Exercise-Based Stroke Rehabilitation: Clinical Considerations Following the COVID-19 Pandemic

Background. The COVID-19 pandemic attributable to the severe acute respiratory syndrome virus (SARS-CoV-2) has had a significant and continuing impact across all areas of healthcare including stroke. Individuals post-stroke are at high risk for infection, disease severity, and mortality after COVID-19 infection. Exercise stroke rehabilitation programs remain critical for individuals recovering from stroke to mitigate risk factors and morbidity associated with the potential long-term consequences of COVID-19. There is currently no exercise rehabilitation guidance for people post-stroke with a history of COVID-19 infection. Purpose. To (1) review the multi-system pathophysiology of COVID-19 related to stroke and exercise; (2) discuss the multi-system benefits of exercise for individuals post-stroke with suspected or confirmed COVID-19 infection; and (3) provide clinical considerations related to COVID-19 for exercise during stroke rehabilitation. This article is intended for healthcare professionals involved in the implementation of exercise rehabilitation for individuals post-stroke who have suspected or confirmed COVID-19 infection and non-infected individuals who want to receive safe exercise rehabilitation. Results. Our clinical considerations integrate pre-COVID-19 stroke (n = 2) and COVID-19 exercise guidelines for non-stroke populations (athletic [n = 6], pulmonary [n = 1], cardiac [n = 2]), COVID-19 pathophysiology literature, considerations of stroke rehabilitation practices, and exercise physiology principles. A clinical decision-making tool for COVID-19 screening and eligibility for stroke exercise rehabilitation is provided, along with key subjective and physiological measures to guide exercise prescription. Conclusion. We propose that this framework promotes safe exercise programming within stroke rehabilitation for COVID-19 and future infectious disease outbreaks.

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Evidence-based practice ‘on-the-go’: using ViaTherapy as a tool to enhance clinical decision making in upper limb rehabilitation after stroke, a quality improvement initiative

BMJ Open Quality ◽

10.1136/bmjoq-2018-000592 ◽

2019 ◽

Vol 8 (3) ◽

pp. e000592 ◽

Cited By ~ 1

Author(s):

Nicola J Hancock ◽

Kathryn Collins ◽

Charlie Dorer ◽

Steven L Wolf ◽

Mark Bayley ◽

...

Keyword(s):

Quality Improvement ◽

Upper Limb ◽

Stroke Rehabilitation ◽

Clinical Decision Making ◽

Clinical Decision ◽

Evidence Based ◽

Improvement Project ◽

Upper Limb Rehabilitation ◽

Community Rehabilitation ◽

Limb Rehabilitation

Recovery of upper limb function after stroke is currently sub-optimal, despite good quality evidence showing that interventions enabling repetitive practice of task-specific activity are effective in improving function. Therapists need to access and engage with such evidence to optimise outcomes with people with stroke, but this is challenging in fast-paced stroke rehabilitation services. This quality improvement project aimed to investigate acceptability and service impact of a new, international tool for accessing evidence on upper limb rehabilitation after stroke—‘ViaTherapy’—in a team of community rehabilitation therapists. Semi-structured interviews were undertaken at baseline to determine confidence in, and barriers to, evidence-based practice (EBP) to support clinical decision making. Reported barriers included time, lack of access to evidence and a research-practice disconnect. The clinicians then integrated use of ‘ViaTherapy’ into their practice for 4 weeks. Follow-up interviews explored the accessibility of the tool in community rehabilitation practice, and its impact on clinician confidence, treatment planning and provision. Clinicians found the tool, used predominantly in mobile device app format, to be concise and simple to use, providing evidence ‘on-the-go’. Confidence in accessing and using EBP grew by 22% from baseline. Clinicans reported changes in intensity of delivery of interventions, as rapid access to recommended doses via the tool was available. Following this work, the participating health and social care service provider changed provision of therapists’ technology to enable use of apps. Barriers to use of EBP in stroke rehabilitation persist; the baseline situation here supported the need for more accessible means of integrating best evidence into clinical processes. This quality improvement project successfully integrated ViaTherapy into clinical practice, and found that the tool has potential to underpin positive changes in upper limb therapy service delivery after stroke, by increasing accessibility to, use of and confidence in EBP. Definitive evaluation is now indicated.

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Clinical Decision Making when Addressing Upper Limb Post-Stroke Sensory Impairments

British Journal of Occupational Therapy ◽

10.4276/030802213x13706169932789 ◽

2013 ◽

Vol 76 (6) ◽

pp. 254-263 ◽

Cited By ~ 6

Author(s):

Susan Doyle ◽

Sally Bennett ◽

Louise Gustafsson

Keyword(s):

Decision Making ◽

Upper Limb ◽

Clinical Decision Making ◽

Clinical Decision ◽

Post Stroke ◽

Sensory Impairments

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Comparing Machine Learning Algorithms for Predicting ICU Admission and Mortality in COVID-19

10.1101/2020.11.20.20235598 ◽

2020 ◽

Author(s):

Sonu Subudhi ◽

Ashish Verma ◽

Ankit B. Patel ◽

C. Corey Hardin ◽

Melin J. Khandekar ◽

...

Keyword(s):

Machine Learning ◽

Clinical Decision Making ◽

Learning Algorithms ◽

Disease Outbreaks ◽

Clinical Decision ◽

Machine Learning Algorithms ◽

Healthcare Database ◽

Icu Admission ◽

Infectious Disease Outbreaks ◽

Better Than

AbstractAs predicting the trajectory of COVID-19 disease is challenging, machine learning models could assist physicians determine high-risk individuals. This study compares the performance of 18 machine learning algorithms for predicting ICU admission and mortality among COVID-19 patients. Using COVID-19 patient data from the Mass General Brigham (MGB) healthcare database, we developed and internally validated models using patients presenting to Emergency Department (ED) between March-April 2020 (n = 1144) and externally validated them using those individuals who encountered ED between May-August 2020 (n = 334). We show that ensemble-based models perform better than other model types at predicting both 5-day ICU admission and 28-day mortality from COVID-19. CRP, LDH, and procalcitonin levels were important for ICU admission models whereas eGFR <60 ml/min/1.73m2, ventilator use, and potassium levels were the most important variables for predicting mortality. Implementing such models would help in clinical decision-making for future COVID-19 and other infectious disease outbreaks.

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Clarity and contradictions: speech and language therapists' insights regarding thickened liquids for post-stroke aspiration

International Journal of Therapy and Rehabilitation ◽

10.12968/ijtr.2019.0020 ◽

2020 ◽

Vol 27 (6) ◽

pp. 1-15

Author(s):

Arlene McCurtin ◽

Ronan Brady ◽

Katherine Coffey ◽

Anne O'Connor

Keyword(s):

Clinical Decision Making ◽

Treatment Effectiveness ◽

Oropharyngeal Dysphagia ◽

Empirical Support ◽

Clinical Decision ◽

Thickened Liquids ◽

Speech And Language ◽

Post Stroke ◽

Treatment Use ◽

Safety First

Background/Aims Oropharyngeal dysphagia is a common condition following stroke, with adverse consequences including aspiration pneumonia. Internationally, aspiration risk is typically managed using thickened liquids, an intervention with limited empirical support and associated treatment adherence issues. This study explores speech and language therapists' perceptions of and reasons for employing this intervention. Methods A total of 22 speech and language therapists working with people with dysphagia post-stroke in hospital settings participated in three focus groups. Participants were recruited through gatekeeper managers and data were analysed using inductive thematic analysis. Results Three themes were identified: primary justifications for treatment use, acute implementation issues, and having doubts. Use of thickened liquids is pivoted on safety-first reasoning, employed as a first step on the treatment ladder and in the context of limited perceived alternatives. Both clarity and contradictions are revealed by therapists, who acknowledge multiple factors that impact treatment effectiveness, including hospital, patient and product issues. Conclusions The findings from this study provide a basis for understanding clinical decision making for a widely-used gateway treatment that requires further empirical support. The data suggest that, similar to other professions, safety-first reasoning is paramount for speech and language therapists. The dominance of thickened liquids in treating aspiration is reflected internationally and warrants ongoing discussion.

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Determinants of research use in clinical decision making among physical therapists providing services post-stroke: a cross-sectional study

Implementation Science ◽

10.1186/1748-5908-5-77 ◽

2010 ◽

Vol 5 (1) ◽

Cited By ~ 39

Author(s):

Nancy M Salbach ◽

Sara JT Guilcher ◽

Susan B Jaglal ◽

David A Davis

Keyword(s):

Decision Making ◽

Clinical Decision Making ◽

Physical Therapists ◽

Clinical Decision ◽

Cross Sectional Study ◽

Research Use ◽

Sectional Study ◽

Cross Sectional ◽

Post Stroke

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Dysphagia therapy post stroke: An exploration of the practices and clinical decision-making of speech-language pathologists in Australia

International Journal of Speech-Language Pathology ◽

10.1080/17549507.2016.1265588 ◽

2017 ◽

Vol 20 (2) ◽

pp. 226-237 ◽

Cited By ~ 11

Author(s):

Olivia Jones ◽

Jade Cartwright ◽

Anne Whitworth ◽

Naomi Cocks

Keyword(s):

Decision Making ◽

Clinical Decision Making ◽

Clinical Decision ◽

Speech Language Pathologists ◽

Post Stroke ◽

Dysphagia Therapy

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Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19

npj Digital Medicine ◽

10.1038/s41746-021-00456-x ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Sonu Subudhi ◽

Ashish Verma ◽

Ankit B. Patel ◽

C. Corey Hardin ◽

Melin J. Khandekar ◽

...

Keyword(s):

Machine Learning ◽

Clinical Decision Making ◽

Learning Algorithms ◽

Disease Outbreaks ◽

Clinical Decision ◽

Machine Learning Algorithms ◽

Healthcare Database ◽

Icu Admission ◽

Infectious Disease Outbreaks ◽

Better Than

AbstractAs predicting the trajectory of COVID-19 is challenging, machine learning models could assist physicians in identifying high-risk individuals. This study compares the performance of 18 machine learning algorithms for predicting ICU admission and mortality among COVID-19 patients. Using COVID-19 patient data from the Mass General Brigham (MGB) Healthcare database, we developed and internally validated models using patients presenting to the Emergency Department (ED) between March-April 2020 (n = 3597) and further validated them using temporally distinct individuals who presented to the ED between May-August 2020 (n = 1711). We show that ensemble-based models perform better than other model types at predicting both 5-day ICU admission and 28-day mortality from COVID-19. CRP, LDH, and O2 saturation were important for ICU admission models whereas eGFR <60 ml/min/1.73 m2, and neutrophil and lymphocyte percentages were the most important variables for predicting mortality. Implementing such models could help in clinical decision-making for future infectious disease outbreaks including COVID-19.

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Post Stroke Rehabilitation

Galen Medical Journal ◽

10.31661/gmj.v5is1.584 ◽

2016 ◽

Vol 5 ◽

pp. 62-65

Author(s):

Sharareh Roshanzamir

Keyword(s):

Stroke Rehabilitation ◽

Multidisciplinary Approach ◽

Memory Loss ◽

Rehabilitation Team ◽

Sensory Deficits ◽

Post Stroke ◽

Rehabilitation Programs ◽

Constraint Induced Movement Therapy ◽

Paretic Limb ◽

Bilateral Arm Training

The modern stroke rehabilitation programs focuses on specific bio-physiological targets. Modern rehabilitation programs mainly make use of its potential plasticity to compensate for injury. Constraint-induced movement therapy (CIMT), bilateral arm training, and task specific training of the paretic limb, are examples of rehabilitation techniques promoting brain neuro-plasticity. There are many tasks other than locomotor function to be addressed by rehabilitation team. Sensory deficits, speech deficits, dysphagia, memory loss, post stroke central pains and bowel and bladder derangements are among the most important of these challenges that makes a multidisciplinary approach to stroke patients necessary.

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Motor Imagery Training for Gait Rehabilitation of People With Post-Stroke Hemiparesis: Practical Applications and Protocols

Global Journal of Health Science ◽

10.5539/gjhs.v10n11p66 ◽

2018 ◽

Vol 10 (11) ◽

pp. 66 ◽

Cited By ~ 4

Author(s):

Ayelet Dunsky ◽

Ruth Dickstein

Keyword(s):

Motor Learning ◽

Motor Imagery ◽

Stroke Rehabilitation ◽

Treatment Session ◽

Practical Applications ◽

Impaired Performance ◽

Post Stroke ◽

Imagery Training ◽

Rehabilitation Programs ◽

Learning Principles

Over the last two decades, the use of motor imagery (MI) for post-stroke rehabilitation has significantly increased. Previous findings support the feasibility of the incorporation of specific MI exercises to improve walking skills in individuals with post-stroke hemiparesis. However, detailed practical applications and specific protocols for the implementation of MI are scarce. The objective of this manuscript is to propose practical applications for a structured MI regimen, including detailed protocols of a six-week intervention targeting gait improvement following stroke. The proposed regimen is based on previous experience with MI rehabilitation programs for gait improvement following stroke, motor learning principles with applications for stroke rehabilitation, and the PETTLEP model. The proposed detailed protocols were found to be adjusted for gait improvement of post-stroke survivors as described in several studies, and may address the targets of different rehabilitation programs. Based on motor learning principles and guidelines, an example of verbal instructions for each treatment session during six weeks of intervention is proposed. The potential of this training program to augment and extend the rehabilitation process was proven in several studies. The variety of possibilities of scenes to image allows the clinician to target specific impaired performance and disabilities. By using the proposed structure and protocols, a large number of therapists may be able to address these targets.

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