WAVE. Wearable-based COVID-19 Markers for Prediction of Clinical Trajectories

Sponsor
University Hospital Inselspital, Berne (Other)
Overall Status
Completed
CT.gov ID
NCT04357834
Collaborator
ETH Zurich (Other)
46
1
8.2
5.6

Study Details

Study Description

Brief Summary

The aim is to develop a wearable-based ICU (intensive care unit) prediction algorithm for inpatients contracted with SARS-CoV-2. Inpatients with suspicion of COVID-19 or with confirmed SARS-CoV-2 infection will be included. The participants will be equipped with a smartwatch, which gathers physiological data throughout hospitalisation.

Condition or Disease Intervention/Treatment Phase
  • Other: Equipment with smartwatch throughout hospital stay on the general ward

Detailed Description

The SARS-CoV-2 pandemic puts an unprecedented burden on the healthcare system, specifically its healthcare providers and the resource demands for intensive care units (ICUs). To support effective care despite large case numbers, hospital operations urgently need improved decision support in early identification of patients at risk of an acute COVID-19 deterioration that requires ICU.

The investigators aim at developing a wearable-based ICU algorithm for inpatients contracted with SARS-CoV-2. Inpatients on the general ward with suspicion of COVID-19 or with confirmed SARS-CoV-2 infection will be included. The participant will be equipped with a smartwatch and wear the device throughout the hospital stay until the patient (1) is discharged home, (2) is transferred to the ICU, or (3) palliative care is initiated. The smartwatch collects several physiological parameters (e.g. heart rate, heart rate variability, respiration rate, oxygen saturation). The collected data will be used to develop an ICU prediction algorithm to detect patients at risk of an acute COVID-19 deterioration that requires ICU.

Study Design

Study Type:
Observational
Actual Enrollment :
46 participants
Observational Model:
Other
Time Perspective:
Prospective
Official Title:
Wearable-based COVID-19 Markers for Prediction of Clinical Trajectories. The WAVE Study.
Actual Study Start Date :
Oct 22, 2020
Actual Primary Completion Date :
Jun 30, 2021
Actual Study Completion Date :
Jun 30, 2021

Arms and Interventions

Arm Intervention/Treatment
Smartwatch group

Other: Equipment with smartwatch throughout hospital stay on the general ward
Participants with confirmed SARS-CoV-2 infection or suspicion of COVID-19 will be equipped with a smartwatch and wear the device throughout the hospital stay on the general ward.

Outcome Measures

Primary Outcome Measures

  1. Diagnostic accuracy of smartwatch data in predicting ICU requirement in COVID-19 contracted inpatients quantified as the area under the receiver operator characteristics curve (AUC ROC > 0.85). [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Accuracy of the WAVE-model will be assessed using physiological data recorded by the smartwatch (Garmin vivoactive 4) during hospitalization complemented by demographic and health-related patient-information and will be analysed using applied machine learning technology for ICU prediction.

Secondary Outcome Measures

  1. Diagnostic accuracy of routine physiological data in predicting ICU requirement in COVID-19 contracted in-patients quantified as the area under the receiver operator characteristics curve (AUC ROC > 0.85). [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Accuracy of the model will be assessed using physiological data routinely recorded during hospitalization and will be analysed using applied machine learning technology for ICU prediction.

  2. Diagnostic accuracy of predicting hospital discharge without ICU admission in COVID-19 contracted in-patients quantified as area under the receiver operator characteristics curve [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Accuracy of the model will be assessed using data on comorbidities, medication treatment during hospitalization and physiological data and will be analysed using casual machine-learning approaches

  3. Change of heart rate from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Heart rate will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) and using routine medical monitors.

  4. Change of heart rate variability from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Heart rate variability will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S)

  5. Change of skin temperature from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Skin temperature will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S)

  6. Change of blood oxygen saturation from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Blood oxygen saturation will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) and using routine medical monitors

  7. Change of respiration rate from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Respiration rate will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) and using routine medical monitors

  8. Change of physical activity from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Physical activity will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S)

  9. Change of stress level from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Stress level will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S)

  10. Change of sleep pattern from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Sleep will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S)

  11. Change of steps per day from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Steps per day will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S)

  12. Change of systolic blood pressure from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Systolic blood pressure will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) and using routine medical monitors

  13. Change of diastolic blood pressure from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Diastolic blood pressure will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) and using routine medical monitors

  14. Change of body temperature from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Body temperature will be recorded throughout the hospitalization using a routine medical thermometer

  15. Change of oxygen partial pressure (pO2) from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Oxygen partial pressure (pO2) will be routinely assessed during the hospitalization in arterial or venous blood gas analyses

  16. Change of CO2 partial pressure (pCO2) from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    CO2 partial pressure (pCO2) will be routinely assessed during the hospitalization in arterial or venous blood gas analyses

  17. Change of blood pH from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Blood pH will be routinely assessed during the hospitalization in arterial or venous blood gas analyses

  18. Change of bicarbonate from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Bicarbonate will be routinely assessed during the hospitalization in arterial or venous blood gas analyses

  19. Change of base excess from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Base excess will be routinely assessed during the hospitalization in arterial or venous blood gas analyses

  20. Change of oxygen flow rate from baseline (hospitalization) to ICU admission [until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days)]

    Oxygen flow rate will be routinely assessed during the hospitalization

Eligibility Criteria

Criteria

Ages Eligible for Study:
18 Years to 120 Years
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
No
Inclusion Criteria:
  • Informed consent as documented by signature

  • Age >= 18 years

  • Suspicion of COVID-19 or patient tested positive for SARS-CoV-2

  • Hospitalisation on the general ward

Exclusion Criteria:
  • Smartwatch cannot be attached around the wrist of the patient

  • Direct transfer from the emergency department or external institution to ICU (i.e. no hospitalization on the general ward)

  • Known allergies to components of the smartwatch

  • Rejection of ICU transfer in the patient decree

Contacts and Locations

Locations

Site City State Country Postal Code
1 Emergency Department, University Hospital Bern, Inselspital Bern Switzerland 3010

Sponsors and Collaborators

  • University Hospital Inselspital, Berne
  • ETH Zurich

Investigators

  • Study Chair: Aristomenis Extradaktylos, Prof. MD, University Hospital Bern - Department of Emergency Medicine

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
University Hospital Inselspital, Berne
ClinicalTrials.gov Identifier:
NCT04357834
Other Study ID Numbers:
  • WAVE
First Posted:
Apr 22, 2020
Last Update Posted:
Aug 26, 2021
Last Verified:
Aug 1, 2021
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Keywords provided by University Hospital Inselspital, Berne
Additional relevant MeSH terms:

Study Results

No Results Posted as of Aug 26, 2021