease in FSS scores correlated with an increase in the OCR/ECAR ratio (Pearson's correlation r=-0.59, p=0.03). A subset of subjects (9/15) had significant reduction in their Interferon Stimulated Genes (ISG) (p=0.007) accompanied by a significant increase in the OCR/ECAR ratio (p=0.013). CONCLUSIONS: Cardiorespiratory function was improved in concomitance with reductions in fatigue following a 12-week aerobic exercise programme. The reduction in fatigue scores correlated with improvements in mitochondrial function.

Segmented 3D Echo Planar Acquisition for Rapid Susceptibility-Weighted Imaging: Application to Microhemorrhage Detection in Traumatic Brain Injury.

BACKGROUND: Susceptibility-weighted imaging (SWI) provides superior image contrast of cerebral microhemorrhages (CMBs). It is based on a three-dimensional (3D) gradient echo (GRE) sequence with a relatively long imaging time. PURPOSE: To evaluate whether an accelerated 3D segmented echo planar imaging SWI is comparable to GRE SWI in detecting CMBs in traumatic brain injury (TBI). STUDY TYPE: Prospective. SUBJECTS: Four healthy volunteers and 46 consecutive subjects (38.0 ± 14.4 years, 16 females; 12 mild, 13 moderate, and 7 severe TBI). FIELD STRENGTH/SEQUENCE: A 3 T scanner/3D gradient echo and 3D segmented echo planar imaging (segEPI). ASSESSMENT: Brain images were acquired using GRE and segEPI in a single session (imaging time = 9 minutes 47 seconds and 1 minute 30 seconds, respectively). The signal-to-noise ratio (SNR) calculated from healthy volunteer thalamus and centrum semiovale were compared. CMBs were counted by three raters blinded to diagnostic information. STATISTICAL TESTS: A t-test was used to assess SNR difference. Pearson correlation and Wilcoxon signed-rank test were performed using CMB counts. The intermethod agreement was evaluated using Bland-Altman method. Intermethod and interrater reliabilities of image-based diffuse axonal injury (DAI) diagnoses were evaluated using Cohen's kappa and percent agreement. P ≤ 0.05 was considered statistically significant. RESULTS: Thalamus SNRs were 16.9 ± 2.2 and 16.5 ± 3 for GRE and segEPI (P = 0.84), respectively. Centrum semiovale SNRs were 25.8 ± 4.6 and 21.1 ± 2.7 (P = 0.13). The correlation coefficient of CMBs was 0.93, and differences were not significant (P = 0.56-0.85). For DAI diagnoses, Cohen's kappa was 0.62-0.84 and percent agreement was 85%-94%. DATA CONCLUSION: CMB counts on segEPI and GRE were highly correlated, and DAI diagnosis was made equally effectively. segEPI SWI can potentially replace GRE SWI in detecting TBI CMBs, especially when time constraints are critical. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Automated Classification of Resting-State fMRI ICA Components Using a Deep Siamese Network.

Manual classification of functional resting state networks (RSNs) derived from Independent Component Analysis (ICA) decomposition can be labor intensive and requires expertise, particularly in large multi-subject analyses. Hence, a fully automatic algorithm that can reliably classify these RSNs is desirable. In this paper, we present a deep learning approach based on a Siamese Network to learn a discriminative feature representation for single-subject ICA component classification. Advantages of this supervised framework are that it requires relatively few training data examples and it does not require the number of ICA components to be specified. In addition, our approach permits one-shot learning, which allows generalization to new classes not seen in the training set with only one example of each new class. The proposed method is shown to out-perform traditional convolutional neural network (CNN) and template matching methods in identifying eleven subject-specific RSNs, achieving 100% accuracy on a holdout data set and over 99% accuracy on an outside data set. We also demonstrate that the method is robust to scan-rescan variation. Finally, we show that the functional connectivity of default mode and salience networks identified by the proposed technique is altered in a group analysis of mild traumatic brain injury (TBI), severe TBI, and healthy subjects.

Information Extraction Framework for Disability Determination Using a Mental Functioning Use-Case.

Natural language processing (NLP) in health care enables transformation of complex narrative information into high value products such as clinical decision support and adverse event monitoring in real time via the electronic health record (EHR). However, information technologies for mental health have consistently lagged because of the complexity of measuring and modeling mental health and illness. The use of NLP to support management of mental health conditions is a viable topic that has not been explored in depth. This paper provides a framework for the advanced application of NLP methods to identify, extract, and organize information on mental health and functioning to inform the decision-making process applied to assessing mental health. We present a use-case related to work disability, guided by the disability determination process of the US Social Security Administration (SSA). From this perspective, the following questions must be addressed about each problem that leads to a disability benefits claim: When did the problem occur and how long has it existed? How severe is it? Does it affect the person's ability to work? and What is the source of the evidence about the problem? Our framework includes 4 dimensions of medical information that are central to assessing disability-temporal sequence and duration, severity, context, and information source. We describe key aspects of each dimension and promising approaches for application in mental functioning. For example, to address temporality, a complete functional timeline must be created with all relevant aspects of functioning such as intermittence, persistence, and recurrence. Severity of mental health symptoms can be successfully identified and extracted on a 4-level ordinal scale from absent to severe. Some NLP work has been reported on the extraction of context for specific cases of wheelchair use in clinical settings. We discuss the links between the task of information source assessment and work on source attribution, coreference resolution, event extraction, and rule-based methods. Gaps were identified in NLP applications that directly applied to the framework and in existing relevant annotated data sets. We highlighted NLP methods with the potential for advanced application in the field of mental functioning. Findings of this work will inform the development of instruments for supporting SSA adjudicators in their disability determination process. The 4 dimensions of medical information may have relevance for a broad array of individuals and organizations responsible for assessing mental health function and ability. Further, our framework with 4 specific dimensions presents significant opportunity for the application of NLP in the realm of mental health and functioning beyond the SSA setting, and it may support the development of robust tools and methods for decision-making related to clinical care, program implementation, and other outcomes.

Extracellular vesicle concentrations of glial fibrillary acidic protein and neurofilament light measured 1 year after traumatic brain injury.

Traumatic brain injury (TBI) is linked to long-term symptoms in a sub-set of patients who sustain an injury, but this risk is not universal, leading us and others to question the nature of individual variability in recovery trajectories. Extracellular vesicles (EVs) are a promising, novel avenue to identify blood-based biomarkers for TBI. Here, our aim was to determine if glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) measured 1-year postinjury in EVs could distinguish patients from controls, and whether these biomarkers relate to TBI severity or recovery outcomes. EV GFAP and EV NfL were measured using an ultrasensitive assay in 72 TBI patients and 20 controls. EV GFAP concentrations were elevated in moderate and severe TBI compared to controls (p's < 0.001) and could distinguish controls from moderate (AUC = 0.86) or severe TBI (AUC = 0.88). Increased EV GFAP and EV NfL levels were associated with lower 1-year Glasgow Outcome Scale-Extended (GOS-E) score (p's < 0.05). These findings suggest that blood-derived EV concentrations of GFAP and NfL drawn even 1 year after injury are higher in TBI patients compared to controls, and are related to injury severity and poor recovery outcomes, suggesting that TBIs alter the activity of these biomarkers, likely contributing to individual variability in recovery.

A comprehensive study of mobility functioning information in clinical notes: Entity hierarchy, corpus annotation, and sequence labeling.

BACKGROUND: Secondary use of Electronic Health Records (EHRs) has mostly focused on health conditions (diseases and drugs). Function is an important health indicator in addition to morbidity and mortality. Nevertheless, function has been overlooked in accessing patients' health status. The World Health Organization (WHO)'s International Classification of Functioning, Disability and Health (ICF) is considered the international standard for describing and coding function and health states. We pioneer the first comprehensive analysis and identification of functioning concepts in the Mobility domain of the ICF. RESULTS: Using physical therapy notes at the National Institutes of Health's Clinical Center, we induced a hierarchical order of mobility-related entities including 5 entities types, 3 relations, 8 attributes, and 33 attribute values. Two domain experts manually curated a gold standard corpus of 14,281 nested entity mentions from 400 clinical notes. Inter-annotator agreement (IAA) of exact matching averaged 92.3 % F1-score on mention text spans, and 96.6 % Cohen's kappa on attributes assignments. A high-performance Ensemble machine learning model for named entity recognition (NER) was trained and evaluated using the gold standard corpus. Average F1-score on exact entity matching of our Ensemble method (84.90 %) outperformed popular NER methods: Conditional Random Field (80.4 %), Recurrent Neural Network (81.82 %), and Bidirectional Encoder Representations from Transformers (82.33 %). CONCLUSIONS: The results of this study show that mobility functioning information can be reliably captured from clinical notes once adequate resources are provided for sequence labeling methods. We expect that functioning concepts in other domains of the ICF can be identified in similar fashion.

Linking Free Text Documentation of Functioning and Disability to the ICF With Natural Language Processing.

Background: Invaluable information on patient functioning and the complex interactions that define it is recorded in free text portions of the Electronic Health Record (EHR). Leveraging this information to improve clinical decision-making and conduct research requires natural language processing (NLP) technologies to identify and organize the information recorded in clinical documentation. Methods: We used natural language processing methods to analyze information about patient functioning recorded in two collections of clinical documents pertaining to claims for federal disability benefits from the U.S. Social Security Administration (SSA). We grounded our analysis in the International Classification of Functioning, Disability, and Health (ICF), and used the Activities and Participation domain of the ICF to classify information about functioning in three key areas: mobility, self-care, and domestic life. After annotating functional status information in our datasets through expert clinical review, we trained machine learning-based NLP models to automatically assign ICF categories to mentions of functional activity. Results: We found that rich and diverse information on patient functioning was documented in the free text records. Annotation of 289 documents for Mobility information yielded 2,455 mentions of Mobility activities and 3,176 specific actions corresponding to 13 ICF-based categories. Annotation of 329 documents for Self-Care and Domestic Life information yielded 3,990 activity mentions and 4,665 specific actions corresponding to 16 ICF-based categories. NLP systems for automated ICF coding achieved over 80% macro-averaged F-measure on both datasets, indicating strong performance across all ICF categories used. Conclusions: Natural language processing can help to navigate the tradeoff between flexible and expressive clinical documentation of functioning and standardizable data for comparability and learning. The ICF has practical limitations for classifying functional status information in clinical documentation but presents a valuable framework for organizing the information recorded in health records about patient functioning. This study advances the development of robust, ICF-based NLP technologies to analyze information on patient functioning and has significant implications for NLP-powered analysis of functional status information in disability benefits management, clinical care, and research.

Estimating premorbid intelligence in persons with traumatic brain injury: an examination of the Test of Premorbid Functioning.

Knowledge of intelligence is essential for interpreting cognitive performance following traumatic brain injury (TBI). The Test of Premorbid Functioning (ToPF), a word reading test co-normed with the Wechsler Adult Intelligence Scale 4th Edition (WAIS-IV), was examined as a tool for estimating premorbid intelligence in persons with a history of TBI. Fifty-two participants with mild, moderate, or severe TBI were administered the ToPF and WAIS-IV between two weeks and 19 months post-injury. The independent ability of the ToPF/demographic score and the Verbal Comprehension Index (VCI) to predict WAIS-IV Full Scale IQ (FSIQ) was examined, as were discrepancies between ToPF and WAIS-IV scores within and between participants. The ToPF/demographic predicted FSIQ accounted for a significant proportion of variability in actual FSIQ, above and beyond that accounted for by education or time since injury. ToPF and WAIS-IV scores did not differ by injury severity. In our sample, the ToPF/demographic predicted FSIQ underestimated intelligence in a substantial portion of our participants (31%), particularly in those with high average to superior intelligence. Finally, VCI scores were more predictive of actual FSIQ than the ToPF/demographic predicted FSIQ. The ToPF frequently underestimated post-injury intelligence and is therefore not accurately measuring premorbid intelligence in our sample, particularly in those with above average to superior intelligence. Clinicians are encouraged to administer the entire WAIS-IV, or at minimum the VCI subtests, for a more accurate measure of intelligence in those with above average intelligence and history of TBI.

Relating Self-Reported Balance Problems to Sensory Organization and Dual-Tasking in Chronic Traumatic Brain Injury.

BACKGROUND: Individuals who have experienced a traumatic brain injury (TBI) often have residual balance problems. It remains unclear whether these balance problems are driven by vestibular dysfunction or gait automaticity deficits, particularly in the chronic stages of TBI recovery, because most studies include only acute/subacute cases. OBJECTIVES: Compare performance on the Sensory Organization Test vestibular score and Dual-Task test in individuals with and without subjective balance problems at least 1 year after a TBI. Investigate the ability of each test to predict perceived balance problems. DESIGN: Prospective cohort study. SETTING: Rehabilitation department within a single institution. PARTICIPANTS: Fifty adults (21-71 years) with a history of mild, moderate, or severe TBI 1 to 5 years following nonpenetrating TBI. INTERVENTIONS: N/A. METHODS: Measures included the Dual-Task test, Sensory Organization Test, Neurobehavioral Symptom Inventory, Dizziness Handicap Inventory, and assessments of four cognitive domains and depression. Participants who endorsed "feeling dizzy" and "loss of balance" on the Neurobehavioral Symptom Inventory were classified as symptomatic (n = 26) and others as asymptomatic (n = 24). T-tests, chi-square, and regression analyses predicting the Dizziness Handicap Inventory total score were performed. RESULTS: Dual-task gait cost was negatively associated with the Dizziness Handicap Inventory (P = .044), controlling for depression and gender, whereas vestibular scores failed to predict balance-related disability. Symptomatic individuals endorsed more balance problems (P < .001) and depression symptoms (P = .007), had poorer dual-task cognitive output (P = .036), and slower dual-task gait velocity (P = .036) than asymptomatic participants. Groups did not differ on Sensory Organization Test scores. CONCLUSIONS: The nature of balance problems in chronic TBI may be related to automaticity of gait. These findings suggest that patients in the chronic stages of TBI may benefit from dual-task assessments and interventions. Balance rehabilitation should be tailored to patient needs and assess cognition and affect.

Brain bases of recovery following cognitive rehabilitation for traumatic brain injury: a preliminary study.

Many patients with traumatic brain injury (TBI) have persistent cognitive deficits, including decreased attention and working memory. This preliminary study examined fMRI data from a clinical trial implementing a 4-week virtual reality driving intervention to assess how sustained training can improve deficits related to traumatic brain injury. Previously-reported behavioral findings showed improvements in working memory and processing speed in those who received the intervention; this report explores the brain bases of these effects by comparing neural activity related to working memory (n-back task) and resting state connectivity before and after the intervention. In the baseline visit (n = 24), working memory activity was prominent in bilateral DLPFC and prefrontal cortex, anterior insula, medial superior frontal gyrus, left thalamus, bilateral supramarginal / angular gyrus, precuneus, and left posterior middle temporal gyrus. Following intervention, participants showed less global activation on the n-back task, with regions of activity only in the bilateral middle frontal cortex, posterior middle frontal gyrus, and supramarginal gyrus. Activity related to working memory load was reduced for the group that went through the intervention (n = 7) compared to the waitlist control group (n = 4). These results suggest that successful cognitive rehabilitation of working memory in TBI may be associated with increased efficiency of brain networks, evidenced by reduced activation of brain activity during cognitive processing. These results highlight the importance of examining brain activity related to cognitive rehabilitation of attention and working memory after brain injury.

A Systematic Review of the Incidence, Prevalence, Costs, and Activity and Work Limitations of Amputation, Osteoarthritis, Rheumatoid Arthritis, Back Pain, Multiple Sclerosis, Spinal Cord Injury, Stroke, and Traumatic Brain Injury in the United States: A 2019 Update.

OBJECTIVES: To present recent evidence on the prevalence, incidence, costs, activity limitations, and work limitations of common conditions requiring rehabilitation. DATA SOURCES: Medline (PubMed), SCOPUS, Web of Science, and the gray literature were searched for relevant articles about amputation, osteoarthritis, rheumatoid arthritis, back pain, multiple sclerosis, spinal cord injury, stroke, and traumatic brain injury. STUDY SELECTION: Relevant articles (N=106) were included. DATA EXTRACTION: Two investigators independently reviewed articles and selected relevant articles for inclusion. Quality grading was performed using the Methodological Evaluation of Observational Research Checklist and Newcastle-Ottawa Quality Assessment Form. DATA SYNTHESIS: The prevalence of back pain in the past 3 months was 33.9% among community-dwelling adults, and patients with back pain contribute $365 billion in all-cause medical costs. Osteoarthritis is the next most prevalent condition (approximately 10.4%), and patients with this condition contribute $460 billion in all-cause medical costs. These 2 conditions are the most prevalent and costly (medically) of the illnesses explored in this study. Stroke follows these conditions in both prevalence (2.5%-3.7%) and medical costs ($28 billion). Other conditions may have a lower prevalence but are associated with relatively higher per capita effects. CONCLUSIONS: Consistent with previous findings, back pain and osteoarthritis are the most prevalent conditions with high aggregate medical costs. By contrast, other conditions have a lower prevalence or cost but relatively higher per capita costs and effects on activity and work. The data are extremely heterogeneous, which makes anything beyond broad comparisons challenging. Additional information is needed to determine the relative impact of each condition.