CoronaWatch - Early Detection of Cardiovascular Risks in COVID-19 Via SmartWatch

Study Overview
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Brief Summary
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In December 2019, a new viral disease called COVID-19 emerged. It is caused by the new corona virus SARS-CoV-2. It was initially described in the chinese city of Wuhan. In the following months, the disease developed into a pandemic, which is currently an immense international challenge. So far, there is little scientific evidence on risk stratification, especially on the prognostic value of biomarkers (laboratory-chemical, clinical and digital) with regard to clinical deterioration of patients with COVID-19. Further scientific studies are needed to establish optimal risk stratification and early detection of clinical deterioration. In this study, the investigators aim to observe patients with COVID-19 via SmartWatches on top of their clinical routine. The investigators aim to determine, whether the addition of SmartWatches enhances risk stratification, early detection of complications and prognostics in patients with COVID-19, who have cardiovascular diseases or receive medication with arrhythmogenic risk.

Detailed Description
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In December 2019, a new viral disease called COVID-19 emerged. It is caused by the new corona virus SARS-CoV-2. It was initially described in the chinese city of Wuhan. In the following months, the disease developed into a pandemic, which is currently an immense international challenge. So far, there is little scientific evidence on risk stratification, especially on the prognostic value of biomarkers (laboratory-chemical, clinical and digital) with regard to clinical deterioration of patients with COVID-19. Further scientific studies are needed to establish optimal risk stratification and early detection of clinical deterioration. In this study, the investigators aim to observe patients with COVID-19 via SmartWatches on top of their clinical routine. The investigators aim to determine, whether the addition of SmartWatches enhances risk stratification, early detection of complications and prognostics in patients with COVID-19, who have cardiovascular diseases or receive medication with arrhythmogenic risk. The study is a monocentric observational study in the sense of a cohort study. 50 COVID-19 patients are aimed to be included. Patients are identified upon presentation at the COVID-19 outpatient clinic or during their stay at the COVID-19 ward at the Centre for Internal Medicine (Krehl-Klinik) at the Heidelberg University Hospital. Since many study-relevant data are routinely collected at presentation in the outpatient clinic or during the inpatient stay, these values are being accessed (e.g. anamnesis, physical examination, ECGs, CT and laboratory values) by our study team. The recruited subjects (n=50) receive medical care according to the instructions of the treating physicians. The treating physicians decide whether a home or inpatient quarantine is necessary and whether a specific therapy is required. SmartWatches are provided to all subjects on the day of recruitment. These are Apple Watches (Series 5). The patient is asked to record an ECG on the Apple Watch 5 times a day (8:00 am, 11:00 am, 2:00 pm, 5:00 pm, 8:00 pm). Furthermore, the activity of the patient is recorded via the App Health. The data collected by the Apple Watch (activity and health-related data of the App Health as well as ECGs) are accessible to the study team at any time, provided that the pseudonymised data transfer via Email has been successfully completed. In order to be able to use the Apple Watch, participants are provided with an iPhone by us. As soon as the COVID-19 disease is cured or the participant died, the study ends for them. However, the study will be conducted for at least 14 days for each patient, even if the patient has healed earlier. If findings relevant to the health of the patients should arise from the study-relevant data (for example the detection of cardiac arrhythmias via the Apple Watch), the investigators report these information to the treating physician and patient as soon as possible.

Official Title
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CoronaWatch - Early Detection of Cardiovascular Risks in COVID-19 Via SmartWatch

Conditions
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COVID-19

Intervention / Treatment
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* Device: Apple Watch Series 5


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Diagnosis of COVID-19 (detection by PCR) Age ≥ 18 The patient has understood the study design and the informed consent form and has signed and dated the informed consent form The patient has got a cardiovascular disease or therapy with potential cardiovascular complications

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| COVID-19<br>Patients with COVID-19, who have cardiovascular diseases or receive medication with arrhythmogenic risk. | Device: Apple Watch Series 5<br>* Digital monitoring via Apple Watch<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Biomarker | Identification of biomarkers (laboratory-chemical, clinical, digital) for risk stratification, early detection of complications and prognosis | 3 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Protective factors | Identification of laboratory-chemical, clinical or digitally measured protective factors, that indicate good prognosis | 3 months | 
| SmartWatch compliance | The amount of time is compared between participants regarding the wearing of a SmartWatch as a monitoring tool | 3 months | 
| Arrhythmias | Detection of an irregular heartbeat (PPG) as a sign of atrial or ventricular arrhythmias and correlation to intermittently recorded ECGs by SmartWatch | 3 months | 
| QT time changes | Detection of QT time changes (prolongation) in intermittently recorded ECGs by SmartWatch and correlation with clinical variables (change of medication, fever, etc.) | 3 months | 
| Longitudinal risk models | Application of artificial intelligence and machine learning techniques for longitudinal risk models by using collected data (e.g. metabolomics) | 3 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Apple Watch, COVID-19, Wearable, SmartWatch, Prognostics, Diagnostics, Risk stratification