The goal of this observational study is to develop and validate an XAI based model that predicts HF events and identifies modifiable con-tributing factors, and to evaluate the added value of integrating high frequency smartwatch data compared to usual care in patients with heart failure. The main objectives of the study are: 1. To develop and validate an XAI based model that predicts HF events and identifies modifiable contributing factors, and to evaluate the added value of integrating high frequency smartwatch data compared to usual care. In the Netherlands usual care includes remote monitoring of heartrate, blood pressure, weight and symptoms. 2. To include insights of the smartwatch into activity patterns, impact on quality of life (KCCQ-12), and patient satisfaction with net promoter score (NPS). Participants will wear a smartwatch for six months and perform an I-lead ecg with the smartwatch weekly.
Study Type
OBSERVATIONAL
Enrollment
95
Medisch Spectrum Twente
Enschede, Netherlands
Heart failure (HF) event
HF event is defined as: * Increase in diuretic treatment * Increase in NYHA class * Hospitalization caused by HF * Death caused by HF
Time frame: From enrollment to the end of follow-up at 6 months
Activity patterns
Activity patterns measured with the smartwatch
Time frame: From enrollment to the end of follow-up at 6 months
Quality of life (QoL)
QoL measured with Kansas City Cardiomyopathy Questionnaire-12
Time frame: Measured at baseline and at the end of follow-up at 6 months. The Kansas City Cardiomyopathy Questionnaire is scored on a scale of 0 to 100; higher scores indicate better health.
Net promotor score
Net promotor score measures how likely patients are to recommend this technology to others. This score ranges from 0 to 10. Higher values indicate a greater likelihood of recommending to others.
Time frame: At the end of follow-up at 6 months
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