COVID-19
Conditions
Keywords
Telemedicine, COVID-19, wearable device, e-Health, Remote monitoring
Brief summary
The aim of the study is to provide clinical decision support to healthcare professionals using a wearable for non-invasive multimodal monitoring, allowing early detection of disease progression to severe forms, as well as the detection of significant clinical events. For the development of the study, 500 individuals with COVID-19 in home confinement will be randomly assigned to form part of the control group, which will be followed conventionally by Primary Care Professionals, or to the experimental group, which will also be provided with the wearable device for non-invasive multimodal monitoring linked to an App for transfering data. Furthermore, the patient will be able to interact with the application on three times daily by indicating the symptoms contemplated and answering the decision clinical questions. In this way, alarms can be generated in the presence of symptoms or significant alterations in the parameters monitored by the device, which the health professionals of the Primary Care teams included in the study will evaluate at the appropriate time, taking the best decision in each case.
Detailed description
As variables to be considered in order to compare the effectiveness of the system against the conventional monitoring protocol, complemented with real-time patient notification of symptoms, certain variables will be collected, such as: Baseline variables: * Age, sex, date of COVID-19 positive diagnosis (PCR or antigen test). * Stage of clinical progression of the disease: according to the Primary Care COVID-19 management * Information collected in the telephone clinical assessment questionnaire in the home follow-up of the patient with SARS-CoV-2 infection Variables generated by the study follow-up: * Vital signs covered by the Bakeey E66 smartwatch device: temperature, respiration rate (RR), heart rate (HR) and oxygen saturation (SatO2) * Clinical symptoms covered by the Home App for submission by the patient: cough, fever, chest pain, respiratory distress (dyspnoea), vomiting and diarrhoea.
Interventions
DEVICEClinical decision support system based on non-invasive multimodal monitoring
Non-invasive multimodal vital signs monitoring with the wearabl to monitor for a period of 10 days after the date of positive diagnosis to COVID-19. The device will be linked to the Home App, which will allow the sending of temperature, HR and RR data to the server every 15 minutes a day and the notification of symptoms by the patient three times a day.
Sponsors
Hospital Clínico Universitario de Valladolid
University of Valladolid
Sanidad de Castilla y León
Increase-Tech
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SUPPORTIVE_CARE
Masking
DOUBLE (Investigator, Outcomes Assessor)
Intervention model description
Single-blind, controlled, randomised clinical trial
Eligibility
Sex/Gender
ALL
Age
16 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Confirmed diagnosis of SARS-CoV-2 disease, detected by PCR or antigen test, performed 72 h prior to patient inclusion in the study. * Acceptance to sign the informed consent document. * Possession of a Smartphone or Tablet with Internet connection. * Possession of mental faculties to participate in the study.
Exclusion criteria
* Age below the age of health majority (16 years). * Lack of digital skills to use the Home App. * Cognitive impairment that prevents the patient from participating in the study. * Disabling pathology of the upper limb.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Evolution to severe progression of COVID-19 | One month after inclusion of patients in the study |
| Need for admission to ICU. | One month after inclusion of patients in the study |
| Mortality rate. | One month after inclusion of patients in the study |
Secondary
| Measure | Time frame |
|---|---|
| Need for invasive mechanical ventilation | One month after inclusion of patients in the study |
| Hospital admission rate | One month after inclusion of patients in the study |
| Economic cost of the care derived from the episode for the social and health care system. | One month after inclusion of patients in the study |
| Occurrence of major vascular events | One month after inclusion of patients in the study |
| Delay to hospital admission | One month after inclusion of patients in the study |
| Average hospital stay | One month after inclusion of patients in the study |
Countries
Spain
Outcome results
None listed