K
Kajal Patel
Researcher at University of Manchester
Publications - 6
Citations - 450
Kajal Patel is an academic researcher from University of Manchester. The author has contributed to research in topics: Chronic pain & Neurofeedback. The author has an hindex of 3, co-authored 6 publications receiving 209 citations.
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Journal ArticleDOI
Long-term clinical outcomes in survivors of severe acute respiratory syndrome and Middle East respiratory syndrome coronavirus outbreaks after hospitalisation or ICU admission: A systematic review and meta-analysis.
Hassaan Ahmed,Kajal Patel,Darren C. Greenwood,Stephen J. Halpin,Penny Lewthwaite,Abayomi Salawu,Lorna Eyre,Andrew Breen,Rory J O’Connor,Anthony K. P. Jones,Manoj Sivan +10 more
TL;DR: Lung function abnormalities, psychological impairment and reduced exercise capacity were common in SARS and MERS survivors, and Clinicians should anticipate and investigate similar long-term outcomes in COVID-19 survivors.
Journal ArticleDOI
Applying the WHO ICF Framework to the Outcome Measures Used in the Evaluation of Long-Term Clinical Outcomes in Coronavirus Outbreaks.
TL;DR: Future COVID-19 follow-up studies are recommended to use the ICF framework to select a combination of outcome measures that capture all the components for a better understanding of the impact on survivors and planning interventions to maximize functional return.
Journal ArticleDOI
Effects of neurofeedback in the management of chronic pain: A systematic review and meta-analysis of clinical trials.
Kajal Patel,Heather Sutherland,James Henshaw,Jason R. Taylor,Christopher A. Brown,Alexander J. Casson,Nelson J. Trujillo‐Barreton,Anthony K. P. Jones,Manoj Sivan,Manoj Sivan +9 more
TL;DR: Neurofeedback is a novel therapy with promising but largely low-quality evidence supporting its use in chronic pain and further high-quality trials comparing different protocols is warranted to determine the most efficacious way to deliver neurofeedback.
Journal ArticleDOI
Using EEG Alpha States to Understand Learning During Alpha Neurofeedback Training for Chronic Pain.
Kajal Patel,James Henshaw,Heather Sutherland,Jason R. Taylor,Alexander J. Casson,Karen Lopez-Diaz,Christopher A. Brown,Anthony K. P. Jones,Manoj Sivan,Nelson J. Trujillo-Barreto +9 more
TL;DR: In this article, the authors quantify the changes during α-NFB for chronic pain in terms of dynamic changes in alpha states, such as fractional occupancy, time in high alpha state, dwell time, and transition probability.
Brain Oscillations in Stroke Rehabilitation: What can they tell us about Impairment, Recovery and Response to Training?
TL;DR: Recognition of such EEG patterns has furthered the understanding of the causal relationship between pathophysiological processes and motor function, opening further opportunities to identify biomarkers which will allow us to predict the response of individual to training and tailor the therapeutic intervention in a personalised way to maximise motor recovery after stroke.