Using Biovitals® Sentinel to Monitor Disease Progression in Subjects Quarantined for Suspected COVID-19

NCT ID: NCT04343794

Last Updated: 2020-04-15

Basic Information

• Recruitment Status: UNKNOWN
• Clinical Phase: NA
• Total Enrollment: 200 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2020-04-01
• Study Completion Date: 2022-01-31

Brief Summary

The novel coronavirus (COVID-19) emerged in December 2019, and in mere months has spread to more than 104 countries, resulting in an outbreak of viral pneumonia worldwide.

Current local quarantine policy in Hong Kong for individuals suspected for COVID-19 requires daily self-reported symptomatology and body temperature, given the intermittent nature and the high dependency of self-discipline undermine the practicality of the approach. To date, the advance in sensor technology has made possible to continuously monitor individual physiological parameters using a simple wearable device. Together with the mobile wearable technology that allowing instantaneous, multi-directional, and massive data transfer, remote continuous physiological monitoring is made possible. The Cardiology division, the Univeristy of Hong Kong has been in collaboration with Biofourmis to implement such technology for remote heart failure management. Similar digital therapeutic system can be applied to remotely monitor physiological parameters of large number of quarantined or suspected COVID-19 at home or in quarantine facility. It is purposed to allow the monitoring team to effectively and remotely monitor COVID-19 quarantined and patients, manage and evaluate the disease progression.

Detailed Description

Owing to the massive outbreak of COVID-19, as of March 9, 2020, the virus has reportedly caused 108,618 infections and 3,800 deaths globally. The World Health Organization (WHO) has declared COVID-19 disease a public health emergency of international concern. As there has yet been specific therapeutic or vaccine for the condition, rigorous implementation of traditional public health measures including isolation, quarantine, social distancing, and community containment is the principle strategy to control the COVID-19 epidemic. In addition to the isolation of confirmed COVID-19 infected patients from noninfected population, it is equally if not more important to quarantine asymptomatic individuals with possible exposure to COVID-19 in order to reduce the viral spread. Indeed, quarantine measures have been initiated in many countries and regions, which restrict movements of asymptomatic individuals with COVID-19 exposure often with fever and symptom surveillance at home or designated facilities for the presumed incubation period (14 days). While conceptually attractive, the intermittency and high dependency of selfdiscipline for body temperature and symptom surveillance undermine the practicality and effectiveness of the approach. Furthermore, it has been reported that as many as 50% of COVID-19 infected patients had not had fever until the full-blown disease, thereby body temperature surveillance per se may not be sufficient to detect early disease progression.

In the past few decades, advances in sensor technology miniaturize electronic physiological sensors that could be incorporated into wearable devices allowing continuous monitoring of physiological parameters such as skin temperature, heart rate, respiratory rate, oxygen saturation, perspiration and activity of ambulatory subjects in a 24/7 basis. Together with current telecommunication platform capable of instantaneous and multi-directional massive data transfer, it is possible to remotely monitor a large number of individual subjects' physiological parameters in a real-time manner, and relay to managing physicians for timely intervention. Nonetheless, such potentials have not been fully explored in the real-world disease management. The current study will assess the impact of remote continuous real-time physiological monitoring using wearable armband device Everion® (Biofourmis, Singapore) and artificial intelligence-powered analytical platform Biovitals® Sentinel (Biofourmis, Singapore) on detection of disease progression in asymptomatic subjects with COVID-19 exposure under mandatory quarantine at designated facilities in Hong Kong. The research hypothesis is that by processing continuous physiological data collected using wearable device Everion® and patient reported outcomes with a cloud-based analytics platform Biovitals® Sentinel, it will possible to detect physiological changes and other clinically meaningful alerts that indicate early clinical progression in quarantined subjects with COVID-19 exposure.

The wearable vital sign monitor Everion® is capable to track multiple vitals sings including heart rate, heart rate variability, blood pulse variation, respiration rate under rest, activity, steps, skin temperature and etc. It is Bluetooth connected to a dedicated study-smartphone that allows remote transfer of all the physiological data captured by the wearable device in real time. A specially-designed application (APP) on the study-smartphone enables the patient to participate in health monitoring by reporting symptoms regularly and make aware of his/her physical and physiological patterns via the monitoring displays on the smart-phone. The patient's passive physiological data from the device and the active data on the symptoms and outcomes from Biovitals® analytics platform are automatically transferred to the monitoring console on the cloud. Thus, the Biofourmis platform solution is proposed to allow the monitoring team to effectively and remotely monitor COVID-19 patients and evaluate the disease progression. Leveraging Everion, the smartphone APP, Biovitals® analytics platform and the caregiver dashboard, biofourmis has built an end to end solution, Biovitals® Sentinel to remote monitor and manage the suspected subjects.

Conditions

COVID19

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

Biovitals

Continuous physiological monitoring using Biovitals platform including (1) armband with multiple physiological sensor, (2) remote monitoring, and (3) Analytic platform. The arm will be worn 23 hours a day and off for 1 hour during showering for recharging battery during 24 hr quarantine period

Group Type: EXPERIMENTAL

BIOVITALS

Intervention Type: DEVICE

Biovitals platform including (1) armband with multiple physiological sensor, (2) remote monitoring, and (3) Analytic platform. The arm will be worn 23 hours a day and off for 1 hour during showering for recharging battery during 24 hr quarantine period

Control

Usual standard care

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

BIOVITALS

Biovitals platform including (1) armband with multiple physiological sensor, (2) remote monitoring, and (3) Analytic platform. The arm will be worn 23 hours a day and off for 1 hour during showering for recharging battery during 24 hr quarantine period

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

• Adult subjects ≥18 years of age
• Quarantined as suspected COVID-19
• Asymptomatic upon enrolment
• All subjects give written informed consent

Exclusion Criteria

• Failure to provide written informed consent

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

The University of Hong Kong

OTHER

Sponsor Role: lead

Responsible Party

Ivan FN Hung MD

Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

David Siu, MD FRCP

Role: PRINCIPAL_INVESTIGATOR

HKU

Locations

The University of Hong Kong, Queen Mary Hospital

Hong Kong, , Hong Kong

Site Status: RECRUITING

Countries

Hong Kong

Central Contacts

David Siu, MD FRCP

Role: CONTACT

cwdsiu@hku.hk

22554694

Ivan Hung, MD FRCPath

Role: CONTACT

ivanhung@hku.hk

22554049

Facility Contacts

David Siu, MD

Role: primary

cwdsiu@hku.hk

22554649

Ivan Hung, MD

Role: backup

ivanhung@hku.hk

22554049

Other Identifiers

COVID19_Biovitals_Protocol_1

Identifier Type: -

Identifier Source: org_study_id