COVID 19HSC19NCT04335097
Sensor Based Vital Signs Monitoring of Covid 19 Patients During Home Isolation
A study testing Biosensors in people with COVID 19, run by Lars Wik at 1 site in Norway.
Trial summary
Severe acute respiratory syndrome (SARS) SARS-Cov-2 disease (COVID-19) is an infectious disease caused by a coronavirus. The pandemic first described in Wuhan, China, has since spread across the whole world and caused dramatic strain on health care in many countries. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- COVID 19
- What is being tested?
- Biosensors
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 138 participants
- Where
- 1 siteNorway
- Study dates
- 22 Apr 2020to 20 Sep 2022
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Valid informed consent.
- All Covid 19 positive patients age ≥18 years who are under care at home for Covid 19 infection.
- Patients with typical Covid 19 clinical symptoms where a test has not been taken may also be included if a test later is positive.
- Able to log into internet.
Who cannot join
- Age <18 years.
- Covid 19 negative.
- Internals in prison.
- Individuals living in special homes due to need of care.
- Refusal of participation.
- Comorbidity that hinder the patient to run the system.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Sensor Based Vital Signs Monitoring of Patients With Clinical Manifestation of Covid 19 Disease During Home Isolation, a Randomized Feasibility Study
Severe acute respiratory syndrome (SARS) SARS-Cov-2 disease (COVID-19) is an infectious disease caused by a coronavirus. The pandemic first described in Wuhan, China, has since spread across the whole world and caused dramatic strain on health care in many countries. Patients infected with the virus mostly report mild to moderate respiratory symptoms like shortness of breath and coughing, and febrile symptoms. It is of paramount importance to preserve health service capacity by identifying those with serious illness without transferring all infected patients to emergency rooms or Hospitals. In addition, it is important to identify seriously ill patients early enough and before they reach a point of deterioration where they can be extremely challenging to handle in both prehospital and hospital environment.
The present study is designed to sample biosensor data from patients treated and observed at home due to mild and moderate SARS-Cov-2 disease. Such a system would be useful, both for the treatment of individual patients as well as for assessing the efficacy and safety of care given to these patients. Investigators intend to improve quality and safety of home care by continuous monitoring and a set of rules for follow-up.
Investigators hypothesized that patients and local health system may benefit from the feedback of a simple monitoring system, which detects changes in respiration, temperature and circulation variables in combination with the patient's subjective experiences of care. Patients may be referred to hospitalization earlier. In the present study we will use live continuous and non-continuous biosensor data to monitor the development of vital parameters for Covid 19 patients compared with patients who are not monitored electronically (standard of care).
Read the detailed description
Severe acute respiratory syndrome (SARS) SARS-Cov-2 disease (COVID-19) is an infectious disease caused by a coronavirus. The pandemic first described in Wuhan, China, has since spread across the whole world and caused dramatic strain on health care in many countries. The virus spreads primarily through droplets of saliva or discharge from the nose when an infected person coughs or sneezes.1 Patients infected with the virus mostly report mild to moderate respiratory symptoms like shortness of breath and coughing, and febrile symptoms. Most recover without requiring special treatment. However, older people, and those with underlying medical problems (cardiovascular disease, diabetes, chronic respiratory disease, and cancer) are more likely to develop serious illness.1 Younger patients have been reported with serious illness as well. In the present situation, it is of paramount importance to preserve health service capacity by identifying those with serious illness without transferring all infected patients to emergency rooms or Hospitals. In addition, it is important to identify seriously ill patients early enough and before they reach a point of deterioration where they can be extremely challenging to handle in both prehospital and hospital environment.
The number of subjects with positive test of the virus is increasing and so does the number of patients hospitalized.2 In parallel, most patients with positive test result or typical clinical symptoms are at home with information what to do if their clinical symptom status deteriorates.2 The Norwegian Interaction Reform was implemented in 2012.3 Key elements of the reform are guidance of the health care in the future and identify new directions. Prevention and early efforts are important and this will be achieved by creating co-working arenas for different parts of our health system. More health services must be moved closer to where the inhabitants live and simultaneously strengthening the community health system. New tools for monitoring the well-being of the patients must be developed in order to act early enough to avoid severe deterioration of health status and avoid new hospitalization. This goal has become even more important during the Covid 19 pandemic because the healthcare system is not prepared or built to take care of all these patients in hospitals.
In the local community's wearable and wireless biosensors collecting continuous physiological data (CPD) in real time in order to generate information reflecting the patients' current state is established. This is recognized as welfare technology, and it is a generic term for a heterogeneous group of technologies.4 There are few studies documenting their efficacy, effectiveness and efficiency. One key driver for the development of wearable biosensors is the potential to use CPD to generate real-time, clinically actionable insights from predictive analytics that include early warnings of clinical deterioration and prompts for behavioral changes. The advent of machine learning methods that can detect subtle patterns from large sets of CPD may make this achievable.
Using CPD to guide clinical decisions may be a major advance for patients with chronic diseases and at present time when our health system is put on an extreme stretch. This may drive the evolution from episodic to continuous patient care.
The present study is designed to sample biosensor data from patients treated and observed at home due to mild and moderate SARS-Cov-2 disease. Such a system would be useful, both for the treatment of individual patients as well as for assessing the efficacy and safety of care given to these patients. Investigators intend to improve quality and safety of home care by continuous monitoring and a set of rules for follow-up.
Investigators hypothesized that patients and local health system may benefit from the feedback of a simple monitoring system, which detects changes in respiration, temperature and circulation variables in combination with the patient's subjective experiences of care. Patients may be referred to hospitalization earlier. In the present study investigators will use live continuous and non-continuous biosensor data to monitor the development of vital parameters for Covid 19 patients compared with patients who are not monitored electronically (standard of care).
- Conditions
- COVID 19
- Being tested
- Biosensors
- Keywords
- symptoms, biosensors, home isolation, NEWS, Outcome
- Medical subject headings
- COVID-19
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
BiosensorsDevice
Also called Self reporting status
Sensor that detect vital signs
| Study group | Role | What they receive |
|---|---|---|
| Control | Active comparator | Follow general recommendations fram doctor and health authorities what to do and pay attention to before new contact with health service. Receives: Device: Biosensors |
| Intervention | Active comparator | Follow general recommendations fram doctor and health authorities what to do and pay attention to before new contact with health service. I addition active reporting of clinical status and continuous vital sign monitoring based on electronic sensors (Welfare technology). Receives: Device: Biosensors |
What is being measured
The primary outcome is the main question the study is designed to answer.
Stop home isolation
Day during home isolation it was stopped due to hospitalization
Measured: 1 to 21 days
NEWS score
5 or >3 for one organ system
Measured: 1 to 21 days
Secondary outcomes (4)
Clinic at hospitalization
Relevant vital clinical findings
Measured: At admittance hospital
Symptoms developed
Symptoms developed during home isolation
Measured: Duration of home isolation
Relative/peers evaluation of the patient
Their description of vital sign development
Measured: Duration of home isolation
Serious of symptoms at admittance hospital
Referred to ICU, intubated, length of stay
Measured: Hospital stay
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Apr 2020
- Study start22 Apr 2020
- Primary completion8 Apr 2022
- Study completion20 Sep 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (7)Papers the sponsor has linked to this study.
- Other trials for COVID 19Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Two groups, control and intervention.
- Masking
- None (open label)
- Enrolment
- 138 participants (actual)
Sponsor and investigators
- Lead sponsor
- Lars Wik
- Sponsor type
- University, hospital or other
- Collaborators
- University of Stavanger, Oslo University Hospital, Norwegian Telemedicine, University of the Basque Country (UPV/EHU)
- Responsible party
- Sponsor-investigator, Lars Wik, Ullevaal University Hospital
- Investigators
- Lars Wik, MD, Principal investigator, Oslo University Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04335097
- Sponsor's protocol ID
- 127157
- Acronym
- HSC19
- Status last verified
- Sep 2022
- First submitted
- 1 Apr 2020
- Last updated
- 21 Sep 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Bodapati RK, Kizer JR, Kop WJ, Kamel H, Stein PK. Addition of 24-Hour Heart Rate Variability Parameters to the Cardiovascular Health Study Stroke Risk Score and Prediction of Incident Stroke: The Cardiovascular Health Study. J Am Heart Assoc. 2017 Jul 21;6(7):e004305. doi: 10.1161/JAHA.116.004305.
PubMed 28733431Seamless Healthcare Monitoring Advancements in Wearable, Attachable, and Invisible Devices. Chapter 5 Ballistocardiography.
The Royal College of Physicians. National Early Warning Score (NEWS) 2: Standardising the assessment of acute-illness severity in the NHS. London: RCP; 2017. p. 1-77.
Williams B, Alberti G, Ball C, et al; Royal College for Physicians: National Early Warning Score (NEWS): Standardising the Assessment of Acute-Illness Severity in the NHS. 2012London, ENG, Royal College of Physicians.
Meld. St. 16 (2010-2011) Report to the Storting (white paper) Summary - National Health and Care Services Plan. https://www.regjeringen.no/en/dokumenter/meld.-st.-16-2010-2011/id639794/
Samsudin MI, Liu N, Prabhakar SM, Chong SL, Kit Lye W, Koh ZX, Guo D, Rajesh R, Ho AFW, Ong MEH. A novel heart rate variability based risk prediction model for septic patients presenting to the emergency department. Medicine (Baltimore). 2018 Jun;97(23):e10866. doi: 10.1097/MD.0000000000010866.
PubMed 29879021Melillo P, Izzo R, Orrico A, Scala P, Attanasio M, Mirra M, De Luca N, Pecchia L. Automatic prediction of cardiovascular and cerebrovascular events using heart rate variability analysis. PLoS One. 2015 Mar 20;10(3):e0118504. doi: 10.1371/journal.pone.0118504. eCollection 2015.
PubMed 25793605
Study at a glance
From the registry record, last updated by the sponsor on 21 Sep 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Sensor Based Vital Signs Monitoring of Patients With Clinical Manifestation of Covid 19 Disease During Home Isolation, a Randomized Feasibility Study
- ClinicalTrials.gov ID
- NCT04335097
- Acronym / sponsor ID
- HSC19 / 127157
- Conditions
- COVID 19
- Keywords
- symptoms, biosensors, home isolation, NEWS, Outcome
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 138 participants (actual)
- Lead sponsor
- Lars WikUniversity, hospital or other
- Collaborators
- University of Stavanger, Oslo University Hospital, Norwegian Telemedicine, University of the Basque Country (UPV/EHU)
- Study start
- 22 Apr 2020 (actual)
- Primary completion
- 8 Apr 2022 (actual)
- Study completion
- 20 Sep 2022 (actual)
- First posted
- 6 Apr 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Severe acute respiratory syndrome (SARS) SARS-Cov-2 disease (COVID-19) is an infectious disease caused by a coronavirus. The pandemic first described in Wuhan, China, has since spread across the whole world and caused dramatic strain on health care in many countries. Patients infected with the virus mostly report mild to moderate respiratory symptoms like shortness of breath and coughing, and febrile symptoms. It is of paramount importance to preserve health service capacity by identifying those with serious illness without transferring all infected patients to emergency rooms or Hospitals. In addition, it is important to identify seriously ill patients early enough and before they reach a point of deterioration where they can be extremely challenging to handle in both prehospital and hospital environment.
The present study is designed to sample biosensor data from patients treated and observed at home due to mild and moderate SARS-Cov-2 disease. Such a system would be useful, both for the treatment of individual patients as well as for assessing the efficacy and safety of care given to these patients. Investigators intend to improve quality and safety of home care by continuous monitoring and a set of rules for follow-up.
Investigators hypothesized that patients and local health system may benefit from the feedback of a simple monitoring system, which detects changes in respiration, temperature and circulation variables in combination with the patient's subjective experiences of care. Patients may be referred to hospitalization earlier. In the present study we will use live continuous and non-continuous biosensor data to monitor the development of vital parameters for Covid 19 patients compared with patients who are not monitored electronically (standard of care).
Detailed description
Severe acute respiratory syndrome (SARS) SARS-Cov-2 disease (COVID-19) is an infectious disease caused by a coronavirus. The pandemic first described in Wuhan, China, has since spread across the whole world and caused dramatic strain on health care in many countries. The virus spreads primarily through droplets of saliva or discharge from the nose when an infected person coughs or sneezes.1 Patients infected with the virus mostly report mild to moderate respiratory symptoms like shortness of breath and coughing, and febrile symptoms. Most recover without requiring special treatment. However, older people, and those with underlying medical problems (cardiovascular disease, diabetes, chronic respiratory disease, and cancer) are more likely to develop serious illness.1 Younger patients have been reported with serious illness as well. In the present situation, it is of paramount importance to preserve health service capacity by identifying those with serious illness without transferring all infected patients to emergency rooms or Hospitals. In addition, it is important to identify seriously ill patients early enough and before they reach a point of deterioration where they can be extremely challenging to handle in both prehospital and hospital environment.
The number of subjects with positive test of the virus is increasing and so does the number of patients hospitalized.2 In parallel, most patients with positive test result or typical clinical symptoms are at home with information what to do if their clinical symptom status deteriorates.2 The Norwegian Interaction Reform was implemented in 2012.3 Key elements of the reform are guidance of the health care in the future and identify new directions. Prevention and early efforts are important and this will be achieved by creating co-working arenas for different parts of our health system. More health services must be moved closer to where the inhabitants live and simultaneously strengthening the community health system. New tools for monitoring the well-being of the patients must be developed in order to act early enough to avoid severe deterioration of health status and avoid new hospitalization. This goal has become even more important during the Covid 19 pandemic because the healthcare system is not prepared or built to take care of all these patients in hospitals.
In the local community's wearable and wireless biosensors collecting continuous physiological data (CPD) in real time in order to generate information reflecting the patients' current state is established. This is recognized as welfare technology, and it is a generic term for a heterogeneous group of technologies.4 There are few studies documenting their efficacy, effectiveness and efficiency. One key driver for the development of wearable biosensors is the potential to use CPD to generate real-time, clinically actionable insights from predictive analytics that include early warnings of clinical deterioration and prompts for behavioral changes. The advent of machine learning methods that can detect subtle patterns from large sets of CPD may make this achievable.
Using CPD to guide clinical decisions may be a major advance for patients with chronic diseases and at present time when our health system is put on an extreme stretch. This may drive the evolution from episodic to continuous patient care.
The present study is designed to sample biosensor data from patients treated and observed at home due to mild and moderate SARS-Cov-2 disease. Such a system would be useful, both for the treatment of individual patients as well as for assessing the efficacy and safety of care given to these patients. Investigators intend to improve quality and safety of home care by continuous monitoring and a set of rules for follow-up.
Investigators hypothesized that patients and local health system may benefit from the feedback of a simple monitoring system, which detects changes in respiration, temperature and circulation variables in combination with the patient's subjective experiences of care. Patients may be referred to hospitalization earlier. In the present study investigators will use live continuous and non-continuous biosensor data to monitor the development of vital parameters for Covid 19 patients compared with patients who are not monitored electronically (standard of care).
Study design
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- Two groups, control and intervention.
| Arm | Type | Receives |
|---|---|---|
| Control | Active comparator | Device: BiosensorsFollow general recommendations fram doctor and health authorities what to do and pay attention to before new contact with health service. |
| Intervention | Active comparator | Device: BiosensorsFollow general recommendations fram doctor and health authorities what to do and pay attention to before new contact with health service. I addition active reporting of clinical status and continuous vital sign monitoring based on electronic sensors (Welfare technology). |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- Valid informed consent.
- All Covid 19 positive patients age ≥18 years who are under care at home for Covid 19 infection.
- Patients with typical Covid 19 clinical symptoms where a test has not been taken may also be included if a test later is positive.
- Able to log into internet.
Key exclusion criteria (6 listed)
- Age <18 years.
- Covid 19 negative.
- Internals in prison.
- Individuals living in special homes due to need of care.
- Refusal of participation.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| BiosensorsAlso: Self reporting statusSensor that detect vital signs | Device | Control, Intervention |
Primary outcome
Stop home isolation
Time frame: 1 to 21 days
Day during home isolation it was stopped due to hospitalization
NEWS score
Time frame: 1 to 21 days
5 or >3 for one organ system
4 secondary outcomes
Clinic at hospitalization
Time frame: At admittance hospital
Symptoms developed
Time frame: Duration of home isolation
Relative/peers evaluation of the patient
Time frame: Duration of home isolation
Serious of symptoms at admittance hospital
Time frame: Hospital stay
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Sep 2022.
- Background: PubMed 28733431Bodapati RK, Kizer JR, Kop WJ, Kamel H, Stein PK. Addition of 24-Hour Heart Rate Variability Parameters to the Cardiovascular Health Study Stroke Risk Score and Prediction of Incident Stroke: The Cardiovascular Health Study. J Am Heart Assoc. 2017 Jul 21;6(7):e004305. doi: 10.1161/JAHA.116.004305.
- BackgroundSeamless Healthcare Monitoring Advancements in Wearable, Attachable, and Invisible Devices. Chapter 5 Ballistocardiography.
- BackgroundThe Royal College of Physicians. National Early Warning Score (NEWS) 2: Standardising the assessment of acute-illness severity in the NHS. London: RCP; 2017. p. 1-77.
- BackgroundWilliams B, Alberti G, Ball C, et al; Royal College for Physicians: National Early Warning Score (NEWS): Standardising the Assessment of Acute-Illness Severity in the NHS. 2012London, ENG, Royal College of Physicians.
- BackgroundMeld. St. 16 (2010-2011) Report to the Storting (white paper) Summary - National Health and Care Services Plan. https://www.regjeringen.no/en/dokumenter/meld.-st.-16-2010-2011/id639794/
- Results publication: PubMed 29879021Samsudin MI, Liu N, Prabhakar SM, Chong SL, Kit Lye W, Koh ZX, Guo D, Rajesh R, Ho AFW, Ong MEH. A novel heart rate variability based risk prediction model for septic patients presenting to the emergency department. Medicine (Baltimore). 2018 Jun;97(23):e10866. doi: 10.1097/MD.0000000000010866.
- Results publication: PubMed 25793605Melillo P, Izzo R, Orrico A, Scala P, Attanasio M, Mirra M, De Luca N, Pecchia L. Automatic prediction of cardiovascular and cerebrovascular events using heart rate variability analysis. PLoS One. 2015 Mar 20;10(3):e0118504. doi: 10.1371/journal.pone.0118504. eCollection 2015.
- World Health Organization (WHO) recommendationLink provided by the sponsor.
- Folke Helse Instituttet (FHI) recommendationsLink provided by the sponsor.
- WHOLink provided by the sponsor.
- Omsyn Welfare TechnologyLink provided by the sponsor.
- E HealthLink provided by the sponsor.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Lars Wik, MD principal investigator
Oslo University Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Biosensors in people with COVID 19, run by Lars Wik at 1 site in Norway.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 21 Sep 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Norway. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Stop home isolation (time frame: 1 to 21 days). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04335097, which also lists 7 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Sep 2022.