Biomarkers of stroke recovery: Consensus-based core recommendations from the Stroke Recovery and Rehabilitation Roundtable

Investigating functional connectivity related to stroke recovery: A systematic review

INTRODUCTION

Stroke recovery is a complex process influenced by various factors, including specific neural reorganization. The objective of this systematic review was to identify important functional connectivity (FC) changes in resting-state fMRI data that were often correlated with motor, emotional, and cognitive outcome improvement.

METHOD

A systematic search using PubMed and SCOPUS databases was conducted to identify relevant studies published between 2010 and 2023.

RESULTS

A total of 766 studies were identified, of which 20 studies (602 S individuals) met the inclusion criteria. Fourteen studies focussed on motor recovery while six on cognitive recovery. All studies reported interhemispheric FC to be strongly associated with motor and cognitive recovery. The preservation and changes of M1-M1 (eight incidences) and M1-SMA (nine incidences) FC were found to be strongly correlated with motor function improvement. For cognitive recovery, restoration and preservation of FC with and between default mode network (DMN)-related regions were important for the process.

CONCLUSIONS

This review identified specific patterns of FC that were consistently reported with recovery of motor and cognitive function. The findings may serve in refining future management strategies to enhance patient outcomes.

Stroke rehabilitation: from diagnosis to therapy

Stroke remains a significant global health burden, necessitating comprehensive and innovative approaches in rehabilitation to optimize recovery outcomes. This paper provides a thorough exploration of rehabilitation strategies in stroke management, focusing on diagnostic methods, acute management, and diverse modalities encompassing physical, occupational, speech, and cognitive therapies. Emphasizing the importance of early identification of rehabilitation needs and leveraging technological advancements, including neurostimulation techniques and assistive technologies, this manuscript highlights the challenges and opportunities in stroke rehabilitation. Additionally, it discusses future directions, such as personalized rehabilitation approaches, neuroplasticity concepts, and advancements in assistive technologies, which hold promise in reshaping the landscape of stroke rehabilitation. By delineating these multifaceted aspects, this manuscript aims to provide insights and directions for optimizing stroke rehabilitation practices and enhancing the quality of life for stroke survivors.

Predicting Role of GFAP and UCH-L1 biomarkers in Spontaneous Subarachnoid Hemorrhage: a preliminary study to evaluate in the short-term their correlation with severity of bleeding and prognosis

BACKGROUND

Spontaneous non-traumatic subarachnoid hemorrhage (sSAH) is a severe brain vascular accident. Glial fibrillary acidic protein (GFAP) and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) can be theoretically assayed to predict a patient's progression, picturing different aspects of clinical failure after sSAH. The study aims to: a) explore the correlation between sSAH blood volume and biomarkers variation; b) evaluate if these can be predictive of the neurogenic response after sSAH and be prognostic of patient outcome; c) establish eventual threshold levels of biomarkers to define patients' clinical outcome.

METHODS

Blood volumetry at CT scan upon admission, GFAP and UCH-L1 were collected at 24 h, at 72 h, and after 7 days from hemorrhage. Trends and cut-off serum sampling were determined. Clinical outcome was assessed with mRS scale at 14 days.

RESULTS

A strong correlation between GFAP and UCH-L1 and blood diffusion volume in all explored serum intervals related to unfavorable outcome. GFAP and UCH-L1 were very early predictors of unfavorable outcomes at 24 h from sSAH (p = 0.002 and 0.011 respectively). Threshold levels of UCH-L1 apparently revealed a very early, early and late predictor of unfavorable outcomes.

CONCLUSION

GFAP and UCH-L1 represent a potential tool for prompt monitoring and customization of therapies in neurosurgical patients.

Vagus nerve stimulation in cerebral stroke: biological mechanisms, therapeutic modalities, clinical applications, and future directions

Stroke is a major disorder of the central nervous system that poses a serious threat to human life and quality of life. Many stroke victims are left with long-term neurological dysfunction, which adversely affects the well-being of the individual and the broader socioeconomic impact. Currently, post-stroke brain dysfunction is a major and difficult area of treatment. Vagus nerve stimulation is a Food and Drug Administration-approved exploratory treatment option for autism, refractory depression, epilepsy, and Alzheimer's disease. It is expected to be a novel therapeutic technique for the treatment of stroke owing to its association with multiple mechanisms such as altering neurotransmitters and the plasticity of central neurons. In animal models of acute ischemic stroke, vagus nerve stimulation has been shown to reduce infarct size, reduce post-stroke neurological damage, and improve learning and memory capacity in rats with stroke by reducing the inflammatory response, regulating blood-brain barrier permeability, and promoting angiogenesis and neurogenesis. At present, vagus nerve stimulation includes both invasive and non-invasive vagus nerve stimulation. Clinical studies have found that invasive vagus nerve stimulation combined with rehabilitation therapy is effective in improving upper limb motor and cognitive abilities in stroke patients. Further clinical studies have shown that non-invasive vagus nerve stimulation, including ear/cervical vagus nerve stimulation, can stimulate vagal projections to the central nervous system similarly to invasive vagus nerve stimulation and can have the same effect. In this paper, we first describe the multiple effects of vagus nerve stimulation in stroke, and then discuss in depth its neuroprotective mechanisms in ischemic stroke. We go on to outline the results of the current major clinical applications of invasive and non-invasive vagus nerve stimulation. Finally, we provide a more comprehensive evaluation of the advantages and disadvantages of different types of vagus nerve stimulation in the treatment of cerebral ischemia and provide an outlook on the developmental trends. We believe that vagus nerve stimulation, as an effective treatment for stroke, will be widely used in clinical practice to promote the recovery of stroke patients and reduce the incidence of disability.

Prediagnosis recognition of acute ischemic stroke by artificial intelligence from facial images

Stroke is a major threat to life and health in modern society, especially in the aging population. Stroke may cause sudden death or severe sequela-like hemiplegia. Although computed tomography (CT) and magnetic resonance imaging (MRI) are standard diagnosis methods, and artificial intelligence models have been built based on these images, shortage in medical resources and the time and cost of CT/MRI imaging hamper fast detection, thus increasing the severity of stroke. Here, we developed a convolutional neural network model by integrating four networks, Xception, ResNet50, VGG19, and EfficientNetb1, to recognize stroke based on 2D facial images with a cross-validation area under curve (AUC) of 0.91 within the training set of 185 acute ischemic stroke patients and 551 age- and sex-matched controls, and AUC of 0.82 in an independent data set regardless of age and sex. The model computed stroke probability was quantitatively associated with facial features, various clinical parameters of blood clotting indicators and leukocyte counts, and, more importantly, stroke incidence in the near future. Our real-time facial image artificial intelligence model can be used to rapidly screen and prediagnose stroke before CT scanning, thus meeting the urgent need in emergency clinics, potentially translatable to routine monitoring.

Data-driven biomarkers better associate with stroke motor outcomes than theory-based biomarkers

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have associated motor outcomes with the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to model chronic motor outcomes after stroke and compares the accuracy of these associations to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients from the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Stroke Recovery Working Group. Using the explained variance metric to measure the strength of the association between chronic motor outcomes and imaging biomarkers, we compared theory-based biomarkers, like lesion load to known motor tracts, to three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had stronger associations with chronic motor outcomes accuracy than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R 2 = 0.210, P < 0.001), performing significantly better than the theory-based biomarkers of lesion load of the corticospinal tract (R 2 = 0.132, P < 0.001) and of multiple descending motor tracts (R 2 = 0.180, P < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R 2 = 0.200, P < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R 2 = 0.167, P < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved the strength of associations for theory-based and data-driven biomarkers. Combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R 2 = 0.241, P < 0.001. Overall, these results demonstrate that out-of-sample associations between chronic motor outcomes and data-driven imaging features, particularly when lesion data is represented in terms of structural disconnection, are stronger than associations between chronic motor outcomes and theory-based biomarkers. However, combining both theory-based and data-driven models provides the most robust associations.

Self-organizing recruitment of compensatory areas maximizes residual motor performance post-stroke

Whereas the orderly recruitment of compensatory motor cortical areas after stroke depends on the size of the motor cortex lesion affecting arm and hand movements, the mechanisms underlying this reorganization are unknown. Here, we hypothesized that the recruitment of compensatory areas results from the motor system's goal to optimize performance given the anatomical constraints before and after the lesion. This optimization is achieved through two complementary plastic processes: a homeostatic regulation process, which maximizes information transfer in sensory-motor networks, and a reinforcement learning process, which minimizes movement error and effort. To test this hypothesis, we developed a neuro-musculoskeletal model that controls a 7-muscle planar arm via a cortical network that includes a primary motor cortex and a premotor cortex that directly project to spinal motor neurons, and a contra-lesional primary motor cortex that projects to spinal motor neurons via the reticular formation. Synapses in the cortical areas are updated via reinforcement learning and the activity of spinal motor neurons is adjusted through homeostatic regulation. The model replicated neural, muscular, and behavioral outcomes in both non-lesioned and lesioned brains. With increasing lesion sizes, the model demonstrated systematic recruitment of the remaining primary motor cortex, premotor cortex, and contra-lesional cortex. The premotor cortex acted as a reserve area for fine motor control recovery, while the contra-lesional cortex helped avoid paralysis at the cost of poor joint control. Plasticity in spinal motor neurons enabled force generation after large cortical lesions despite weak corticospinal inputs. Compensatory activity in the premotor and contra-lesional motor cortex was more prominent in the early recovery period, gradually decreasing as the network minimized effort. Thus, the orderly recruitment of compensatory areas following strokes of varying sizes results from biologically plausible local plastic processes that maximize performance, whether the brain is intact or lesioned.

Clinically relevant estimation of minimal number of trials for the uncontrolled manifold analysis

Movement biomarkers are crucial for assessing sensorimotor impairments and tracking the effects of interventions over time. The Uncontrolled Manifold (UCM) analysis has been proposed as a novel biomarker for evaluating movement stability and coordination in various motor tasks across neurological and musculoskeletal disorders. Through inter-trial analysis, the UCM partitions the variance of elemental variables (e.g., finger forces) into components that affect (VORT) and do not affect (VUCM) a performance variable (e.g., total force). A third index, ΔV, is computed as the normalized difference between VORT and VUCM. However, the minimum number of trials required to achieve stable UCM estimates, considering its clinimetric properties, is unknown. This study aimed to determine the minimal number (N) of trials for UCM estimates by computing bootstrap estimates of standard errors (SE) at different N trials using thresholds based on the minimal detectable change (MDC, i.e., the minimum change in an outcome measure beyond measurement error). Thirteen adults (24.6 ± 1.1 years old) performed a finger-pressing coordination task. We computed the 95 % confidence intervals (CI) of bootstrap SE distributions for each UCM estimate and detected the lowest number of trials with the 95 % CI of SE below each MDC threshold. We found the minimal N of trials required was VUCM = 14, VORT = 4 and ΔV = 18. Our findings highlight that a relatively low number of trials (i.e., N = 18) are sufficient to compute all UCM estimates beyond the MDC, supporting the use of the UCM framework in clinical settings where many repetitions of a motor task are not practical.

Defining Trajectories of Linguistic, Cognitive-Communicative, and Quality of Life Outcomes in Aphasia: Longitudinal Observational Study Protocol

Objective

To describe the trajectories of linguistic, cognitive-communicative, and health-related quality of life (HRQOL) outcomes after stroke in persons with aphasia.

Design

Longitudinal observational study from inpatient rehabilitation to 18 months after stroke.

Setting

Four US mid-west inpatient rehabilitation facilities (IRFs).

Participants

We plan to recruit 400 adult (older than 21 years) English speakers who meet the following inclusion criteria: (1) Diagnosis of aphasia after a left-hemisphere infarct confirmed by CT scan or magnetic resonance imaging (MRI); (2) first admission for inpatient rehabilitation due to a neurologic event; and (3) sufficient cognitive capacity to provide informed consent and participate in testing. Exclusion criteria include any neurologic condition other than stroke that could affect language, cognition or speech, such as Parkinson's disease, Alzheimer's disease, traumatic brain injury, or the presence of right-hemisphere lesions.

Interventions

Not applicable.

Main Outcome Measures

Subjects are administered a test battery of linguistic, cognitive-communicative, and HRQOL measures. Linguistic measures include the Western Aphasia Battery-Revised and the Apraxia of Speech Rating Scale. Cognitive-communicative measures include the Communication Participation Item Bank, Connor's Continuous Performance Test-3, the Communication Confidence Rating Scale for Aphasia, the Communication Effectiveness Index, the Neurological Quality of Life measurement system (Neuro-QoL) Communication short form, and the Neuro-QoL Cognitive Function short form. HRQOL measures include the 39-item Stroke & Aphasia Quality of Life Scale, Neuro-QoL Fatigue, Sleep Disturbance, Depression, Ability to Participate in Social Roles & Activities, and Satisfaction with Social Roles & Activities tests, and the Patient-Reported Outcome Measurement and Information System 10-item Global Health short form. The test battery is administered initially during inpatient rehabilitation, and at 3-, 6-, 12-, and 18-months post-IRF discharge. Biomarker samples are collected via saliva samples at admission and a subgroup of participants also undergo resting state fMRI scans.

Results

Not applicable.

Conclusions

This longitudinal observational study will develop trajectory models for recovery of clinically relevant linguistic, cognitive-communicative, and quality of life outcomes over 18 months after inpatient rehabilitation. Models will identify individual differences in the patterns of recovery based on variations in personal, genetic, imaging, and therapy characteristics. The resulting models will provide an unparalleled representation of recovery from aphasia resulting from stroke. This improved understanding of recovery will enable clinicians to better tailor and plan rehabilitation therapies to individual patient's needs.

Corticomotor pathway function and recovery after stroke: a look back and a way forward

Stroke is a leading cause of adult disability that results in motor deficits and reduced independence. Regaining independence relies on motor recovery, particularly regaining function of the hand and arm. This review presents evidence from human studies that have used transcranial magnetic stimulation (TMS) to identify neurophysiological mechanisms underlying upper limb motor recovery early after stroke. TMS studies undertaken at the subacute stage after stroke have identified several neurophysiological factors that can drive motor impairment, including membrane excitability, the recruitment of corticomotor neurons, and glutamatergic and GABAergic neurotransmission. However, the inherent variability and subsequent poor reliability of measures derived from motor evoked potentials (MEPs) limit the use of TMS for prognosis at the individual patient level. Currently, prediction tools that provide the most accurate information about upper limb motor outcomes for individual patients early after stroke combine clinical measures with a simple neurophysiological biomarker based on MEP presence or absence, i.e. MEP status. Here, we propose a new compositional framework to examine MEPs across several upper limb muscles within a threshold matrix. The matrix can provide a more comprehensive view of corticomotor function and recovery after stroke by quantifying the evolution of subthreshold and suprathreshold MEPs through compositional analyses. Our contention is that subthreshold responses might be the most sensitive to reduced output of corticomotor neurons, desynchronized firing of the remaining neurons, and myelination processes that occur early after stroke. Quantifying subthreshold responses might provide new insights into post-stroke neurophysiology and improve the accuracy of prediction of upper limb motor outcomes.

Establishing minimal clinically important differences and cut-off values for the lower limb motricity index and trunk control test in older patients with acute stroke: a prospective cohort study

OBJECTIVE

To establish the Minimal Clinically Important Differences (MCIDs) for lower limb strength measured by the Motricity Index (LLMI) and trunk function assessed by the Trunk Control Test (TCT) in the acute phase of stroke in older patients. Further, the study sought to determine the cutoff values predicting functional prognosis at discharge for both the LLMI and TCT.

METHODS

This prospective cohort study was conducted for older patients (≥65 years) admitted for acute stroke, receiving guideline-based stroke care that includes early rehabilitation. The LLMI and TCT were measured within 7 days of admission and at discharge. The MCID was derived from receiving operating characteristic curves, based on a ≥ 1 point shift in the modified Rankin Scale (mRS) from admission to discharge. A good functional prognosis at discharge was defined as an mRS score of ≤ 3.

RESULTS

A total of 201 older patients with acute stroke were included. The TCT achieved an MCID of 13 (area under the curve [AUC] = 0.704, 95% confidence interval [CI]: 0.633-0.775), whereas the LLMI lacked the precision to produce a significant MCID. The optimal cutoff points for predicting a good outcome were found to be an LLMI score of 65 (AUC = 0.770, 95% CI: 0.705-0.835) and a TCT score of 25 (AUC = 0.827, 95% CI: 0.768-0.887) upon admission.

CONCLUSIONS

This study identified a valid MCID for the TCT, failed to do so for the LLMI, and established cutoff values for both the LLMI and TCT that can predict good outcomes in older patients with acute stroke.

Improving physical movement during stroke rehabilitation: investigating associations between sleep measured by wearable actigraphy technology, fatigue, and key biomarkers

BACKGROUND

Sleep disturbance and fatigue are common in individuals undergoing inpatient rehabilitation following stroke. Understanding the relationships between sleep, fatigue, motor performance, and key biomarkers of inflammation and neuroplasticity could provide valuable insight into stroke recovery, possibly leading to personalized rehabilitation strategies. This study aimed to investigate the influence of sleep quality on motor function following stroke utilizing wearable technology to obtain objective sleep measurements. Additionally, we aimed to determine if there were relationships between sleep, fatigue, and motor function. Lastly, the study aimed to determine if salivary biomarkers of stress, inflammation, and neuroplasticity were associated with motor function or fatigue post-stroke.

METHODS

Eighteen individuals who experienced a stroke and were undergoing inpatient rehabilitation participated in a cross-sectional observational study. Following consent, participants completed questionnaires to assess sleep patterns, fatigue, and quality of life. Objective sleep was measured throughout one night using the wearable Philips Actiwatch. Upper limb motor performance was assessed on the following day and saliva was collected for biomarker analysis. Correlation analyses were performed to assess the relationships between variables.

RESULTS

Participants reported poor sleep quality, frequent awakenings, and difficulties falling asleep following stroke. We identified a significant negative relationship between fatigue severity and both sleep quality (r=-0.539, p = 0.021) and participants experience of awakening from sleep (r=-0.656, p = 0.003). A significant positive relationship was found between grip strength on the non-hemiplegic limb and salivary gene expression of Brain-derived Neurotrophic Factor (r = 0.606, p = 0.028), as well as a significant negative relationship between grip strength on the hemiplegic side and salivary gene expression of C-reactive Protein (r=-0.556, p = 0.048).

CONCLUSION

The findings of this study emphasize the importance of considering sleep quality, fatigue, and biomarkers in stroke rehabilitation to optimize recovery and that interventions may need to be tailored to the individual. Future longitudinal studies are required to explore these relationships over time. Integrating wearable technology for sleep and biomarker analysis can enhance monitoring and prediction of outcomes following stroke, ultimately improving rehabilitation strategies and patient outcomes.

Clinical applicability of automated tractography for stroke rehabilitation: Z-score conversion of fractional anisotropy

[Purpose] To expand the applicability of diffusion-tensor tractography fractional anisotropy for stroke rehabilitation, this study aimed to provide references for representative neural tracts from non-lesioned hemispheres. Therefore, we applied the assessment of neural integrity to representative stroke patients using Z-score conversion. [Participants and Methods] Fractional anisotropy values were assessed in neural tracts, including the corticospinal tract, inferior fronto-occipital fasciculus, uncinate fasciculus, and anterior thalamic radiation, of stroke patients receiving acute care. [Results] Data were collected from 60 patients for the non-lesioned right hemisphere and 68 patients for the non-lesioned left hemisphere. Mean fractional anisotropy values in the corticospinal tract and inferior fronto-occipital fasciculus were notably elevated, reaching approximately 0.6 and 0.5, respectively. The mean fractional anisotropy values for other neural tracts were approximately 0.4, and, the overall standard deviations were approximately 0.04. In two typical stroke patients assessed using Z-scores, the scores in the corticospinal tract corresponded to the severity of the hemiparesis. The scores in the anterior thalamic radiation and inferior fronto-occipital fasciculus were associated with more significant brain dysfunction, including inattention and aphasia. [Conclusion] In this study, the Z-score findings related to stroke symptoms align with those reported in the literature, indicating the appropriateness of the methodology used and its potential in future applications.

Biomarkers of Motor Outcomes After Stroke

Predicting motor outcomes after stroke based on clinical judgment alone is often inaccurate and can lead to inefficient and inequitable allocation of rehabilitation resources. Prediction tools are being developed so that clinicians can make evidence-based, accurate, and reproducible prognoses for individual patients. Biomarkers of corticospinal tract structure and function can improve prediction tool performance, particularly for patients with initially moderate to severe motor impairment. Being able to make accurate predictions for individual patients supports rehabilitation planning and communication with patients and families.

The test-retest reliability of non-navigated transcranial magnetic stimulation (TMS) measures of corticospinal pathway excitability early after stroke

PURPOSE

Motor evoked potential (MEP) characteristics are potential biomarkers of whether rehabilitation interventions drive motor recovery after stroke. The test-retest reliability of Transcranial Magnetic Stimulation (TMS) measurements in sub-acute stroke remains unclear. This study aims to determine the test-retest reliability of upper limb MEP measures elicited by non-neuronavigated transcranial magnetic stimulation in sub-acute-stroke.

METHODS

In two identical data collection sessions, 1-3 days apart, TMS measures assessed: motor threshold (MT), amplitude, latency (MEP-L), silent period (SP), recruitment curve slope in the biceps brachii (BB), extensor carpi radialis (ECR), and abductor pollicis brevis (APB) muscles of paretic and non-paretic upper limbs. Test-retest reliability was calculated using the intra-class correlation coefficient (ICC) and 95% confidence intervals (CI). Acceptable reliability was set at a lower 95% CI of 0.70 or above. The limits of agreement (LOA) and smallest detectable change (SDC) were calculated.

RESULTS

30 participants with sub-acute stroke were included (av 36 days post stroke) reliability was variable between poor to good for the different MEP characteristics. The SDC values differed across muscles and MEP characteristics in both paretic and less paretic limbs.

CONCLUSIONS

The present findings indicate there is limited evidence for acceptable test-retest reliability of non-navigated TMS outcomes when using the appropriate 95% CI for ICC, SDC and LOA values.

CLINICAL TRIAL REGISTRATION

Current Controlled Trials: ISCRT 19090862, http://www.controlled-trials.com.

Do lower limb motor-evoked potentials predict walking outcomes post-stroke?

BACKGROUND

This observational study examined whether lower limb (LL) motor-evoked potentials (MEPs) 1 week post-stroke predict recovery of independent walking, use of ankle-foot orthosis (AFO) or walking aid, at 3 and 6 months post-stroke.

METHODS

Non-ambulatory participants were recruited 5 days post-stroke. Transcranial magnetic stimulation was used to determine tibialis anterior MEP status and clinical assessments (age, National Institutes of Health Stroke Scale (NIHSS), ankle dorsiflexion strength, LL motricity index, Berg Balance Test) were completed 1 week post-stroke. Functional Ambulation Category (FAC), use of AFO and walking aid were assessed 3 months and 6 months post-stroke. MEP status, alone and combined with clinical measures, and walking outcomes at 3 and 6 months were analysed with Pearson χ2 and multivariate binary logistic regression.

RESULTS

Ninety participants were included (median age 72 years (38-97 years)). Most participants (81%) walked independently (FAC ≥ 4), 17% used an AFO, and 49% used a walking aid 3 months post-stroke with similar findings at 6 months. Independent walking was better predicted by age, LL strength and Berg Balance Test (accuracy 92%, 95% CI 85% to 97%) than MEP status (accuracy 73%, 95% CI 63% to 83%). AFO use was better predicted by NIHSS and MEP status (accuracy 88%, 95% CI 79% to 94%) than MEP status alone (accuracy 76%, 95% CI 65% to 84%). No variables predicted use of walking aids.

CONCLUSIONS

The presence of LL MEPs 1-week post-stroke predicts independent walking at 3 and 6 months post-stroke. However, the absence of MEPs does not preclude independent walking. Clinical factors, particularly age, balance and stroke severity, more strongly predict independent walking than MEP status. LL MEP status adds little value as a biomarker for walking outcomes.

A prospective reappraisal of motor outcome prediction in patients with acute stroke by using atlas-based diffusion tensor imaging biomarkers

BACKGROUND

Diffusion tensor imaging (DTI) biomarkers can be used to quantify microstructural changes in the cerebral white matter (WM) following injury.

OBJECTIVES

This prospective single-center study aimed to evaluate whether atlas-based DTI-derived metrics obtained within 1 week after stroke can predict the motor outcome at 3 months.

METHODS

Forty patients with small acute stroke (2-7 days after onset) involving the corticospinal tract were included. Each patient underwent magnetic resonance imaging (MRI) within 1 week and at 3 months after stroke, and the changes based on DTI-derived metrics were compared by performing WM tract atlas-based quantitative analysis.

RESULTS

A total of 40 patients were included, with median age 63.5 years and a majority of males (72.5%). Patients were classified into good-prognosis group (mRS 0-2, n = 27) and poor-prognosis group (mRS 3-5, n = 13) by outcome. The median (25th-75th percentile) of MD (0.7 (0.6-0.7) vs. 0.7 (0.7-0.8); p = 0.049) and AD (0.6 (0.5, 0.7) vs. 0.7 (0.6, 0.8); p = 0.023) ratios within 1 week were significantly lower in the poor-prognosis group compared to the good-prognosis group. The ROC curve of the combined DTI-derived metrics model showed comparable Youden index (65.5% vs. 58.4%-65.4%) and higher specificity (96.3% vs. 69.2%-88.5%) compared to clinical indexes. The area under the ROC curve of the combined DTI-derived metrics model is comparable to those of the clinical indexes (all p > 0.1) and higher than those of the individual DTI-derived metrics parameters.

CONCLUSIONS

Atlas-based DTI-derived metrics at acute stage provide objective information for prognosis prediction of patients with ischemic or lacunar stroke.

Compensatory increase in ipsilesional supplementary motor area and premotor connectivity is associated with greater gait impairments: a personalized fMRI analysis in chronic stroke

Background

Balance and mobility impairments are prevalent post-stroke and a large number of survivors require walking assistance at 6 months post-stroke which diminishes their overall quality of life. Personalized interventions for gait and balance rehabilitation are crucial. Recent evidence indicates that stroke lesions in primary motor pathways, such as corticoreticular pathways (CRP) and corticospinal tract (CST), may lead to reliance on alternate motor pathways as compensation, but the current evidence lacks comprehensive knowledge about the underlying neural mechanisms.

Methods

In this study, we investigate the functional connectivity (FC) changes within the motor network derived from an individualized cortical parcellation approach in 33 participants with chronic stroke compared to 17 healthy controls. The correlations between altered motor FC and gait deficits (i.e., walking speed and walking balance) were then estimated in the stroke population to understand the compensation mechanism of the motor network in motor function rehabilitation post-stroke.

Results

Our results demonstrated significant FC increases between ipsilesional medial supplementary motor area (SMA) and premotor in stroke compared to healthy controls. Furthermore, we also revealed a negative correlation between ipsilesional SMA-premotor FC and self-selected walking speed, as well as the Functional Gait Assessment (FGA) scores.

Conclusion

The increased FC between the ipsilesional SMA and premotor regions could be a compensatory mechanism within the motor network following a stroke when the individual can presumably no longer rely on the more precise CST modulation of movements to produce a healthy walking pattern. These findings enhance our understanding of individualized motor network FC changes and their connection to gait and walking balance impairments post-stroke, improving stroke rehabilitation interventions.

Genome-Wide Association Studies of 3 Distinct Recovery Phenotypes in Mild Ischemic Stroke

BACKGROUND AND OBJECTIVES

Stroke genetic research has made substantial progress in the past decade. Its recovery application, however, remains behind, in part due to its reliance on the modified Rankin Scale (mRS) score as a measure of poststroke outcome. The mRS does not map well to biological processes because numerous psychosocial factors drive much of what the mRS captures. Second, the mRS contains multiple disparate biological events into a single measure further limiting its use for biological discovery. This led us to investigate the effect of distinct stroke recovery phenotypes on genetic variation associations with Genome-Wide Association Studies (GWASs) by repurposing the NIH Stroke Scale (NIHSS) and its subscores.

METHODS

In the Vitamin Intervention for Stroke Prevention cohort, we estimated changes in cognition, motor, and global impairments over 2 years using specific measures. We included genotyped participants with a total NIHSS score greater than zero at randomization and excluded those with recurrent stroke during the trial. A GWAS linear mixed-effects model predicted score changes, with participant as a random effect, and included initial score, age, sex, treatment group, and the first 5 ancestry principal components.

RESULTS

In total, 1,270 participants (64% male) were included with a median NIHSS score of 2 (interquartile range [IQR] 1-3) and median age 68 (IQR 59-75) years. At randomization, 20% had cognitive deficits (NIHSS Cog-4 score >0) and 70% had ≥1 motor deficits (impairment score >1). At 2 years, these percentages improved to 7.2% with cognitive deficits and 30% with motor deficits. GWAS identified novel suggestive gene-impairment associations (p < 5e-6) for cognition (CAMK2D, EVX2, LINC0143, PTPRM, SGMS1, and SMAD2), motor (ACBD6, KDM4B, MARK4, PTPRS, ROBO1, and ROBO2), and global (MSR1 and ROBO2) impairments.

DISCUSSION

Defining domain-specific stroke recovery phenotypes and using longitudinal clinical trial designs can help detect novel genes associated with chronic recovery. These data support the use of granular endpoints to identify genetic associations related to stroke recovery.

Spontaneous Behavioural Recovery Following Stroke Relates to the Integrity of Parietal and Temporal Regions

Stroke is a devastating disease that results in neurological deficits and represents a leading cause of death and disability worldwide. Following a stroke, there is a degree of spontaneous recovery of function, the neural basis of which is of great interest among clinicians in their efforts to reduce disability following stroke and enhance rehabilitation. Conventionally, work on spontaneous recovery has tended to focus on the neural reorganization of motor cortical regions, with comparably little attention being paid to changes in non-motor regions and how these relate to recovery. Here we show, using structural neuroimaging in a macaque stroke model (N = 31) and by exploiting individual differences in spontaneous behavioural recovery, that the preservation of regions in the parietal and temporal cortices predict animal recovery. To characterize recovery, we performed a clustering analysis using Non-Human Primate Stroke Scale (NHPSS) scores and identified a good versus poor recovery group. By comparing the preservation of brain volumes in the two groups, we found that brain areas in integrity of brain areas in parietal, temporal and somatosensory cortex were associated with better recovery. In addition, a decoding approach performed across all subjects revealed that the preservation of specific brain regions in the parietal, somatosensory and medial frontal cortex predicted recovery. Together, these findings highlight the importance of parietal and temporal regions in spontaneous behavioural recovery.

2023 Sylvia Docker lecture: Ignite your passion, and connect, to make a difference

Together, we grow our profession of occupational therapy as we engage in understanding and addressing the issues that challenge the people we work with. In this Sylvia Docker Lecture, I will share the collective journeys of myself and other occupational therapists and health professionals who have undertaken (or are currently undertaking) their PhDs and are actively involved in research, to address these challenges. Together, we will explore three themes: understanding the WHY that ignites one's passion; living the journey-the EXPERIENCE; and making a difference-the IMPACT. Stories will be told through the lived experience of those engaged in research as currently enrolled PhD students, emerging researchers, and experienced researchers. These stories will capture the lived experience across individuals, and at different times in the research journey. Stories are summarised and captured using natural language processing. Topics are identified, concept maps visualised, and outputs interpreted in context of related theoretical models. Key topics identified include: the clinical and personal motivators that have ignited the passion in individuals; the value of connecting with others and growing networks; and how one's research has made a difference. The impact of discoveries and outcomes are highlighted, together with the importance of people and networks. Analysis of connections and synthesis over time revealed frequent and strong connections across themes, concepts and topics; with synthesising concepts of passion, networks, knowledge translation, opportunities, supervision and communication emerging and being shaped over time. These collective journeys provide inspiration and pathways to creative careers that have future potential in the growth of the profession of occupational therapy. It is recommended that each occupational therapist take the time to reflect on the 'why' that ignites your passion, your journey and how you can make a difference!

Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients

BACKGROUND

Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanisms depend on the time after stroke is yet to be assessed.

AIM

We investigated the response to an intensive protocol of robot-assisted rehabilitation in sub-acute and chronic stroke patients, by analyzing the underlying changes in clinical scores, electroencephalography (EEG) and end-effector kinematics. We aimed at identifying neural correlates of the participants' upper limb motor function recovery, following an intensive 2-week rehabilitation protocol.

DESIGN

Prospective cohort study.

SETTING

Inpatients and outpatients from the Neurorehabilitation Unit of Pisa University Hospital, Italy.

POPULATION

Sub-acute and chronic stroke survivors.

METHODS

Thirty-one stroke survivors (14 sub-acute, 17 chronic) with mild-to-moderate UL paresis were enrolled. All participants underwent ten rehabilitative sessions of task-oriented exercises with a planar end-effector robotic device. All patients were evaluated with the Fugl-Meyer Assessment Scale and the Wolf Motor Function Test, at recruitment (T0), end-of-treatment (T1), and one-month follow-up (T2). Along with clinical scales, kinematic parameters and quantitative EEG were collected for each patient. Kinematics metrics were related to velocity, acceleration and smoothness of the movement. Relative power in four frequency bands was extracted from the EEG signals. The evolution over time of kinematic and EEG features was analyzed, in correlation with motor recovery.

RESULTS

Both groups displayed significant gains in motility after treatment. Sub-acute patients displayed more pronounced clinical improvements, significant changes in kinematic parameters, and a larger increase in Beta-band in the motor area of the affected hemisphere. In both groups these improvements were associated to a decrease in the Delta-band of both hemispheres. Improvements were retained at T2.

CONCLUSIONS

The intensive two-week rehabilitation protocol was effective in both chronic and sub-acute patients, and improvements in the two groups shared similar dynamics. However, stronger cortical and behavioral changes were observed in sub-acute patients suggesting different reorganizational patterns.

CLINICAL REHABILITATION IMPACT

This study paves the way to personalized approaches to UL motor rehabilitation after stroke, as highlighted by different neurophysiological modifications following recovery in subacute and chronic stroke patients.

A translational roadmap for transcranial magnetic and direct current stimulation in stroke rehabilitation: Consensus-based core recommendations from the third stroke recovery and rehabilitation roundtable

BACKGROUND AND AIMS

The purpose of this Third Stroke Recovery and Rehabilitation Roundtable (SRRR3) was to develop consensus recommendations to address outstanding barriers for the translation of preclinical and clinical research using the non-invasive brain stimulation (NIBS) techniques Transcranial Magnetic Stimulation (TMS) and Transcranial Direct Current Stimulation (tDCS) and provide a roadmap for the integration of these techniques into clinical practice.

METHODS

International NIBS and stroke recovery experts (N = 18) contributed to the consensus process. Using a nominal group technique, recommendations were reached via a five-stage process, involving a thematic survey, two priority ranking surveys, a literature review and an in-person meeting.

RESULTS AND CONCLUSIONS

Results of our consensus process yielded five key evidence-based and feasibility barriers for the translation of preclinical and clinical NIBS research, which were formulated into five core consensus recommendations. Recommendations highlight an urgent need for (1) increased understanding of NIBS mechanisms, (2) improved methodological rigor in both preclinical and clinical NIBS studies, (3) standardization of outcome measures, (4) increased clinical relevance in preclinical animal models, and (5) greater optimization and individualization of NIBS protocols. To facilitate the implementation of these recommendations, the expert panel developed a new SRRR3 Unified NIBS Research Checklist. These recommendations represent a translational pathway for the use of NIBS in stroke rehabilitation research and practice.

Prevalence of Arm Weakness, Pre-Stroke Outcomes and Other Post-Stroke Impairments Using Routinely Collected Clinical Data on an Acute Stroke Unit

INTRODUCTION

The prevalence of upper limb motor weakness early post-stroke may be changing, which can have clinical and research implications. Our primary aim was to describe the prevalence of upper limb motor weakness early post-stroke, with a secondary aim to contextualize this prevalence by describing pre-stroke outcomes, other post-stroke impairments, functional activities, and discharge destination.

METHODS

This cross-sectional observational study extracted clinical data from confirmed stroke patients admitted to a metropolitan stroke unit over 15-months. The primary upper limb weakness measure was Shoulder Abduction and Finger Extension (SAFE) score. Demographics (eg, age), clinical characteristics (eg, stroke severity), pre-stroke outcomes (eg, clinical frailty), other post-stroke impairments (eg, command following), functional activities (eg, ambulation), and discharge destination were also extracted.

RESULTS

A total of 463 participants had a confirmed stroke and SAFE score. One-third of patients received ≥1 acute medical intervention(s). Nearly one-quarter of patients were classified as frail pre-stroke. Upper limb weakness (SAFE≤8) was present in 35% [95% CI: 30%-39%] at a median of 1-day post-stroke, with 22% presenting with mild-moderate weakness (SAFE5-8). The most common other impairments were upper limb coordination (46%), delayed recall (41%), and upper limb sensation (26%). After a median 3-day acute stroke stay, 52% of the sample were discharged home.

CONCLUSION

Upper limb weakness was present in just over a third (35%) of the sample early post-stroke. Data on pre-stroke outcomes and the prevalence of other post-stroke impairments highlights the complexity and heterogeneity of stroke recovery. Further research is required to tease out meaningful recovery phenotypes and their implications.

Measuring Neuroplasticity in Response to Cardiovascular Exercise in People With Stroke: A Critical Perspective

BACKGROUND

Rehabilitative treatments that promote neuroplasticity are believed to improve recovery after stroke. Animal studies have shown that cardiovascular exercise (CE) promotes neuroplasticity but the effects of this intervention on the human brain and its implications for the functional recovery of patients remain unclear. The use of biomarkers has enabled the assessment of cellular and molecular events that occur in the central nervous system after brain injury. Some of these biomarkers have proven to be particularly valuable for the diagnosis of severity, prognosis of recovery, as well as for measuring the neuroplastic response to different treatments after stroke.

OBJECTIVES

To provide a critical analysis on the current evidence supporting the use of neurophysiological, neuroimaging, and blood biomarkers to assess the neuroplastic response to CE in individuals poststroke.

RESULTS

Most biomarkers used are responsive to the effects of acute and chronic CE interventions, but the response appears to be variable and is not consistently associated with functional improvements. Small sample sizes, methodological variability, incomplete information regarding patient's characteristics, inadequate standardization of training parameters, and lack of reporting of associations with functional outcomes preclude the quantification of the neuroplastic effects of CE poststroke using biomarkers.

CONCLUSION

Consensus on the optimal biomarkers to monitor the neuroplastic response to CE is currently lacking. By addressing critical methodological issues, future studies could advance our understanding of the use of biomarkers to measure the impact of CE on neuroplasticity and functional recovery in patients with stroke.

The volume and the distribution of premorbid white matter hyperintensities: Impact on post-stroke aphasia

White matter hyperintensities (WMH) are a radiological manifestation of progressive white matter integrity loss. The total volume and distribution of WMH within the corpus callosum have been associated with pathological cognitive ageing processes but have not been considered in relation to post-stroke aphasia outcomes. We investigated the contribution of both the total volume of WMH, and the extent of WMH lesion load in the corpus callosum to the recovery of language after first-ever stroke. Behavioural and neuroimaging data from individuals (N = 37) with a left-hemisphere stroke were included at the early subacute stage of recovery. Spoken language comprehension and production abilities were assessed using word and sentence-level tasks. Neuroimaging data was used to derive stroke lesion variables (volume and lesion load to language critical regions) and WMH variables (WMH volume and lesion load to three callosal segments). WMH volume did not predict variance in language measures, when considered together with stroke lesion and demographic variables. However, WMH lesion load in the forceps minor segment of the corpus callosum explained variance in early subacute comprehension abilities (t = -2.59, p = .01) together with corrected stroke lesion volume and socio-demographic variables. Premorbid WMH lesions in the forceps minor were negatively associated with early subacute language comprehension after aphasic stroke. This negative impact of callosal WMH on language is consistent with converging evidence from pathological ageing suggesting that callosal WMH disrupt the neural networks supporting a range of cognitive functions.

A translational roadmap for transcranial magnetic and direct current stimulation in stroke rehabilitation: Consensus-based core recommendations from the third stroke recovery and rehabilitation roundtable

BACKGROUND AND AIMS

The purpose of this Third Stroke Recovery and Rehabilitation Roundtable (SRRR3) was to develop consensus recommendations to address outstanding barriers for the translation of preclinical and clinical research using the non-invasive brain stimulation (NIBS) techniques Transcranial Magnetic Stimulation (TMS) and Transcranial Direct Current Stimulation (tDCS) and provide a roadmap for the integration of these techniques into clinical practice.

METHODS

International NIBS and stroke recovery experts (N = 18) contributed to the consensus process. Using a nominal group technique, recommendations were reached via a five-stage process, involving a thematic survey, two priority ranking surveys, a literature review and an in-person meeting.

RESULTS AND CONCLUSIONS

Results of our consensus process yielded five key evidence-based and feasibility barriers for the translation of preclinical and clinical NIBS research, which were formulated into five core consensus recommendations. Recommendations highlight an urgent need for (1) increased understanding of NIBS mechanisms, (2) improved methodological rigor in both preclinical and clinical NIBS studies, (3) standardization of outcome measures, (4) increased clinical relevance in preclinical animal models, and (5) greater optimization and individualization of NIBS protocols. To facilitate the implementation of these recommendations, the expert panel developed a new SRRR3 Unified NIBS Research Checklist. These recommendations represent a translational pathway for the use of NIBS in stroke rehabilitation research and practice.

The Evolution of Hand Proprioceptive and Motor Impairments in the Sub-Acute Phase After Stroke

BACKGROUND

Hand proprioception is essential for fine movements and therefore many activities of daily living. Although frequently impaired after stroke, it is unclear how hand proprioception evolves in the sub-acute phase and whether it follows a similar pattern of changes as motor impairments.

OBJECTIVE

This work investigates whether there is a corresponding pattern of changes over time in hand proprioception and motor function as comprehensively quantified by a combination of robotic, clinical, and neurophysiological assessments.

METHODS

Finger proprioception (position sense) and motor function (force, velocity, range of motion) were evaluated using robotic assessments at baseline (<3 months after stroke) and up to 4 weeks later (discharge). Clinical assessments (among others, Box & Block Test [BBT]) as well as Somatosensory/Motor Evoked Potentials (SSEP/MEP) were additionally performed.

RESULTS

Complete datasets from 45 participants post-stroke were obtained. For 42% of all study participants proprioception and motor function had a dissociated pattern of changes (only 1 function considerably improved). This dissociation was either due to the absence of a measurable impairment in 1 modality at baseline, or due to a severe lesion of central somatosensory or motor tracts (absent SSEP/MEP). Better baseline BBT correlated with proprioceptive gains, while proprioceptive impairment at baseline did not correlate with change in BBT.

CONCLUSIONS

Proprioception and motor function frequently followed a dissociated pattern of changes in sub-acute stroke. This highlights the importance of monitoring both functions, which could help to further personalize therapies.

Applications of Repetitive Transcranial Magnetic Stimulation to Improve Upper Limb Motor Performance After Stroke: A Systematic Review

BACKGROUND

Noninvasive brain stimulation (NIBS) is a promising technique for improving upper limb motor performance post-stroke. Its application has been guided by the interhemispheric competition model and typically involves suppression of contralesional motor cortex. However, the bimodal balance recovery model prompts a more tailored application of NIBS based on ipsilesional corticomotor function.

OBJECTIVE

To review and assess the application of repetitive transcranial magnetic stimulation (rTMS) protocols that aimed to improve upper limb motor performance after stroke.

METHODS

A PubMed search was conducted for studies published between 1st January 2005 and 1st November 2022 using rTMS to improve upper limb motor performance of human adults after stroke. Studies were grouped according to whether facilitatory or suppressive rTMS was applied to the contralesional hemisphere.

RESULTS

Of the 492 studies identified, 70 were included in this review. Only 2 studies did not conform to the interhemispheric competition model, and facilitated the contralesional hemisphere. Only 21 out of 70 (30%) studies reported motor evoked potential (MEP) status as a biomarker of ipsilesional corticomotor function. Around half of the studies (37/70, 53%) checked whether rTMS had the expected effect by measuring corticomotor excitability (CME) after application.

CONCLUSION

The interhemispheric competition model dominates the application of rTMS post-stroke. The majority of recent and current studies do not consider bimodal balance recovery model for the application of rTMS. Evaluating CME after the application rTMS could confirm that the intervention had the intended neurophysiological effect. Future studies could select patients and apply rTMS protocols based on ipsilesional MEP status.

Neuromodulation for Post-Stroke Motor Recovery: a Narrative Review of Invasive and Non‑Invasive Tools

PURPOSE OF REVIEW

Stroke remains a leading disabling condition, and many survivors have permanent disability despite acute stroke treatment and subsequent standard-of-care rehabilitation therapies. Adjunctive neuromodulation is an emerging frontier in the field of stroke recovery. In this narrative review, we aim to highlight and summarize various neuromodulation techniques currently being investigated to enhance recovery and reduce impairment in patients with stroke.

RECENT FINDINGS

For motor recovery, repetitive transcranial magnetic simulation (rTMS) and direct current stimulation (tDCS) have shown promising results in many smaller-scale trials. Still, their efficacy has yet to be proven in large-scale pivotal trials. A promising large-scale study investigating higher dose tDCS combined with constraint movement therapy to enhance motor recovery is currently underway. MRI-guided tDCS studies in subacute and chronic post-stroke aphasia showed promising benefits for picture-naming recovery. rTMS, particularly inhibitory stimulation over the contralesional homolog, could represent a pathway forward in post-stroke motor recovery in the setting of a well-designed and adequately powered clinical trial. Recently evidenced-based guideline actually supported Level A (definite efficacy) for the use of low-frequency rTMS of the primary motor cortex for hand motor recovery in the post-acute stage of stroke based on the meta-analysis result. Adjunctive vagal nerve stimulation has recently received FDA approval to enhance upper limb motor recovery in chronic ischemic stroke with moderate impairment, and progress has been made to implement it in real-world practice. Despite a few small and large-scale studies in epidural stimulation (EDS), further research on the utilization of EDS in post-stroke recovery is needed. Deep brain stimulation or stent-based neuromodulation has yet to be further tested regarding safety and efficacy. Adjunctive neuromodulation to rehabilitation therapy is a promising avenue for promoting post-stroke recovery and decreasing the overall burden of disability. The pipeline for neuromodulation technology remains strong as they span from the preclinical stage to the post-market stage. We are optimistic to see that more neuromodulation tools will be available to stroke survivors in the not-to-distant future.

Physical functioning factors predicting a return home after stroke rehabilitation: A systematic review and meta-analysis

OBJECTIVES

This systematic review and meta-analysis sought to identify the physical functioning factors associated with home discharge after inpatient stroke rehabilitation.

DATA SOURCES

A search of PubMed, Embase, CINHAL, The Cochrane Library (Trials), Web of Science, and PEDro were conducted up until May 2023.

METHODS

Two independent reviewers selected studies for population (patients with stroke), predictive factors (physical functioning), outcome (discharge destination), setting (inpatient rehabilitation), and study designs (observational and experimental studies). Predictive factors were identified among assessments of the "body function" and "activity" components of the International Classification of Functioning. Methodological quality was assessed with the Newcastle-Ottawa Scale. The findings used quantitative and narrative syntheses. Meta-analyses were performed with the inverse variance method and the random-effects model using included studies with sufficient data.

RESULTS

Forty-five studies were included with 204,787 participants. Included studies assessed the association of independence in activities of daily living, walking, rolling, transferring, and balance on admission with a probability of returning home. Motor (odds ratio = 1.23, 95% confidence interval: 1.12-1.35, p < .001) and total (odds ratio = 1.34, 95% confidence interval: 1.14-1.57, p < .001) Functional Independence Measure scores on admission were significantly associated with home discharge in meta-analyses. Additionally, included studies showed that independence in motor activities, such as sitting, transferring, and walking, and scores above thresholds for the Functional Independence Measure and Berg Balance Scale on admission were associated with discharge destination.

CONCLUSION

This review showed that higher independence in activities of daily living on admission is associated with home discharge after inpatient stroke rehabilitation.

IC3 protocol: a longitudinal observational study of cognition after stroke using novel digital health technology

INTRODUCTION

Stroke is a major cause of death and disability worldwide, frequently resulting in persistent cognitive deficits among survivors. These deficits negatively impact recovery and therapy engagement, and their treatment is consistently rated as high priority by stakeholders and clinicians. Although clinical guidelines endorse cognitive screening for poststroke management, there is currently no gold-standard approach for identifying cognitive deficits after stroke, and clinical stroke services lack the capacity for long-term cognitive monitoring and care. Currently, available assessment tools are either not stroke-specific, not in-depth or lack scalability, leading to heterogeneity in patient assessments.

METHODS AND ANALYSIS

To address these challenges, a cost-effective, scalable and comprehensive screening tool is needed to provide a stroke-specific assessment of cognition. The current study presents such a novel digital tool, the Imperial Comprehensive Cognitive Assessment in Cerebrovascular Disease (IC3), designed to detect both domain-general and domain-specific cognitive deficits in patients after stroke with minimal input from a health professional. To ensure its reliability, we will use multiple validation approaches, and aim to recruit a large normative sample of age-matched, gender-matched and education-matched UK-based controls. Moreover, the IC3 assessment will be integrated within a larger prospective observational longitudinal clinical trial, where poststroke cognition will be examined in tandem with brain imaging and blood biomarkers to identify novel multimodal biomarkers of recovery after stroke. This study will enable deeper cognitive phenotyping of patients at a large scale, while identifying those with highest risk of progressive cognitive decline, as well as those with greatest potential for recovery.

ETHICS AND DISSEMINATION

This study has been approved by South West-Frenchay Research Ethics Committee (IRAS 299333) and authorised by the UK's Health Research Authority. Results from the study will be disseminated at conferences and within peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT05885295. Stage: Pre-results.

Lesion-specific cortical activation following sensory stimulation in patients with subacute stroke

BACKGROUND

Sensory stimulation can play a fundamental role in the activation of the primary sensorimotor cortex (S1-M1), which can promote motor learning and M1 plasticity in stroke patients. However, studies have focused mainly on investigating the influence of brain lesion profiles on the activation patterns of S1-M1 during motor tasks instead of sensory tasks. Therefore, the objective of this study is to explore the lesion-specific activation patterns due to different brain lesion profiles and types during focal vibration (FV).

METHODS

In total 52 subacute stroke patients were recruited in this clinical experiment, including patients with basal ganglia hemorrhage/ischemia, brainstem ischemia, other subcortical ischemia, cortical ischemia, and mixed cortical-subcortical ischemia. Electroencephalograms (EEG) were recorded following a resting state lasting for 4 min and three sessions of FV. FV was applied over the muscle belly of the affected limb's biceps for 3 min each session. Beta motor-related EEG power desynchronization overlying S1-M1 was used to indicate the activation of S1-M1, while the laterality coefficient (LC) of the activation of S1-M1 was used to assess the interhemispheric asymmetry of brain activation.

RESULTS

(1) Regarding brain lesion profiles, FV could lead to the significant activation of bilateral S1-M1 in patients with basal ganglia ischemia and other subcortical ischemia. The activation of ipsilesional S1-M1 in patients with brainstem ischemia was higher than that in patients with cortical ischemia. No activation of S1-M1 was observed in patients with lesions involving cortical regions. (2) Regarding brain lesion types, FV could induce the activation of bilateral S1-M1 in patients with basal ganglia hemorrhage, which was significantly higher than that in patients with basal ganglia ischemia. Additionally, LC showed no significant correlation with the modified Barthel index (MBI) in all patients, but a positive correlation with MBI in patients with basal ganglia lesions.

CONCLUSIONS

These results reveal that sensory stimulation can induce lesion-specific activation patterns of S1-M1. This indicates FV could be applied in a personalized manner based on the lesion-specific activation of S1-M1 in stroke patients with different lesion profiles and types. Our study may contribute to a better understanding of the underlying mechanisms of cortical reorganization.

Perceptions of stroke survivors regarding factors affecting adoption of technology and exergames for rehabilitation

BACKGROUND

Task-specific motor training and repetitive practice are essential components of clinical rehabilitation. Emerging evidence suggests that incorporating gaming interfaces (also referred to as "exergames"), including virtual reality and augmented reality (VR/AR)-based interfaces for motor training, can enhance the engagement and efficacy of poststroke rehabilitation.

OBJECTIVE

To investigate perceptions of individuals with stroke regarding technology and exergames for rehabilitation.

DESIGN

This qualitative phenomenological study included a convenience sample of 11 individuals with stroke (61.7 ± 12.4 years, 6 women and 5 men, 63.5 ± 41.2 months post stroke).

SETTING

Community.

INTERVENTIONS

N/A.

OUTCOME MEASURES

Semistructured open-ended focus-group interviews to understand their perceptions on technology and exergames to improve recovery were coded using thematic content analysis.

RESULTS

Individuals with stroke were comfortable using smartphones, computers, and rehabilitation technologies but had limited experiences using exergames and VR/AR devices. Individuals with stroke were motivated to use technologies and exergames to improve their functional recovery. Participants identified facilitators (eg, enhancing functional recovery, feedback, therapist supervision) and barriers (eg, safety, inaccessibility, inadequate knowledge) to adopting exergames in their daily lives. Participants wanted the exergames to be customizable, goal oriented, and enjoyable to maintain their engagement. They were willing to use exergames to improve their functional recovery but indicated that these games could not replace the therapist's supervision.

CONCLUSIONS

Despite having limited experiences with exergames, people post stroke perceived that exergames could promote functional recovery. The perspectives gained from the present study can inform user-centered game design for neurorehabilitation.

White matter hyperintensities modify relationships between corticospinal tract damage and motor outcomes after stroke

Motor outcomes after stroke relate to corticospinal tract (CST) damage. Concurrent damage from white matter hyperintensities (WMHs) might impact neurological capacity for recovery after CST injury. Here, we evaluated if WMHs modulate the relationship between CST damage and post-stroke motor impairment outcome. We included 223 individuals from the ENIGMA Stroke Recovery Working Group. CST damage was indexed with weighted CST lesion load (CST-LL). Mixed effects beta-regression models were fit to test the impact of CST-LL, WMH volume, and their interaction on motor impairment. WMH volume related to motor impairment above and beyond CST-LL (β = 0.178, p = 0.022). We tested if relationships varied by WMH severity (mild vs. moderate-severe). In individuals with mild WMHs, motor impairment related to CST-LL (β = 0.888, p < 0.001) with a CST-LL x WMH interaction (β = -0.211, 0.026). In individuals with moderate-severe WMHs, motor impairment related to WMH volume (β = 0.299, p = 0.044), but did not significantly relate to CST-LL or a CST-LL x WMH interaction. WMH-related damage may be under-recognised in stroke research as a factor contributing to variability in motor outcomes. Our findings emphasize the importance of brain structural reserve in motor outcomes after brain injury.

A naturalistic study comparing the efficacy of unilateral and bilateral sequential theta burst stimulation in treating major depression - the U-B-D study protocol

BACKGROUND

Major depressive disorder (MDD) is a prevalent mental health condition affecting millions worldwide, leading to disability and reduced quality of life. MDD poses a global health priority due to its early onset and association with other disabling conditions. Available treatments for MDD exhibit varying effectiveness, and a substantial portion of individuals remain resistant to treatment. Repetitive transcranial magnetic stimulation (rTMS), applied to the left and/or right dorsolateral prefrontal cortex (DLPFC), is an alternative treatment strategy for those experiencing treatment-resistant MDD. The objective of this study is to investigate whether this newer form of rTMS, namely theta burst stimulation (TBS), when performed unilaterally or bilaterally, is efficacious in treatment-resistant MDD.

METHODS

In this naturalistic, randomized double-blinded non-inferiority trial, participants with a major depressive episode will be randomized to receive either unilateral (i.e., continuous TBS [cTBS] to the right and sham TBS to the left DLPFC) or bilateral sequential TBS (i.e., cTBS to the right and intermittent TBS [iTBS] to the left DLPFC) delivered 5 days a week for 4-6 weeks. Responders will move onto a 6-month flexible maintenance phase where TBS treatment will be delivered at a decreasing frequency depending on degree of symptom mitigation. Several clinical assessments and neuroimaging and neurophysiological biomarkers will be collected to investigate treatment response and potential associated biomarkers. A non-inferiority analysis will investigate whether bilateral sequential TBS is non-inferior to unilateral TBS and regression analyses will investigate biomarkers of treatment response. We expect to recruit a maximal of 256 participants. This trial is approved by the Research Ethics Board of The Royal's Institute of Mental Health Research (REB# 2,019,071) and will follow the Declaration of Helsinki. Findings will be published in peer-reviewed journals.

DISCUSSION

Comprehensive assessment of symptoms and neurophysiological biomarkers will contribute to understanding the differential efficacy of the tested treatment protocols, identifying biomarkers for treatment response, and shedding light into underlying mechanisms of TBS. Our findings will inform future clinical trials and aid in personalizing treatment selection and scheduling for individuals with MDD.

TRIAL REGISTRATION

The trial is registered on https://clinicaltrials.gov/ct2/home (#NCT04142996).

Ethical Considerations in Neuroprognostication Following Acute Brain Injury

Neuroprognostication following acute brain injury (ABI) is a complex process that involves integrating vast amounts of information to predict a patient's likely trajectory of neurologic recovery. In this setting, critically evaluating salient ethical questions is imperative, and the implications often inform high-stakes conversations about the continuation, limitation, or withdrawal of life-sustaining therapy. While neuroprognostication is central to these clinical "life-or-death" decisions, the ethical underpinnings of neuroprognostication itself have been underexplored for patients with ABI. In this article, we discuss the ethical challenges of individualized neuroprognostication including parsing and communicating its inherent uncertainty to surrogate decision-makers. We also explore the population-based ethical considerations that arise in the context of heterogenous prognostication practices. Finally, we examine the emergence of artificial intelligence-aided neuroprognostication, proposing an ethical framework relevant to both modern and longstanding prognostic tools.

Interhemispheric Structural Connectivity Underlies Motor Recovery after Stroke

OBJECTIVE

Although ample evidence highlights that the ipsilesional corticospinal tract (CST) plays a crucial role in motor recovery after stroke, studies on cortico-cortical motor connections remain scarce and provide inconclusive results. Given their unique potential to serve as structural reserve enabling motor network reorganization, the question arises whether cortico-cortical connections may facilitate motor control depending on CST damage.

METHODS

Diffusion spectrum imaging (DSI) and a novel compartment-wise analysis approach were used to quantify structural connectivity between bilateral cortical core motor regions in chronic stroke patients. Basal and complex motor control were differentially assessed.

RESULTS

Both basal and complex motor performance were correlated with structural connectivity between bilateral premotor areas and ipsilesional primary motor cortex (M1) as well as interhemispheric M1 to M1 connectivity. Whereas complex motor skills depended on CST integrity, a strong association between M1 to M1 connectivity and basal motor control was observed independent of CST integrity especially in patients who underwent substantial motor recovery. Harnessing the informational wealth of cortico-cortical connectivity facilitated the explanation of both basal and complex motor control.

INTERPRETATION

We demonstrate for the first time that distinct aspects of cortical structural reserve enable basal and complex motor control after stroke. In particular, recovery of basal motor control may be supported via an alternative route through contralesional M1 and non-crossing fibers of the contralesional CST. Our findings help to explain previous conflicting interpretations regarding the functional role of the contralesional M1 and highlight the potential of cortico-cortical structural connectivity as a future biomarker for motor recovery post-stroke. ANN NEUROL 2023;94:785-797.

Functional MRI evaluation of hyperbaric oxygen therapy effect on hand motor recovery in a chronic post-stroke patient: a case report and physiological discussion

Introduction

Impairments in activities of daily living (ADL) are a major concern in post-stroke rehabilitation. Upper-limb motor impairments, specifically, have been correlated with low quality of life. In the current case report, we used both task-based and resting state functional MRI (fMRI) tools to investigate the neural response mechanisms and functional reorganization underlying hyperbaric oxygen therapy (HBOT)-induced motor rehabilitation in a chronic post-stroke patient suffering from severe upper-limb motor impairment.

Methods

We studied motor task fMRI activation and resting-state functional connectivity (rsFC) in a 61-year-old right-handed male patient who suffered hemiparesis and physical weakness in the right upper limb, 2 years after his acute insult, pre- and post-treatment of 60 daily HBOT sessions. Motor functions were assessed at baseline and at the end of the treatment using the Fugl-Meyer assessment (FMA) and the handgrip maximum voluntary contraction (MVC).

Results

Following HBOT, the FMA score improved from 17 (severe impairment) to 31 (moderate impairment). Following the intervention during trials involving the affected hand, there was an observed increase in fMRI activation in both the supplementary motor cortex (SMA) and the premotor cortex (PMA) bilaterally. The lateralization index (LI) decreased from 1 to 0.63, demonstrating the recruitment of the contralesional hemisphere. The region of interest, ROI-to-ROI, analysis revealed increased post-intervention inter-hemispheric connectivity (P = 0.002) and a between-network connectivity increase (z-score: 0.35 ± 0.21 to 0.41 ± 0.21, P < 0.0001). Seed-to-voxel-based rsFC analysis using the right SMA as seed showed increased connectivity to the left posterior parietal cortex, the left primary somatosensory cortex, and the premotor cortex.

Conclusion

This study provides additional insights into HBOT-induced brain plasticity and functional improvement in chronic post-stroke patients.

PSIs of EEG With Refined Frequency Decomposition Could Prognose Motor Recovery Before Rehabilitation Intervention

Stroke often leads to permanent impairment in motor function. Accurate and quantitative prognosis of potential motor recovery before rehabilitation intervention can help healthcare centers improve resources organization and enable individualized intervention. The context of this paper investigated the potential of using electroencephalography (EEG) functional connectivity (FC) measures as biomarkers for assessing and prognosing improvement of Fugl-Meyer Assessment in upper extremity motor function ( ∆FMU) among participants with chronic stroke. EEG data from resting and motor imagery task were recorded from 13 participants with chronic stroke. Three functional connectivity methods, which were Pearson correlation measure (PCM), weighted Phase Lag Index (wPLI) and phase synchronization index (PSI), were investigated, under three regions of interest (inter-hemispheric, intra-hemispheric, and whole-brain), in two statues (resting and motor imagery), with 15 refined center frequencies. We applied correlation analysis to identify the optimal center frequencies and pairs of synchronized channels that were consistently associated with ∆FMU . Predictive models were generated using regression analysis algorithms based on optimized center frequencies and channel pairs identified from the proposed analysis method, with leave-one-out cross-validation. We found that PSI in the Alpha band (with center frequency of 9Hz) was the most sensitive FC measures for prognosing motor recovery. Strong and significant correlations were identified between the predictions and actual ∆FMU scores both in the resting state ( [Formula: see text], [Formula: see text], N=13) and motor imagery ( [Formula: see text], [Formula: see text], N=13). Our results suggested that EEG connectivity measured with PSI in resting state could be a promising biomarker for quantifying motor recovery before motor rehabilitation intervention.

Integrative Approaches in Acute Ischemic Stroke: From Symptom Recognition to Future Innovations

Among the high prevalence of cerebrovascular diseases nowadays, acute ischemic stroke stands out, representing a significant worldwide health issue with important socio-economic implications. Prompt diagnosis and intervention are important milestones for the management of this multifaceted pathology, making understanding the various stroke-onset symptoms crucial. A key role in acute ischemic stroke management is emphasizing the essential role of a multi-disciplinary team, therefore, increasing the efficiency of recognition and treatment. Neuroimaging and neuroradiology have evolved dramatically over the years, with multiple approaches that provide a higher understanding of the morphological aspects as well as timely recognition of cerebral artery occlusions for effective therapy planning. Regarding the treatment matter, the pharmacological approach, particularly fibrinolytic therapy, has its merits and challenges. Endovascular thrombectomy, a game-changer in stroke management, has witnessed significant advances, with technologies like stent retrievers and aspiration catheters playing pivotal roles. For select patients, combining pharmacological and endovascular strategies offers evidence-backed benefits. The aim of our comprehensive study on acute ischemic stroke is to efficiently compare the current therapies, recognize novel possibilities from the literature, and describe the state of the art in the interdisciplinary approach to acute ischemic stroke. As we aspire for holistic patient management, the emphasis is not just on medical intervention but also on physical therapy, mental health, and community engagement. The future holds promising innovations, with artificial intelligence poised to reshape stroke diagnostics and treatments. Bridging the gap between groundbreaking research and clinical practice remains a challenge, urging continuous collaboration and research.

Patterns of Visual Task-based Functional MRI Activation in Chronic Posterior Cerebral Artery Stroke Patients

PURPOSE

Stroke is a principal cause of disability worldwide. In motor stroke, the tools for stratification and prognostication are plentiful. Conversely, in stroke causing mainly visual and cognitive problems, there is still no gold standard modality to use. The purpose of this study was to explore the fMRI recruitment pattern in chronic posterior cerebral artery (PCA) stroke patients and to investigate fMRI as a biomarker of disability in these patients.

METHODS

The study included 10 chronic PCA stroke patients and another 10 age-matched volunteer controls. The clinical presentation, cognitive state, and performance in visual perceptual skills battery (TVPS-3) were determined for both patients and control groups. Task-based fMRI scans were acquired while performing a passive visual task. Individual and group analyses of the fMRI scans as well as correlation analysis with the clinical and behavioral data were done.

RESULTS

At the level of behavioral assessment there was non-selective global impairment in all visual skills subtests. On visual task-based fMRI, patients recruited more brain areas than controls. These activations were present in the ipsilesional side distributed in the ipsilesional cerebellum, dorsolateral prefrontal cortex mainly Brodmann area (BA) 9, superior parietal lobule (somatosensory associative cortex, BA 7), superior temporal gyrus (BA 22), supramarginal gyrus (BA 40), and contralesional associative visual cortex (BA 19). Spearman's rank correlation was computed to assess the relationship between the TVPS scores and the numbers of fMRI neuronal clusters in each patient above the main control activations, there was a negative correlation between the two variables, r(10) = -0.85, p ≤ 0.001.

CONCLUSION

In chronic PCA stroke patients with residual visual impairments, the brain attempts to recruit more neighboring and distant functional areas for executing the impaired visual skill. This intense recruitment pattern in poorly recovering patients appears to be a sign of failed compensation. Consequently, fMRI has the potential for clinically relevant prognostic assessment in patients surviving PCA stroke; however, as this study included no longitudinal data, this potential should be further investigated in longitudinal imaging studies, with a larger cohort, and multiple time points.

Data-driven biomarkers outperform theory-based biomarkers in predicting stroke motor outcomes

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have predicted motor outcomes based on the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to predict chronic motor outcomes after stroke and compares the accuracy of these predictions to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients (293 female/496 male) from the ENIGMA Stroke Recovery Working Group (age 64.9±18.0 years; time since stroke 12.2±0.2 months; normalised motor score 0.7±0.5 (range [0,1]). The out-of-sample prediction accuracy of two theory-based biomarkers was assessed: lesion load of the corticospinal tract, and lesion load of multiple descending motor tracts. These theory-based prediction accuracies were compared to the prediction accuracy from three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had better prediction accuracy - as measured by higher explained variance in chronic motor outcomes - than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R2 = 0.210, p < 0.001), performing significantly better than predictions using the theory-based biomarkers of lesion load of the corticospinal tract (R2 = 0.132, p< 0.001) and of multiple descending motor tracts (R2 = 0.180, p < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R2 =0.200, p < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R2 =0.167, p < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved prediction accuracy for theory-based and data-driven biomarkers. Finally, combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R2 = 0.241, p < 0.001. Overall, these results demonstrate that models that predict chronic motor outcomes using data-driven features, particularly when lesion data is represented in terms of structural disconnection, perform better than models that predict chronic motor outcomes using theory-based features from the motor system. However, combining both theory-based and data-driven models provides the best predictions.

The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

BACKGROUND

To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion.

METHODS

This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10-3 mm2/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal-Wallis test with Tukey-Kramer post-hoc tests were used for comparison. A p < .05 was considered statistically significant.

RESULTS

The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10-3 mm2/s and 0.8 × 10-3 mm2/s (p < .001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10-3 mm2/s (p = .062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10-3 mm2/s achieved the highest DSC in the segmentation of AIS lesion.

CONCLUSIONS

The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10-3 mm2/s in segmentating AIS lesion with highest DSC.

KEY POINTS

• Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10-3 mm2/s.

ICTs and interventions in telerehabilitation and their effects on stroke recovery

Telerehabilitation (TR) is a new model to provide rehabilitation services to stroke survivors. It is a promising approach to deliver mainstream interventions for movement, cognitive, speech and language, and other disorders. TR has two major components: information and communication technologies (ICTs) and stroke interventions. ICTs provide a platform on which interventions are delivered and subsequently result in stroke recovery. In this mini-review, we went over features of ICTs that facilitate TR, as well as stroke interventions that can be delivered via TR platforms. Then, we reviewed the effects of TR on various stroke disorders. In most studies, TR is a feasible and effective solution in delivering interventions to patients. It is not inferior to usual care and in-clinic therapy with matching dose and intensity. With new technologies, TR may result in better outcomes than usual care for some disorders. One the other hand, TR also have many limitations that could lead to worse outcomes than traditional rehabilitation. In the end, we discussed major concerns and possible solutions related to TR, and also discussed potential directions for TR development.

Recombination of the right cerebral cortex in patients with left side USN after stroke: fNIRS evidence from resting state

Objective

Unilateral spatial neglect (USN) is an impaired contralesional stimulus detection, response, or action, causing functional disability. After a stroke, the right hemisphere experiences USN more noticeably, severely, and persistently than the left. However, few studies using fNIRS have been reported in cases of USN. This study aimed to confirm weaker RSFC in USN and investigate the potential inherent features in hemodynamic fluctuations that may be associated with USN. Furthermore, these features were combined into a mathematical model for more accurate classification.

Methods

A total of 33 stroke patients with right-sided brain damage were chosen, of whom 12 had non-USN after stroke, and 21 had USN after stroke (the USN group). Graph theory was used to evaluate the hemodynamic signals of the brain's right cerebral cortex during rest. Furthermore, a support vector machine model was built to categorize the subjects into two groups based on the chosen network properties.

Results

First, mean functional connectivity was lower in the USN group (0.745 ± 0.239) than in the non-USN group (0.843 ± 0.254) (t = -4.300, p < 0.001). Second, compared with the non-USN group, USN patients had a larger clustering coefficient (C) (t = 3.145, p < 0.001), local efficiency (LE) (t = 3.189, p < 0.001), and smaller global efficiency (GE) (t = 3.047, p < 0.001). Notably, there were differences in characteristic path length (L) and small worldness (σ) values between the two groups at certain thresholds, mainly as higher L (t = 3.074, p < 0.001) and lower small worldness (σ) values (t = 2.998, p < 0.001) in USN patients compared with non-USN patients. Finally, the classification accuracy of the SVM model based on AUC aC (t = -2.259, p = 0.031) and AUC aLE (t = -2.063, p = 0.048) was 85%, the sensitivity was 75%, and the specificity was 89%.

Conclusion

The functional network architecture of the right cerebral cortex exhibits significant topological alterations in individuals with USN following stroke, and the sensitivity index based on the small-world property AUC may be utilized to identify these patients accurately.

Machine learning in predicting outcomes for stroke patients following rehabilitation treatment: A systematic review

OBJECTIVE

This review aimed to summarize the use of machine learning for predicting the potential benefits of stroke rehabilitation treatments, to evaluate the risk of bias of predictive models, and to provide recommendations for future models.

MATERIALS AND METHODS

This systematic review was conducted in accordance with the PRISMA statement and the CHARMS checklist. The PubMed, Embase, Cochrane Library, Scopus, and CNKI databases were searched up to April 08, 2023. The PROBAST tool was used to assess the risk of bias of the included models.

RESULTS

Ten studies within 32 models met our inclusion criteria. The optimal AUC value of the included models ranged from 0.63 to 0.91, and the optimal R2 value ranged from 0.64 to 0.91. All of the included models were rated as having a high or unclear risk of bias, and most of them were downgraded due to inappropriate data sources or analysis processes.

DISCUSSION AND CONCLUSION

There remains much room for improvement in future modeling studies, such as high-quality data sources and model analysis. Reliable predictive models should be developed to improve the efficacy of rehabilitation treatment by clinicians.

Patient's assessment and prediction of recovery after stroke: a roadmap for clinicians

BACKGROUND AND PURPOSE

In neurorehabilitation clinical practice, assessment is usually more oriented to evaluate patient's present status, than to plan interventions according to predicted outcomes. Therefore, we conducted an extensive review of current prognostic models available in the literature for recovery prediction of many functions and constructs, after stroke. We reported results in the form of a practical guide for clinicians, with the aim of promoting the culture of early clinical assessment for patient stratification, according to expected outcome. To define a roadmap for clinicians, a stepwise sequence of five actions has been developed, from collecting information of past medical history to the adoption of validated prediction tools. Furthermore, a clinically-oriented organization of available prediction tools for recovery after stroke have been proposed for motor, language, physiological and independency functions. Finally, biomarkers and online resources with prognostic value have been reviewed, to give the most updated state of the art on prediction tools after stroke.

RECOMMENDATIONS FOR CLINICAL PRACTICE

Clinical assessment should be directed both towards the objective evaluation of the present health status, and to the prediction of expected recovery. The use of specific outcome measures with predictive value is recommended to help clinicians with the definition of sound therapeutic goals.

Clinical, Neuroimaging and Robotic Measures Predict Long-Term Proprioceptive Impairments following Stroke

Proprioceptive impairments occur in ~50% of stroke survivors, with 20-40% still impaired six months post-stroke. Early identification of those likely to have persistent impairments is key to personalizing rehabilitation strategies and reducing long-term proprioceptive impairments. In this study, clinical, neuroimaging and robotic measures were used to predict proprioceptive impairments at six months post-stroke on a robotic assessment of proprioception. Clinical assessments, neuroimaging, and a robotic arm position matching (APM) task were performed for 133 stroke participants two weeks post-stroke (12.4 ± 8.4 days). The APM task was also performed six months post-stroke (191.2 ± 18.0 days). Robotics allow more precise measurements of proprioception than clinical assessments. Consequently, an overall APM Task Score was used as ground truth to classify proprioceptive impairments at six months post-stroke. Other APM performance parameters from the two-week assessment were used as predictive features. Clinical assessments included the Thumb Localisation Test (TLT), Behavioural Inattention Test (BIT), Functional Independence Measure (FIM) and demographic information (age, sex and affected arm). Logistic regression classifiers were trained to predict proprioceptive impairments at six months post-stroke using data collected two weeks post-stroke. Models containing robotic features, either alone or in conjunction with clinical and neuroimaging features, had a greater area under the curve (AUC) and lower Akaike Information Criterion (AIC) than models which only contained clinical or neuroimaging features. All models performed similarly with regard to accuracy and F1-score (>70% accuracy). Robotic features were also among the most important when all features were combined into a single model. Predicting long-term proprioceptive impairments, using data collected as early as two weeks post-stroke, is feasible. Identifying those at risk of long-term impairments is an important step towards improving proprioceptive rehabilitation after a stroke.