CARP study [COVID-19]
Research type
Research Study
Full title
COVID-19 Advanced Respiratory Physiology Study
IRAS ID
280405
Contact name
Chris Carlin
Contact email
Sponsor organisation
NHS Greater Glasgow & Clyde
Duration of Study in the UK
1 years, 2 months, 30 days
Research summary
Patients with COVID-19 pneumonia are at risk of sudden deterioration. The COVID-19 pandemic presents a requirement to monitor unprecedented numbers of patients with respiratory failure for deterioration. Continuous monitoring of breathing with respiratory rate measurement is recommended in international guidelines, but currently this monitoring is only available in critical care units. \n\nSmall wearable respiratory sensors (around the size of a 10p coin) have been developed. These can potentially monitor a large number of patient’s breathing across a hospital or in the community. We require a trial to determine the feasibility and to start exploring the potential utility of wearable respiratory sensor monitoring in patients with respiratory failure. \n\nCOVID-19 is a new disease. We require additional information about the mechanisms of breathing problems in COVID-19, the mechanisms of response to treatment and the progress and recovery of patients after hospital discharge. New techniques (parasternal EMG, thoracic electrical impedance tomography and wearable wristwatch PPG sensor) have the potential to measure aspects of breathing problems in COVID-19 and other respiratory disorders and give us insights into disease mechanisms and treatment responses. We propose in the CARP sub-studies to explore the feasibility and utility of these non-invasive physiology measurements during hospital admission and post-discharge.\n\nIn the trial evaluation, we will compare the acquired sensor data with de-identified detailed electronic health record data. This will allow us to explore whether the wearable and other physiology measurements might associate with or help predict clinical deterioration in patients with COVID-19 and other respiratory disorders. This data analysis will also provide insights into respiratory failure mechanisms and identify treatment responses. The evaluation will include machine learning analysis which allows us to input large amounts of data and identify patterns from it which can predict clinical events. The output from this study will help us to begin establishing whether wearable respiratory sensor monitoring provides value over and above available clinical information, and allow us to define priorities for future studies including informing trial design and power calculations for these.\n\n
REC name
South East Scotland REC 01
REC reference
20/SS/0078
Date of REC Opinion
16 Jul 2020
REC opinion
Further Information Favourable Opinion