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

Study Overview
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Brief Summary
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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.

Detailed Description
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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.

Official Title
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Wearable-based COVID-19 Markers for Prediction of Clinical Trajectories. The WAVE Study.

Conditions
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COVID, COVID 19, SARS-CoV 2

Intervention / Treatment
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* Other: Equipment with smartwatch throughout hospital stay on the general ward


Participation Criteria
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Eligibility Criteria
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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

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 120 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Smartwatch group<br> | Other: Equipment with smartwatch throughout hospital stay on the general ward<br>* 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.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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). | 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. | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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). | 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. | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Diagnostic accuracy of predicting hospital discharge without ICU admission in COVID-19 contracted in-patients quantified as area under the receiver operator characteristics curve | 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 | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of heart rate from baseline (hospitalization) to ICU admission | Heart rate will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) and using routine medical monitors. | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of heart rate variability from baseline (hospitalization) to ICU admission | Heart rate variability will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of skin temperature from baseline (hospitalization) to ICU admission | Skin temperature will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of blood oxygen saturation from baseline (hospitalization) to ICU admission | Blood oxygen saturation will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) and using routine medical monitors | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of respiration rate from baseline (hospitalization) to ICU admission | Respiration rate will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) and using routine medical monitors | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of physical activity from baseline (hospitalization) to ICU admission | Physical activity will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of stress level from baseline (hospitalization) to ICU admission | Stress level will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of sleep pattern from baseline (hospitalization) to ICU admission | Sleep will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of steps per day from baseline (hospitalization) to ICU admission | Steps per day will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of systolic blood pressure from baseline (hospitalization) to ICU admission | Systolic blood pressure will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) and using routine medical monitors | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of diastolic blood pressure from baseline (hospitalization) to ICU admission | Diastolic blood pressure will be recorded throughout the hospitalization using a smartwatch (Garmin vivoactive 4S) and using routine medical monitors | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of body temperature from baseline (hospitalization) to ICU admission | Body temperature will be recorded throughout the hospitalization using a routine medical thermometer | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of oxygen partial pressure (pO2) from baseline (hospitalization) to ICU admission | Oxygen partial pressure (pO2) will be routinely assessed during the hospitalization in arterial or venous blood gas analyses | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of CO2 partial pressure (pCO2) from baseline (hospitalization) to ICU admission | CO2 partial pressure (pCO2) will be routinely assessed during the hospitalization in arterial or venous blood gas analyses | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of blood pH from baseline (hospitalization) to ICU admission | Blood pH will be routinely assessed during the hospitalization in arterial or venous blood gas analyses | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of bicarbonate from baseline (hospitalization) to ICU admission | Bicarbonate will be routinely assessed during the hospitalization in arterial or venous blood gas analyses | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of base excess from baseline (hospitalization) to ICU admission | Base excess will be routinely assessed during the hospitalization in arterial or venous blood gas analyses | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 
| Change of oxygen flow rate from baseline (hospitalization) to ICU admission | Oxygen flow rate will be routinely assessed during the hospitalization | until hospital discharge, transfer to ICU or palliative care is initiated (expected to be on average after 7-30 days) | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Smartwatch, Intensive care, Intensive care unit, Prediction, Artificial intelligence, Clinical trajectories