Back to resultsCOntinuous Signs Monitoring In Covid-19 Patients (COSMIC-19)
Primary Purpose
COVID-19
Status
Completed
Phase
Not Applicable
Locations
United Kingdom
Study Type
Interventional
Intervention
Continuous vital sign monitoring - Isansys Patient Status Engine
Machine Learning/AI Algorithm
Sponsored by
About this trial
This is an interventional other trial for COVID-19
Eligibility Criteria
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):
- Positive nasopharyngeal swab during this admission OR
- Nasopharyngeal swab pending during this admission and the treating team suspect COVID-19 OR
- Negative nasopharyngeal swab during this admission but the treating team continue to suspect COVID-19 OR
- Positive nasopharyngeal swab in the last 7 days
- 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:
- Patients unable to give informed consent.
- Patients with a life expectancy of <24hours.
- Known allergy or history of contact dermatitis to medical adhesives.
- Patients with pacemakers, implantable defibrillators or neurostimulators.
- Patients with an arterio-venous fistula in either arm.
Sites / Locations
- The Christie NHS Foundation Trust
- Manchester University NHS Foundation Trust
Arms of the Study
Arm 1
Arm Type
Other
Arm Label
Wearable monitors - Isansys Patient Status Engine
Arm Description
All patients will wear the continuous vital sign monitoring sensors.
Outcomes
Primary Outcome Measures
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.
Secondary Outcome Measures
Performance of the wearable vital signs sensor as measured by the percentage of possible data capture that is actually obtained
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
Full Information
NCT ID
NCT04581031
First Posted
May 4, 2020
Last Updated
May 26, 2022
Sponsor
The Christie NHS Foundation Trust
Collaborators
Manchester University NHS Foundation Trust, Aptus Clinical Ltd., Zenzium Ltd.
1. Study Identification
Unique Protocol Identification Number
NCT04581031
Brief Title
COntinuous Signs Monitoring In Covid-19 Patients
Acronym
COSMIC-19
Official Title
COntinuous Signs Monitoring In Covid-19 Patients
Study Type
Interventional
2. Study Status
Record Verification Date
May 2022
Overall Recruitment Status
Completed
Study Start Date
July 11, 2020 (Actual)
Primary Completion Date
April 22, 2022 (Actual)
Study Completion Date
April 22, 2022 (Actual)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Sponsor
Name of the Sponsor
The Christie NHS Foundation Trust
Collaborators
Manchester University NHS Foundation Trust, Aptus Clinical Ltd., Zenzium Ltd.
4. Oversight
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
Data Monitoring Committee
No
5. Study Description
Brief Summary
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.
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.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
COVID-19
7. Study Design
Primary Purpose
Other
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Masking Description
The treating team on the ward will be blinded to the observations recorded by the wearable vital signs sensors
Allocation
N/A
Enrollment
48 (Actual)
8. Arms, Groups, and Interventions
Arm Title
Wearable monitors - Isansys Patient Status Engine
Arm Type
Other
Arm Description
All patients will wear the continuous vital sign monitoring sensors.
Intervention Type
Device
Intervention Name(s)
Continuous vital sign monitoring - Isansys Patient Status Engine
Intervention Description
CE marked wearable continuous vital signs monitors
Intervention Type
Other
Intervention Name(s)
Machine Learning/AI Algorithm
Intervention Description
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.
Primary Outcome Measure Information:
Title
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.
Time Frame
1 year
Secondary Outcome Measure Information:
Title
Performance of the wearable vital signs sensor as measured by the percentage of possible data capture that is actually obtained
Time Frame
1 year
Title
Look for evidence of circadian disruption in the vital signs of the enrolled patients.
Description
To investigate whether circadian rhythm disruption is involved in COVID-19
Time Frame
1 year
10. Eligibility
Sex
All
Minimum Age & Unit of Time
16 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
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):
Positive nasopharyngeal swab during this admission OR
Nasopharyngeal swab pending during this admission and the treating team suspect COVID-19 OR
Negative nasopharyngeal swab during this admission but the treating team continue to suspect COVID-19 OR
Positive nasopharyngeal swab in the last 7 days
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:
Patients unable to give informed consent.
Patients with a life expectancy of <24hours.
Known allergy or history of contact dermatitis to medical adhesives.
Patients with pacemakers, implantable defibrillators or neurostimulators.
Patients with an arterio-venous fistula in either arm.
Facility Information:
Facility Name
The Christie NHS Foundation Trust
City
Manchester
ZIP/Postal Code
M20 4BX
Country
United Kingdom
Facility Name
Manchester University NHS Foundation Trust
City
Manchester
Country
United Kingdom
12. IPD Sharing Statement
Plan to Share IPD
No
Learn more about this trial
COntinuous Signs Monitoring In Covid-19 Patients
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