COntinuous Signs Monitoring In Covid-19 Patients (COSMIC-19)

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.

Study Overview

• Status: Completed
• Conditions: COVID-19
• Intervention / Treatment: Device: Continuous vital sign monitoring - Isansys Patient Status Engine; Other: Machine Learning/AI Algorithm

Detailed 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.

• Study Type: Interventional
• Enrollment (Actual): 48
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United Kingdom
  • Manchester, United Kingdom, M20 4BX
    • The Christie Nhs Foundation Trust
  • Manchester, United Kingdom
    • Manchester University NHS Foundation Trust

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 16 years and older (ADULT, OLDER_ADULT, CHILD)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

Participants are eligible to be included in the study only if all of the following criteria apply:

1. Adult (aged 16 years or older), hospital inpatients

2. Suspected or confirmed COVID-19 infection (nasopharyngeal swab sent or planned):

   1. Positive nasopharyngeal swab during this admission OR
   2. Nasopharyngeal swab pending during this admission and the treating team suspect COVID-19 OR
   3. Negative nasopharyngeal swab during this admission but the treating team continue to suspect COVID-19 OR
   4. Positive nasopharyngeal swab in the last 7 days
3. 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.
4. 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.
5. For full active treatment (including escalation to critical care)
6. 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:

1. Patients unable to give informed consent.
2. Patients with a life expectancy of <24hours.
3. Known allergy or history of contact dermatitis to medical adhesives.
4. Patients with pacemakers, implantable defibrillators or neurostimulators.
5. Patients with an arterio-venous fistula in either arm.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: OTHER
• Allocation: NA
• Interventional Model: SINGLE_GROUP
• Masking: NONE

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
OTHER: Wearable monitors - Isansys Patient Status Engine; All patients will wear the continuous vital sign monitoring sensors.	Device: Continuous vital sign monitoring - Isansys Patient Status Engine; CE marked wearable continuous vital signs monitors; Other: Machine Learning/AI Algorithm; Patient data will be subjected to machine learning/AI algorithms to determine whether algorithms may be beneficial as an early indication of patient's condition worsening.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
Development of an AI model to predict clinically relevant outcomes for ward-based patients with COVID-19 monitored for up to 20 days. Metrics to be employed depend on the algorithm used but include, Log-Loss, precision and/or recall and confusion matrix.	1 year

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Performance of the wearable vital signs sensor as measured by the percentage of possible data capture that is actually obtained		1 year
Look for evidence of circadian disruption in the vital signs of the enrolled patients.	To investigate whether circadian rhythm disruption is involved in COVID-19	1 year

Collaborators and Investigators

• Sponsor: The Christie NHS Foundation Trust
• Collaborators: Manchester University NHS Foundation Trust; Aptus Clinical Ltd.; Zenzium Ltd.

Study record dates

Study Major Dates

• Study Start (ACTUAL): July 11, 2020
• Primary Completion (ACTUAL): April 22, 2022
• Study Completion (ACTUAL): April 22, 2022

Study Registration Dates

• First Submitted: May 4, 2020
• First Submitted That Met QC Criteria: October 6, 2020
• First Posted (ACTUAL): October 9, 2020

Study Record Updates

• Last Update Posted (ACTUAL): May 27, 2022
• Last Update Submitted That Met QC Criteria: May 26, 2022
• Last Verified: May 1, 2022

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Virus Diseases; Infections; Respiratory Tract Infections; Respiratory Tract Diseases; Pneumonia, Viral; Pneumonia; Lung Diseases; COVID-19
• Other Study ID Numbers: CFTSp187

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No