Walking Outcome After Traumatic Paraplegic Spinal Cord Injury: The Function of Which Myotomes Makes a Difference?

BACKGROUND: Accurate prediction of walking function after a traumatic spinal cord injury (SCI) is crucial for an appropriate tailoring and application of therapeutical interventions. Long-term outcome of ambulation is strongly related to residual muscle function acutely after injury and its recovery potential. The identification of the underlying determinants of ambulation, however, remains a challenging task in SCI, a neurological disorder presented with heterogeneous clinical manifestations and recovery trajectories. OBJECTIVES: Stratification of walking function and determination of its most relevant underlying muscle functions based on stratified homogeneous patient subgroups. METHODS: Data from individuals with paraplegic SCI were used to develop a prediction-based stratification model, applying unbiased recursive partitioning conditional inference tree (URP-CTREE). The primary outcome was the 6-minute walk test at 6 months after injury. Standardized neurological assessments ≤15 days after injury were chosen as predictors. Resulting subgroups were incorporated into a subsequent node-specific analysis to attribute the role of individual lower extremity myotomes for the prognosis of walking function. RESULTS: Using URP-CTREE, the study group of 361 SCI patients was divided into 8 homogeneous subgroups. The node specific analysis uncovered that proximal myotomes L2 and L3 were driving factors for the differentiation between walkers and non-walkers. Distal myotomes L4-S1 were revealed to be responsible for the prognostic distinction of indoor and outdoor walkers (with and without aids). CONCLUSION: Stratification of a heterogeneous population with paraplegic SCI into more homogeneous subgroups, combined with the identification of underlying muscle functions prospectively determining the walking outcome, enable potential benefit for application in clinical trials and practice

Strategies to augment volitional and reflex function may improve locomotor capacity following incomplete spinal cord injury

Many studies highlight the remarkable plasticity demonstrated by spinal circuits following an incomplete spinal cord injury (SCI). Such plasticity can contribute to improvements in volitional motor recovery, such as walking function, although similar mechanisms underlying this recovery may also contribute to the manifestation of exaggerated responses to afferent input, or spastic behaviors. Rehabilitation interventions directed toward augmenting spinal excitability have shown some initial success in improving locomotor function. However, the potential effects of these strategies on involuntary motor behaviors may be of concern. In this article, we provide a brief review of the mechanisms underlying recovery of volitional function and exaggerated reflexes, and the potential overlap between these changes. We then highlight findings from studies that explore changes in spinal excitability during volitional movement in controlled conditions, as well as altered kinematic and behavioral performance during functional tasks. The initial focus will be directed toward recovery of reflex and volitional behaviors following incomplete SCI, followed by recent work elucidating neurophysiological mechanisms underlying patterns of static and dynamic muscle activation following chronic incomplete SCI during primarily single-joint movements. We will then transition to studies of locomotor function and the role of altered spinal integration following incomplete SCI, including enhanced excitability of specific spinal circuits with physical and pharmacological interventions that can modulate locomotor output. The effects of previous and newly developed strategies will need to focus on changes in both volitional function and involuntary spastic reflexes for the successful translation of effective therapies to the clinical setting

Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation.

After an initial period of recovery, human neurological injury has long been thought to be static. In order to improve quality of life for those suffering from stroke, spinal cord injury, or traumatic brain injury, researchers have been working to restore the nervous system and reduce neurological deficits through a number of mechanisms. For example, neurobiologists have been identifying and manipulating components of the intra- and extracellular milieu to alter the regenerative potential of neurons, neuro-engineers have been producing brain-machine and neural interfaces that circumvent lesions to restore functionality, and neurorehabilitation experts have been developing new ways to revitalize the nervous system even in chronic disease. While each of these areas holds promise, their individual paths to clinical relevance remain difficult. Nonetheless, these methods are now able to synergistically enhance recovery of native motor function to levels which were previously believed to be impossible. Furthermore, such recovery can even persist after training, and for the first time there is evidence of functional axonal regrowth and rewiring in the central nervous system of animal models. To attain this type of regeneration, rehabilitation paradigms that pair cortically-based intent with activation of affected circuits and positive neurofeedback appear to be required-a phenomenon which raises new and far reaching questions about the underlying relationship between conscious action and neural repair. For this reason, we argue that multi-modal therapy will be necessary to facilitate a truly robust recovery, and that the success of investigational microscopic techniques may depend on their integration into macroscopic frameworks that include task-based neurorehabilitation. We further identify critical components of future neural repair strategies and explore the most updated knowledge, progress, and challenges in the fields of cellular neuronal repair, neural interfacing, and neurorehabilitation, all with the goal of better understanding neurological injury and how to improve recovery

Effects of Training Intensity on Locomotor Performance in Individuals With Chronic Spinal Cord Injury: A Randomized Crossover Study

Background. Many physical interventions can improve locomotor function in individuals with motor incomplete spinal cord injury (iSCI), although the training parameters that maximize recovery are not clear. Previous studies in individuals with other neurologic injuries suggest the intensity of locomotor training (LT) may positively influence walking outcomes. However, the effects of intensity during training of individuals with iSCI have not been tested. Objective. The purpose of this pilot, blinded-assessor randomized trial was to evaluate the effects of LT intensity on walking outcomes in individuals with iSCI. Methods. Using a crossover design, ambulatory participants with iSCI \u3e1 year duration performed either high- or low-intensity LT for ≤20 sessions over 4 to 6 weeks. Four weeks following completion, the training interventions were alternated. Targeted intensities focused on achieving specific ranges of heart rate (HR) or ratings of perceived exertion (RPE), with intensity manipulated by increasing speeds or applying loads. Results. Significantly greater increases in peak treadmill speeds (0.18 vs 0.02 m/s) and secondary measures of metabolic function and overground speed were observed following high- versus low-intensity training, with no effects of intervention order. Moderate to high correlations were observed between differences in walking speed or distances and differences in HRs or RPEs during high- versus low-intensity training. Conclusion. This pilot study provides the first evidence that the intensity of stepping practice may be an important determinant of LT outcomes in individuals with iSCI. Whether such training is feasible in larger patient populations and contributes to improved locomotor outcomes deserves further consideration

Biomechanics

Biomechanics is a vast discipline within the field of Biomedical Engineering. It explores the underlying mechanics of how biological and physiological systems move. It encompasses important clinical applications to address questions related to medicine using engineering mechanics principles. Biomechanics includes interdisciplinary concepts from engineers, physicians, therapists, biologists, physicists, and mathematicians. Through their collaborative efforts, biomechanics research is ever changing and expanding, explaining new mechanisms and principles for dynamic human systems. Biomechanics is used to describe how the human body moves, walks, and breathes, in addition to how it responds to injury and rehabilitation. Advanced biomechanical modeling methods, such as inverse dynamics, finite element analysis, and musculoskeletal modeling are used to simulate and investigate human situations in regard to movement and injury. Biomechanical technologies are progressing to answer contemporary medical questions. The future of biomechanics is dependent on interdisciplinary research efforts and the education of tomorrow’s scientists

Prediction of three-dimensional crutch walking patterns using a torque-driven model

Computational prediction of 3D crutch-assisted walking patterns is a challenging problem that could be applied to study different biomechanical aspects of crutch walking in virtual subjects, to assist physiotherapists to choose the optimal crutch walking pattern for a specific subject, and to help in the design and control of exoskeletons, when crutches are needed for balance. The aim of this work is to generate a method to predict three-dimensional crutch-assisted walking motions following different patterns without tracking any experimental data. To reach this goal, we collected gait data from a healthy subject performing a four-point non-alternating crutch walking pattern, and developed a 3D torque-driven full-body model of the subject including the crutches and foot- and crutch-ground contact models. First, we developed a predictive (i.e., no tracking of experimental data) optimal control problem formulation to predict crutch walking cycles following the same pattern as the experimental data collected, using different cost functions. To reduce errors with respect to reference data, a cost function combining minimization terms of angular momentum, mechanical power, joint jerk and torque change was chosen. Then, the problem formulation was adapted to handle different foot- and crutch-ground conditions to make it capable of predicting three new crutch walking patterns, one of them at different speeds. A key aspect of our algorithm is that having ground reactions as additional controls allows one to define phases inside the cycle without the need of formulating a multiple-phase problem, thus facilitating the definition of different crutch walking patterns.Postprint (author's final draft

The association of selected multiple sclerosis symptoms with disability and quality of life:a large Danish self-report survey

Abstract Background People with multiple sclerosis (MS) experience a wide range of unpredictable and variable symptoms. The symptomatology of MS has previously been reported in large sample registry studies; however, some symptoms may be underreported in registries based on clinician-reported outcomes and how the symptoms are associated with quality of life (QoL) are often not addressed. The aim of this study was to comprehensively evaluate the frequency of selected MS related symptoms and their associations with disability and QoL in a large self-report study. Methods We conducted a cross-sectional questionnaire survey among all patients at the Danish Multiple Sclerosis Center, Copenhagen University Hospital, Denmark. The questionnaire included information on clinical and sociodemographic characteristics, descriptors of QoL and disability, as well as prevalence and severity of the following MS symptoms: impaired ambulation, spasticity, chronic pain, fatigue, bowel and bladder dysfunction, and sleep disturbances. Results Questionnaires were returned by 2244/3606 (62%). Participants without MS diagnosis or incomplete questionnaires were excluded, n = 235. A total of 2009 questionnaires were included for analysis (mean age 49.4 years; mean disease duration 11.7 years; and 69% were women). The most frequently reported symptoms were bowel and bladder dysfunction (74%), fatigue (66%), sleep disturbances (59%), spasticity (51%) and impaired ambulation (38%). With exception of fatigue and sleep disturbances, all other symptoms increased in severity with higher disability level. Invisible symptoms (also referred to as hidden symptoms) such as fatigue, pain and sleep disturbances had the strongest associations with the overall QoL. Conclusion We found invisible symptoms highly prevalent, even at mild disability levels. Fatigue, pain and sleep disturbances had the strongest associations with the overall QoL and were more frequently reported in our study compared with previous registry-based studies. These symptoms may be underreported in registries based on clinician reported outcomes, which emphasizes the importance of including standardized patient reported outcomes in nationwide registries to better understand the impact of the symptom burden in MS

The Development of Limb Accelerations as a Measure of Neuromuscular Impairment and Predictor of Ambulatory Ability Following Spinal Cord Injury

After a spinal cord injury (SCI), clinicians must quickly decide if they want to focus therapy towards gait training or wheeled mobility interventions to maximize an individual's functional mobility by discharge. Clinical prediction rules (CPRs) such as those that use age, strength, and sensation, can assist clinicians in making those difficult decisions, but for individuals with an incomplete SCI, these CPRs are often inaccurate. Additionally, these models only predict whether an individual can walk a short distance without physical assistance, which is not a sufficient description of functional ambulation. Limb accelerations (LA), captured unobtrusively and at a low cost from wearable accelerometers, may provide a responsive and informative movement biomarker of neuromuscular impairment that can be used to determine more accurate predictions of ambulatory ability among those who would benefit from them the most. Our long-term goal is to build a new CPR using LA that predicts functional ambulation after SCI, thus enabling appropriately targeted mobility training. As a first step towards this goal, we utilized a cross-sectional study to build a foundational knowledge of LA and its relationship to measures of neuromuscular impairment (Aim 1) and ambulatory ability (Aim 2) using machine learning techniques and a sample with chronic, motor incomplete SCI and known, diverse functional abilities. Using a longitudinal study consisting of individuals with acute, incomplete SCI, we established that LA is reliable when measured acutely at admission to inpatient rehabilitation (Aim 3a). We also investigated the changes in LA over time (Aim 3b) and in relation to clinical measures (Aim 4a) and explored the potential utility of LA measured at admission to inpatient rehabilitation to predict long-term ambulatory ability (Aim 4b) for those with acute, incomplete SCI. These results demonstrated that LA is a reliable and clinically-relevant metric that is likely to improve the prediction of ambulatory ability, thus improving long-term, functional outcomes for individuals with SCI