At a glance
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Observational Study for the Improvement of a Digital Health Platform for Remote Monitoring of Patients With Heart Failure
In Brief
An observational study evaluating Telemonitoring for Heart Failure. Completed, enrolled 154 participants across 7 sites in 2 countries.
Detailed Summary
In the present project, we propose to run an observational study in order to create a huge dataset with telemonitoring data from heart failure (HF) patients. The dataset will contain physiological measurements, socio-demographic data, risk factor information, medication tracking, symptomatology, clinical events and health-related questionnaire answers from each patient. Furthermore, health-related alarms will be delivered to the medical professionals whenever a measure from a patient is out of a predefined clinical range. These alarms and its defined level of relevance (indicated by the medical professionals) will also be Included in the dataset. With the annotated dataset we will be able to implement and train Machine Learning (ML) models that will improve the alarm-based system by making it more robust, trustworthy and reliable.
Study Details
Timeline
Interventions
All patients will be telemonitored in order to create a labeled and diverse dataset that will include the following data: Physiological parameters (measured periodically), socio-demographic data, risk factors, medication tracking, symptomatology questionnaire for patients, NYHA-class, clinical interventions, health questionnaire answers, classified alarms with their respective timestamp and annotation by the MD, and measurement ranges for each personalized alarm and their changes