Neurorehabilitation and neural repair最新文献

Purpose: Exercise reduces cognitive deficits in traumatic brain injury (TBI), but early post-trauma exercise is often discouraged due to potential harm. The purpose was to evaluate the interaction between pre- and post-injury physical exercise on cognition, neuronal survival and inflammation.

Methods: Rats were either sham-operated and kept sedentary (Sham) or subjected to controlled cortical impact injury and then distributed into sedentary (Tbi), pre-injury exercise (Pre-Tbi), post-injury exercise with early (24 hours, Tbi-early) or late (6 days, Tbi-late) onset, and a combination of pre- and post-injury exercise with early (Pre-Tbi-early) or late (Pre-Tbi-late) onset. Object recognition memory, hippocampal volume, neuronal survival (NeuN⁺) in the hippocampus and perirhinal cortex, and microglial activity (Iba-1) in the hippocampus were evaluated.

Results: All exercise conditions, except TBI-early, attenuated the significant memory impairment at 24-hour retention caused by TBI. Additionally, Pre-TBI-early treatment led to memory improvement at 3-hour retention. Pre-TBI reduced neuronal death and microglial activation in the hippocampus. TBI-late, but not TBI-early, mitigated hippocampal volume loss, loss of mature neurons in the hippocampus, and inflammation. Combining pre-injury and early-onset exercise reduced memory deficits but did not affect neuronal death or microglial activation. Combining pre-injury and late-onset exercise had a similar memory-enhancing effect than late post-injury treatment alone, albeit with reduced effects on neuronal density and neuroinflammation.

Conclusions: Pre-TBI physical exercise reduces the necessary onset delay of post-TBI exercise to obtain cognitive benefits, yet the exact mechanisms underlying this reduction require further research.

Background: The use of prediction tools in stroke rehabilitation research and clinical practice is increasing, but it is not clear whether these prediction tools out-perform clinician predictions.

Objective: This study aimed to compare physiotherapist predictions for independent walking with the Time to Walking Independently after STroke (TWIST) prediction tool.

Methods: Adults with new lower limb weakness and unable to walk independently (Functional Ambulation Category [FAC] < 4) were recruited. At 1 week post-stroke, the treating physiotherapist was asked to predict whether their patient would achieve independent walking by 4, 6, 9, 12, 16, or 26 weeks, or remain dependent. Predictions were also made using the TWIST prediction tool, but not shared. Binary logistic regressions were conducted with the time independent walking was achieved as the dependent variable and independent variables were the physiotherapist and TWIST predictions.

Results: Ninety-one participants were included (median age 71 years, 36 [40%] female). Most participants (67 [74%]) were non-ambulatory (FAC = 0) at 1-week post-stroke. Thirty-seven physiotherapists were recruited. Physiotherapists made accurate predictions for time taken to achieve independent walking for 39 participants (43%). Prediction accuracy was not related to physiotherapist confidence or years of stroke-specific experience. TWIST out-performed physiotherapist predictions (Physiotherapists 76%-77%, TWIST 86%-88% accurate) for participants who achieved independent walking by 4, 6, and 9 weeks post-stroke. Accuracy of physiotherapist and TWIST predictions was similar for 16 and 26 weeks post-stroke.

Conclusions: The TWIST prediction tool is more accurate than physiotherapists at predicting whether a patient will achieve independent walking by 4, 6, or 9 weeks post-stroke, but not for 16 or 26 weeks post-stroke. TWIST may be useful to inform early rehabilitation and discharge planning. Clinical Trial Registration-URL: www.anzctr.org.au Unique Identifier: ACTRN12617001434381.

Background and objective: The biomarkers of hand function may differ based on level of motor impairment after stroke. The objective of this study was to determine the relationship between resting state functional connectivity (RsFC) and unimanual contralesional hand function after stroke and whether brain-behavior relationships differ based on level of grasp function.

Methods: Sixty-two individuals with chronic, left-hemisphere stroke were separated into three functional levels based on Box and Blocks Test performance with the contralesional hand: Low (moved 0 blocks), Moderate (moved >0% but <90% of blocks relative to the ipsilesional hand), and High (moved ≥90% of blocks relative to the ipsilesional hand).

Results: RsFC in the ipsilesional and interhemispheric motor networks was reduced in the Low group compared to the Moderate and High groups. While interhemispheric RsFC correlated with hand function (grip strength and Stroke Impact Scale Hand) across the sample, contralesional RsFC correlated with hand function in the Low group and no measures of connectivity correlated with hand function in the Moderate and High groups. Linear regression modeling found that contralesional RsFC significantly predicted hand function in the Low group, while no measure correlated with hand function in the High group. Corticospinal tract integrity was the only predictor of hand function for the Moderate group and in an analysis across the entire sample.

Conclusions: Differences in brain-hand function relationships based on level of motor impairment may have implications for predictive models of treatment response and the development of intervention protocols aimed at improving hand function after stroke.

Background: Early prediction of poststroke motor recovery is challenging in clinical settings. The Prediction recovery potential (PREP2) algorithm is the most accurate approach for prediction of Upper Limb function available to date but lacks external validation.

Objectives: (i) To externally validate the PREP2 algorithm in a prospective cohort, (ii) to study the characteristics of patients misclassified by the algorithm, and (iii) to compare the performance according to the presence of cognitive syndromes (aphasia, neglect, cognitive disorders).

Methods: We enrolled 143 patients with stroke and upper extremity weakness persistent at Day 3. Evaluation to predict the recovery status according to the PREP2 algorithm included age, SAFE and NIHSS scores at Day 3 and transcranial magnetic stimulation to determine the presence of the motor-evoked potential before day seven. Actual recovery (excellent, good, limited, or poor) was defined based on the Action Research Arm test score at 3 months. Accuracy was computed by comparing the predictions of the PREP2 and the actual category of the patient. Additionally, to investigate misclassifications and the impact of cognitive syndromes, we recorded SAFE and NIHSS scores at Day 7, the Montreal Cognitive Assessment (MoCA) score, the presence of aphasia and neglect and Magnetic Resonance Imaging was used to evaluate the corticospinal tract lesion load.

Results: The PREP2 algorithm showed a very good predictive value with 78% accuracy [95% CI: 71.2%-86.1%], especially for the extreme categories of recovery (EXCELLENT 87.5% [95% CI: 78.9%-96.2%] and POOR 94.9% [95% CI: 87.9%-100%]), and only 46.5% [95% CI: 19.05%-73.25%] for the GOOD category and even worse than chance for the LIMITED category 0%. Pessimistic predictions (false-negative cases) had a drastic improvement in the SAFE score acutely compared to that of well-predicted patients with unfavorable recovery (P < 001). The predictive value of PREP2 decreased significantly when patients had cognitive disorders (MoCA score <24) versus not (69.4% [95% CI: 52.8%-86.1%] vs 93.1% [95% CI: 83.9%-100%], P = .01).

Conclusion: Our study provides an external validation of the PREP2 algorithm in a prospective population and underlines the importance of taking into account cognitive syndromes in motor recovery prediction.

Objective: To explore the efficacy and tolerability of high-frequency repetitive transcranial magnetic stimulation (rTMS) in the treatment of post-stroke working memory (WM) impairment and its changes in brain function.

Methods: In the present randomized, double-blinded, sham-controlled design, 10 Hz rTMS was administered to the left dorsolateral prefrontal cortex (DLPFC) of patients with post-stroke WM impairment for 14 days. Measures included WM (primary outcome), comprehensive neuropsychological tests, and the functional near-infrared spectroscopy test. Patients were assessed at baseline, after the intervention (week 2), and 4 weeks after treatment cessation (week 6).

Results: Of 123 stroke patients, 82 finished the trial. The rTMS group showed more WM improvement at week 2 (t = 5.55, P < .001) and week 6 (t = 2.11, P = .045) than the sham group. Most of the neuropsychological test scores were markedly improved in the rTMS group. In particular, the rTMS group exhibited significantly higher oxygenated hemoglobin content and significantly stronger functional connectivity in the left DLPFC, right pre-motor cortex (PMC), and right superior parietal lobule (SPL) at weeks 2 and 6. Dropout rates were equal (18% [9/50 cases] in each group), and headaches were the most common side effect (rTMS: 36% [18/50 cases]; sham: 30% [15/50 cases]).

Conclusions: High-frequency rTMS was effective in improving post-stroke WM impairment, with good tolerability, and the efficacy lasted up to 4 weeks, which may be due to the activation of the left DLPFC, right PMC, and right SPL brain regions and their synergistic enhancement of neural remodeling.

Background: Balance training covers a range of different modalities and complexity levels for people with multiple sclerosis (MS). When evaluating the effects of balance training across different kinds of interventions, determination of the specific intervention content that predict effects are needed.

Objective: To investigate the effects of balance training on gait and dynamic balance outcomes.

Methods: Four databases were systematically searched. Randomized controlled trials involving people with MS (Expanded Disability Status Scale [EDSS] score ≤7.5) where at least 50% of the intervention targeted balance control were included. Interventions were categorized based on training types. Risk-of-bias was assessed using the Tool for the Assessment of Study Quality and Reporting in Exercise (TESTEX).

Results: A total of 18 included studies involved 902 people with MS (EDSS range from 0 to 7.5). Interventions evaluated with a balance composite score or a mobility test showed a moderate effect size (ES = 0.46 [95% confidence interval (CI) = 0.18 to 0.74]; p < .01) and a small overall ES (ES = 0.19 [95% CI = 0.01-0.36]; p = .04), respectively, across different training types. Stepping and gait speed outcomes showed no effect. Cognitive dual-task training showed a significant effect (ES = 0.81 [95% CI = 0.24 to 1.37]) on subgroup level, when evaluated with a mobility outcome measure. The median TESTEX score on study quality and reporting was 11 (maximum score = 15).

Conclusions: Improvements of balance were found across interventions when measured by balance composite scores and mobility tests, but not when measured by stepping or gait speed outcomes. Large training volume was positively associated with effect on balance. A definition of intensity in balance training is needed for evaluation of its impact on the effect of balance interventions.

Background: The prognosis of prolonged disorders of consciousness (pDoC) in children has consistently posed a formidable challenge in clinical decision-making.

Objective: This study aimed to develop a machine learning (ML) model based on conventional structural magnetic resonance imaging (csMRI) to predict outcomes in children with pDoC.

Methods: A total of 196 children with pDoC were included in this study. Based on the consciousness states 1 year after brain injury, the children were categorized into either the favorable prognosis group or the poor prognosis group. They were then randomly assigned to the training set (n = 138) or the test set (n = 58). Semi-quantitative visual assessments of brain csMRI were conducted and Least Absolute Shrinkage and Selection Operator regression was used to identify significant features predicting outcomes. Based on the selected features, support vector machine (SVM), random forests (RF), and logistic regression (LR) were used to develop csMRI, clinical, and csMRI-clinical-merge models, respectively. Finally, the performances of all models were evaluated.

Results: Seven csMRI features and 4 clinical features were identified as important predictors of consciousness recovery. All models achieved satisfactory prognostic performances (all areas under the curve [AUCs] >0.70). Notably, the csMRI model developed using the SVM exhibited the best performance, with an AUC, accuracy, sensitivity, and specificity of 0.851, 0.845, 0.844, and 0.846, respectively.

Conclusions: A csMRI-based prediction model for the prognosis of children with pDoC was developed, showing potential to predict recovery of consciousness 1 year after brain injury and is worth popularizing in clinical practice.

Background: The rapid advancement of technology-focused strategies in neurorehabilitation has brought optimism to individuals with neurological disorders, caregivers, and physicians while reshaping medical practice and training.

Objectives: We critically examine the implications of technology in neurorehabilitation, drawing on discussions from the 2021 and 2024 World Congress for NeuroRehabilitation. While acknowledging the value of technology, it highlights inherent limitations and ethical concerns, particularly regarding the potential overshadowing of humanistic approaches. The integration of technologies such as robotics, artificial intelligence, neuromodulation, and brain-computer interfaces enriches neurorehabilitation by offering interdisciplinary solutions. However, ethical considerations arise regarding the balance between compensation for deficits, accessibility of technologies, and their alignment with fundamental principles of care. Additionally, the pitfalls of relying solely on neuroimaging data are discussed, stressing the necessity for a more comprehensive understanding of individual variability and clinical skills in rehabilitation.

Results: From a clinical perspective, the article advocates for realistic solutions that prioritize individual needs, quality of life, and social inclusion over technological allure. It underscores the importance of modesty and honesty in responding to expectations while emphasizing the uniqueness of each individual's experience. Moreover, it argues for the preservation of human-centric approaches alongside technological advancements, recognizing the invaluable role of clinical observation and human interaction in rehabilitation.

Conclusion: Ultimately, the article calls for a balanced attitude that integrates both scientific and humanistic perspectives in neurorehabilitation. It highlights the symbiotic relationship between the sciences and humanities, advocating for philosophical questioning to guide the ethical implementation of new technologies and foster interdisciplinary dialogue.

Background: Patients with poststroke pusher syndrome (PS) require longer duration of rehabilitation and more supplemental care after discharge. Effective treatment of PS remains a challenge. The role of repetitive transcranial magnetic stimulation (rTMS) for PS has not been examined.

Objective: Assess the efficacy of rTMS for patients with poststroke PS in reducing pushing behavior, enhancing motor recovery and improving mobility.

Methods: A randomized, patient- and assessor-blinded sham-controlled trial with intention-to-treat analysis was conducted. Thirty-four eligible patients with poststroke PS were randomly allocated to receive either rTMS or sham rTMS for 2 weeks. Pushing behavior on the Burke lateropulsion scale and scale for contraversive pushing, motor function on Fugl-Meyer assessment scale-motor domain (FMA-m) and mobility on modified Rivermead mobility index were measured at baseline, 1 and 2 weeks after intervention. Repeated-measures analysis of covariance was used for data analysis.

Results: There was no significant interaction between intervention and time on Burke lateropulsion scale (F = 2.747, P = .076), scale for contraversive pushing (F = 1.583, P = .214), or change of modified Rivermead mobility index (F = 1.183, P = .297). However, a significant interaction between intervention and time was observed for FMA-m (F = 5.464, P = .019). Post hoc comparisons of FMA-m show better improvement in rTMS group with mean differences of 12.7 (95% CI -7.3 to 32.7) and 15.7 (95% CI -4.6 to 36.0) at post-treatment week 1 and week 2 respectively.

Conclusions: rTMS did not demonstrate significant efficacy in improving pushing behavior and mobility in patients with PS. However, rTMS might have potential effect in enhancing motor function for patients with PS.

Registration: The study was registered in the Chinese Clinical Trial Registry (registration No. ChiCTR2200058015 at http://www.chictr.org.cn/searchprojen.aspx) on March 26, 2022.

Background: Gait disturbances are exacerbated in people with Parkinson's disease (PD) during dual-task walking (DTW). Transcranial direct current stimulation (tDCS) has been shown to exert beneficial effects on gait performance and cortical excitability in PD; however, its combined effects with treadmill training (TT) remain undetermined.

Objective: To investigate the effects of tDCS followed by TT on DTW performance and cortical excitability in individuals with PD.

Methods: Thirty-four PD participants were randomized to dorsal lateral prefrontal cortex (DLPFC) tDCS and TT group (DLPFC tDCS + TT group) or sham tDCS and TT group (sham tDCS + TT group) for 50 minutes per session (20 minutes tDCS followed by 30 minutes TT), 12 sessions within 5 weeks (2-3 sessions each week). Outcome measures included cognitive dual-task walking (CDTW), motor dual-task walking (MDTW), usual walking performance, cortical excitability, functional mobility, cognitive function, and quality of life.

Results: The DLPFC tDCS + TT group exerted significantly greater improvement in CDTW velocity (P = .046), cadence (P = .043), and stride time (P = .041) compared to sham tDCS + TT group. In addition, DLPFC tDCS + TT group demonstrated a significant increase in resting motor threshold of stimulated hemisphere compared with sham tDCS + TT group (P = .026). However, no significant differences between groups were found in MDTW performance and other outcomes.

Conclusion: Twelve-session DLPFC tDCS followed by TT significantly improved CDTW performance and decreased cortical excitability more than TT alone in individuals with PD. Applying DLPFC tDCS prior to TT could be suggested for gait rehabilitation in individuals with PD.

Clinical trial registration number: Australian New Zealand Clinical Trials Registry ACTRN12622000101785.