Phenotype clustering of hospitalized high-risk patients with COVID-19 - a machine learning approach within the multicentre, multinational PCHF-COVICAV registry.

Journal: Cardiology journal
Published Date: Jun 4, 2024

Abstract

IMTRODUCTION: The high-risk population of patients with cardiovascular (CV) disease or risk factors (RF) suffering from COVID-19 is heterogeneous. Several predictors for impaired prognosis have been identified. However, with machine learning (ML) approaches, certain phenotypes may be confined to classify the affected population and to predict outcome. This study aimed to phenotype patients using unsupervised ML technique within the International Postgraduate Course Heart Failure Registry for patients hospitalized with COVID-19 and Cardiovascular disease and/or RF (PCHF-COVICAV).

Authors

  • Mateusz Sokolski
    Wroclaw Medical University, Faculty of Medicine, Institute of Heart Diseases, Wroclaw, Poland and Intitute of Heart Diseases, University Hospital, Wroclaw, Poland. matsok@gmail.com.
  • Sander Trenson
    Department of Cardiology, Sint-Jan Hospital Bruges, Bruges, Belgium.
  • Konrad Reszka
    Wroclaw Medical University, Faculty of Medicine, Institute of Heart Diseases, Wroclaw, Poland and Intitute of Heart Diseases, University Hospital, Wroclaw, Poland.
  • Szymon Urban
    Wroclaw Medical University, Faculty of Medicine, Institute of Heart Diseases, Wroclaw, Poland and Intitute of Heart Diseases, University Hospital, Wroclaw, Poland.
  • Justyna M Sokolska
    Wroclaw Medical University, Faculty of Medicine, Institute of Heart Diseases, Wroclaw, Poland and Intitute of Heart Diseases, University Hospital, Wroclaw, Poland.
  • Tor Biering-Sørensen
    Brigham and Women's Hospital, Boston, MA, USA.
  • Mats C Højbjerg Lassen
    Department of Cardiology, Copenhagen University Hospital - Herlev & Gentofte, Copenhagen, Denmark.
  • Kristoffer Grundtvig Skaarup
    Department of Cardiology, Copenhagen University Hospital - Herlev & Gentofte, Copenhagen, Denmark.
  • Carmen Basic
    Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • Zacharias Mandalenakis
    Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • Klemens Ablasser
    Division of Cardiology, Medical University of Graz, Austria.
  • Peter P Rainer
    Medical University of Graz, Graz, Austria.
  • Markus Wallner
    Temple University School of Medicine, Cardiovascular Research Center, Department of Physiology, Philadelphia, PA 19140, USA.
  • Valentina A Rossi
    Department of Cardiology, University Heart Center, University Hospital, Zurich, Switzerland.
  • Marzia Lilliu
    Division of Infectious Diseases, Azienda ULSS 9, M. Magalini Hospital, Villafranca di Verona, Verona, Italy.
  • Goran Loncar
    Department of Cardiology, Institute for Cardiovascular Diseases Dedinje (ICVDD), Belgrade, Serbia.
  • Huseyin A Cakmak
    Department of Cardiology, Mustafakemalpasa State Hospital, Bursa, Türkiye.
  • Frank Ruschitzka
    Acute Cardiac Care, Andreas Grüntzig Heart Catheterization Laboratories, Department of Cardiology, University Heart Center, University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091, Zurich, Switzerland.
  • Andreas J Flammer
    Department of Cardiology, University Heart Center, University Hospital, Zurich, Switzerland.

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