The greatest mortality and disability from stroke occurs in low- and middle-income countries. A significant barrier to implementation of best stroke care practices in these settings is limited ...availability of specialized healthcare training. We conducted a systematic review to determine the most effective methods for the provision of speciality stroke care education for hospital-based healthcare professionals in low-resource settings.
We followed the PRISMA guidelines for systematic reviews and searched PubMed, Web of Science and Scopus for original clinical research articles that described or evaluated stroke care education for hospital-based healthcare professionals in low-resource settings. Two reviewers screened titles/abstracts and then full text articles. Three reviewers critically appraised the articles selected for inclusion.
A total of 1,182 articles were identified and eight were eligible for inclusion in this review; three were randomized controlled trials, four were non-randomized studies, and one was a descriptive study. Most studies used several approaches to education. A "train-the-trainer" approach to education was found to have the most positive clinical outcomes (lower overall complications, lengths of stay in hospital, and clinical vascular events). When used for quality improvement, the "train-the-trainer" approach increased patient reception of eligible performance measures. When technology was used to provide stroke education there was an increased frequency in diagnosis of stroke and use of antithrombotic treatment, reduced door-to-needle times, and increased support for decision making in medication prescription was reported. Task-shifting workshops for non-neurologists improved knowledge of stroke and patient care. Multidimensional education demonstrated an overall care quality improvement and increased prescriptions for evidence-based therapies, although, there were no significant differences in secondary prevention efforts, stroke reoccurrence or mortality rates.
The "train the trainer" approach is likely the most effective strategy for specialist stroke education, while technology is also useful if resources are available to support its development and use. If resources are limited, basic knowledge education should be considered at a minimum and multidimensional training may not be as beneficial. Research into communities of practice, led by those in similar settings, may be helpful to develop educational initiatives with relevance to local contexts.
•The study established the utility of EEG parameters as prognostic markers for assessing condition of stroke.•It used one-minute EEG data to predict type of stroke, severity of stroke and affected ...artery during stroke using Deep Learning models.•The study predicts stroke severity on terms of NIHSS score, hence removing subjectivity.•This study is the first to report artery affected due to stroke using EEG data.
Stroke has become a leading cause of disability worldwide. Early medication and rehabilitation is the key to help post-stroke survivors recover faster. Presently, doctors rely on imaging modalities like CT/MRI for diagnosing stroke patients. The diagnosis done using these modalities can be highly subjective. Apart from this, these imaging modalities are very costly, time taking and inconvenient for the patients. So there is a need of faster, portable and an automated diagnostic system for assessing post-stroke conditions so that right measures can be taken in the right time. To cater to this need EEG comes in handy because of its portable nature. So, in this work, utility of EEG has been studied to diagnose three aspects of stroke: 1) type of stoke, 2) affected artery and 3) severity of stroke. To achieve this, one-minute resting state EEG data was used to extract 57 features. The features were ranked and selected using ranking algorithm and deep learning (DL) models were trained with supervision from information extracted using MRI data. To find out type of stroke and affected artery DWI, SWI and MRA images were used, and severity of stroke was recorded in terms of NIHSS score. Three different DL models were trained for each task i.e. type of stroke, affected artery and severity of stroke. For classifying type of stroke an accuracy of 97.74% was obtained using 37 features. For stroke severity, the model gave RMSE of 2.1955 with a high correlation value (r = 0.91). The DL model for classifying affected artery used 33 features and gave accuracy of 95.7%. It was also found that less complex time domain features and QEEG features were frequently selected out of 57 features for all the DL models. Features in delta and theta sub-bands were frequently selected along with QEEG features. The work presented here established that EEG can act as a reliable modality for faster diagnosis of stroke specifics and hence can help medical professionals in speeding the decision making process.
Background: Cognitive deficit is one of the common impairments that occur post stroke and have a major effect on the quality of life of stroke survivors. However, the intervention and outcome ...measures used to remediate post-stroke cognitive impairments are diverse and highly heterogeneous. Therefore, a review of intervention and outcome measures for post-stroke cognitive impairments was carried out. Objectives: To review all available information on the recent advancements in intervention and outcome measures for post-stroke cognitive impairments. Methods: An electronic database search was conducted in PubMed, Medline, Google Scholar, and the Cochrane Library with key search terms between 2001 and 2021. The search results were systematically screened, and data was independently extracted by three reviewers. The data was thematically analyzed and narratively synthesized. Results: The search retrieved 2018 records, and we included 12 studies that met the inclusion criteria. Most of the studies targeted global cognitive deficits in ischemic stroke patients in the chronic phase. We categorized data based on the type of cognitive impairment, cognitive- domain targeted, intervention, and available outcome measures for post-stroke cognitive rehabilitation. Attention, memory, executive function, and global cognition were the common cognitive components targeted, managed, and assessed using an outcome measure. We found that technology is replacing conventional approaches to improve cognitive impairment. Conclusion: Regardless of many new developments in post-stroke cognitive rehabilitation interventions driven by technology, there is limited data available on actual implementation as a scalable solution. There is an extensive need for future research for evidence-based assessment and management of cognitive impairments in post-stroke rehabilitation.
Abstract
Objective
The study aims to determine the effects of implementing stroke unit (SU) care in a remote hospital in North-East India.
Materials and Methods
This before-and-after implementation ...study was performed at the Baptist Christian Mission Hospital, Tezpur, Assam between January 2015 and December 2017. Before the implementation of stroke unit care (pre-SU), we collected information on usual stroke care and 1-month outcome of 125 consecutive stroke admissions. Staff was then trained in the delivery of SU care for 1 month, and the same information was collected in a second (post-SU) cohort of 125 patients.
Statistical Analysis
Chi-square and Mann–Whitney U test were used to compare group differences. The loss to follow-up was imputed by using multiple imputations using the Markov Chain Monto Carlo method. The sensitivity analysis was also performed by using propensity score matching of the groups for baseline stroke severity (National Institute of Health Stroke Scale) using the nearest neighbor approach to control for confounding, and missing values were imputed by using multiple imputations. The adjusted odds ratio was calculated in univariate and multivariate regression analysis after adjusting for baseline variables. All the analysis was done by using SPSS, version 21.0., IBM Corp and R version 4.0.0., Armonk, New York, United States.
Results
The pre-SU and post-SU groups were age and gender matched. The post-SU group showed higher rates of swallow assessment (36.8 vs. 0%,
p
< 0.001), mobility assessment, and re-education (100 vs. 91.5%,
p
= 0.037). The post-SU group also showed reduced complications (28 vs. 45%,
p
= 0.006) and a shorter length of hospital stay (4 ± 2.16 vs. 5 ± 2.68 days,
p
= 0.026). The functional outcome (modified ranking scale) at 1-month showed no difference between the groups, good outcome in post-SU (39.6%) versus pre-SU (35.7%),
p
= 0.552.
Conclusion
The implementation of this physician-based SU care model in a remote hospital in India shows improvements in quality measures, complications, and possibly patient outcomes.
Stroke is a leading cause of permanent disability worldwide. Even after adequate treatment, the majority of patients do not recover fully, making them dependent on others for carrying out Activities ...of Daily Living (ADL). An improved understanding of the underlying mechanism of plasticity will help us in customizing the translational approach for learning and rehabilitation following a stroke. For this study, a 2-minute resting state EEG data were recorded at 5 time-points for 3-months after stroke onset. Directed Transfer Function (DTF) was used to study neural reorganization for 3 months. DTF for different brain regions and sub-bands was correlated with FMA. The information flow was studied for different brain regions as well as Affected Region (AR). Occipital region showed good correlation (r = 0.45 to 0.47) with FMA. Contra-lesional and ipsi-lesional regions trajectories complement each other during acute and sub-acute phase. The information outflow vs inflow imbalance of AR was restored by the end of 3 months. DTF can be used as biomarker for studying neuroplasticity. Occipital, temporal and motor cortex regions play an important role during neuro-rehabilitation. The information about different regions during rehabilitation will help us in designing subject-specific interventions for better recovery.
Post-stroke monitoring is a crucial step for properly studying the progress of stroke patients. The rehabilitation process consists of exercise regimes that help in constantly engaging the affected ...part of the brain leading to faster recovery. The work here studies the effectiveness of the rehabilitation regime by investigating several parameters that can play important role in observing the immediate effect of the exercises. Various parameters from different wavelet coefficients were extracted for monitoring rehabilitation for up to 90 days. Energy and waveform length show maximum variation when monitoring pre and post-exercise changes. The parameters were correlated with clinical(FMA) score. Centroid Index gave high correlation value for beta band (r = -0.559). Alpha band on the other hand showed a good correlation with all the extracted fe atures, maximum being -0.6988 with energy. So for monitoring post-stroke rehabilitation alpha and beta bands should be focused. Region-specific analyses were also done to monitor changes in different parts of the brain.
The Na x MnO2 system is an important class of materials with potential applications in rechargeable batteries, supercapacitors, catalysts, and gas sensors. This work reports the synthesis of Na x ...MnO2 (x = 0.39, 0.44, 0.48, 0.66, and 0.70) compounds and their characterization by powder X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and impedance spectroscopy (IS) techniques. The compounds in this series exhibit a significant variation in their structures with the extent of Na-content. The change in the nature of bonding with increasing Na content was investigated, and its effect on material stability as well as electrotransport properties was investigated. A detailed thermodynamic evaluation of these materials was carried out employing calorimetric techniques, and the data were correlated with changes in the chemical environment around the Na ion. This analysis is crucial for predicting the thermodynamic stability of Na x MnO2 compounds under different environments for their applications in Na-ion batteries.
The NaxMnO2 system is an important class of materials with potential applications in rechargeable batteries, supercapacitors, catalysts, and gas sensors. This work reports the synthesis of NaxMnO2 (x ...= 0.39, 0.44, 0.48, 0.66, and 0.70) compounds and their characterization by powder X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and impedance spectroscopy (IS) techniques. The compounds in this series exhibit a significant variation in their structures with the extent of Na-content. The change in the nature of bonding with increasing Na content was investigated, and its effect on material stability as well as electrotransport properties was investigated. A detailed thermodynamic evaluation of these materials was carried out employing calorimetric techniques, and the data were correlated with changes in the chemical environment around the Na ion. This analysis is crucial for predicting the thermodynamic stability of NaxMnO2 compounds under different environments for their applications in Na-ion batteries.The NaxMnO2 system is an important class of materials with potential applications in rechargeable batteries, supercapacitors, catalysts, and gas sensors. This work reports the synthesis of NaxMnO2 (x = 0.39, 0.44, 0.48, 0.66, and 0.70) compounds and their characterization by powder X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and impedance spectroscopy (IS) techniques. The compounds in this series exhibit a significant variation in their structures with the extent of Na-content. The change in the nature of bonding with increasing Na content was investigated, and its effect on material stability as well as electrotransport properties was investigated. A detailed thermodynamic evaluation of these materials was carried out employing calorimetric techniques, and the data were correlated with changes in the chemical environment around the Na ion. This analysis is crucial for predicting the thermodynamic stability of NaxMnO2 compounds under different environments for their applications in Na-ion batteries.
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