Vanessa Escolar, Cardiology Department, School of Medicine, Basurto University Hospital, Bilbao, San Sebastián, Spain
Ainara Lozano, Cardiology Department, School of Medicine, Basurto University Hospital, Bilbao, San Sebastián, Spain
Nekane Larburu, Biomedical Department, Vicomtech Research and Technological Center, Donostia, San Sebastián, Spain
Jon Kerexeta, Biomedical Department, Vicomtech Research and Technological Center, Donostia, San Sebastián, Spain
Roberto Álvarez, Biomedical Department, Vicomtech Research and Technological Center, Donostia, San Sebastián, Spain
Amaia Echebarria, Cardiology Department, School of Medicine, Basurto University Hospital, Bilbao, San Sebastián, Spain
Alberto Azcona, Cardiology Department, School of Medicine, Basurto University Hospital, Bilbao, San Sebastián, Spain


Introduction: Heart failure (HF) is a major concern in public health. We have used artificial intelligence to analyze information and improve patient outcomes. Method: An Observational, retrospective, and non-randomized study with patients enrolled in our telemonitoring program (May 2014-February 2018). We collected patients’ clinical data, telemonitoring transmissions, and HF decompensations. Results: A total of 240 patients were enrolled with a follow-up of 13.44 ± 8.65 months. During this interval, 527 HF decompensations in 148 different patients were detected. Significant weight increases, desaturation below 90% and perception of clinical worsening are good predictors of HF decompensation. We have built a predictive model applying machine learning (ML) techniques, obtaining the best results with the combination of “Weight + Ankle + well-being plus alerts of systolic and diastolic blood pressure, oxygen saturation, and heart rate.” Conclusions: ML techniques are useful tools for the analysis of HF datasets and the creation of predictive models that improve the accuracy of the actual remote patient telemonitoring programs.



Keywords: Heart failure decompensations. Hospital admissions. Remote patient telemonitoring. Artificial intelligence. Machine learning. Predictive models.