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This is a pilot study to assess whether artificial intelligence (AI) combined with continuous vital signs monitoring from wearable sensors can predict clinically relevant outcomes in patients with suspected or confirmed Covid-19 infection on general medical wards.
Full description
Adult patients on general medical wards with COVID-19 infection considered to be at high risk of deterioration will be asked to wear vital signs sensors for the duration of their hospital stay. These sensors are an established method of recording patient vital signs and are CE marked. Patients enrolled in the study will continue to receive routine medical care as directed by their treating team.
All data recorded from the wearable sensors in this study will be analysed in conjunction with routine data collected during the patient's treatment. Several models will be created using deep learning AI techniques with the aim of reliably predicting several important clinical outcomes. The study will identify whether continuous monitoring alone can improve identification of deteriorating patients compared to traditional vital signs and if the addition of AI technology / algorithms can provide even earlier identification.
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Inclusion criteria
Participants are eligible to be included in the study only if all of the following criteria apply:
Adult (aged 16 years or older), hospital inpatients
Suspected or confirmed COVID-19 infection (nasopharyngeal swab sent or planned):
Emergency admission to hospital within the last 72 hours and/or a positive nasopharyngeal test within the last 72 hours taken from a patient who was already an inpatient at the time the swab was taken.
Symptoms consistent with COVID-19 infection at the time of admission or when swab taken: cough, shortness of breath, alteration to sense of taste or smell, fevers or other symptoms in keeping with COVID-19 in the opinion of the study team.
For full active treatment (including escalation to critical care)
The patient is at risk of deterioration (as evidenced by a requirement for supplementary oxygen)
Exclusion criteria
Participants are excluded from the study if any of the following criteria apply:
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Masking
48 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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