Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients.

Journal: Scientific reports
Published Date: Feb 5, 2021

Abstract

Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and prognostic markers of disease progression and death. From a cohort of approx. 2.6 million citizens in Denmark, SARS-CoV-2 PCR tests were performed on subjects suspected for COVID-19 disease; 3944 cases had at least one positive test and were subjected to further analysis. SARS-CoV-2 positive cases from the United Kingdom Biobank was used for external validation. The ML models predicted the risk of death (Receiver Operation Characteristics-Area Under the Curve, ROC-AUC) of 0.906 at diagnosis, 0.818, at hospital admission and 0.721 at Intensive Care Unit (ICU) admission. Similar metrics were achieved for predicted risks of hospital and ICU admission and use of mechanical ventilation. Common risk factors, included age, body mass index and hypertension, although the top risk features shifted towards markers of shock and organ dysfunction in ICU patients. The external validation indicated fair predictive performance for mortality prediction, but suboptimal performance for predicting ICU admission. ML may be used to identify drivers of progression to more severe disease and for prognostication patients in patients with COVID-19. We provide access to an online risk calculator based on these findings.

Authors

  • Espen Jimenez-Solem
    Department of Clinical Pharmacology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.
  • Tonny S Petersen
    Department of Clinical Pharmacology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.
  • Casper Hansen
    Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
  • Christian Hansen
    Department of Simulation and Graphics, University of Magdeburg Universitätsplatz 2, Magdeburg, 39106 Germany.
  • Christina Lioma
    Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
  • Christian Igel
    Department of Computer Science, University of Copenhagen, Copenhagen Ø DK-2100, Denmark.
  • Wouter Boomsma
    Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
  • Oswin Krause
    Department of Computer Science, University of Copenhagen, Universitetsparken 5, Copenhagen 2100, Denmark.
  • Stephan Lorenzen
    Aiomic, Copenhagen, Denmark.
  • Raghavendra Selvan
    Department of Computer Science, University of Copenhagen, Denmark. Electronic address: raghav@di.ku.dk.
  • Janne Petersen
    Center for Clinical Research and Prevention, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.
  • Martin Erik Nyeland
    Department of Clinical Pharmacology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.
  • Mikkel Zöllner Ankarfeldt
    Center for Clinical Research and Prevention, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.
  • Gert Mehl Virenfeldt
    Center for Clinical Research and Prevention, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.
  • Matilde Winther-Jensen
    Center for Clinical Research and Prevention, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.
  • Allan Linneberg
    Center for Clinical Research and Prevention, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.
  • Mostafa Mehdipour Ghazi
    Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
  • Nicki Detlefsen
    Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
  • Andreas David Lauritzen
    Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
  • Abraham George Smith
    Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
  • Marleen de Bruijne
  • Bulat Ibragimov
    Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California, 94305, USA.
  • Jens Petersen
    Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany; Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Martin Lillholm
    Department of Computer Science, University of Copenhagen, Copenhagen Ø DK-2100, Denmark; Biomediq A/S, Copenhagen Ø DK-2100, Denmark.
  • Jon Middleton
    Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
  • Stine Hasling Mogensen
    Danish Medicines Agency, Copenhagen, Denmark.
  • Hans-Christian Thorsen-Meyer
    Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Intensive Care, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
  • Anders Perner
    Department of Intensive Care, Copenhagen University Hospital-Rigshospitalet, DK-2100 Copenhagen, Denmark.
  • Marie Helleberg
    Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.
  • Benjamin Skov Kaas-Hansen
    Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Clinical Pharmacology Unit, Zealand University Hospital, Roskilde, Denmark.
  • Mikkel Bonde
    Department of Organ Surgery and Transplantation, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.
  • Alexander Bonde
    Department of Organ Surgery and Transplantation, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.
  • Akshay Pai
    Department of Computer Science, University of Copenhagen, Copenhagen Ø DK-2100, Denmark; Biomediq A/S, Copenhagen Ø DK-2100, Denmark.
  • Mads Nielsen
    Department of Computer Science, University of Copenhagen, Copenhagen Ø DK-2100, Denmark; Biomediq A/S, Copenhagen Ø DK-2100, Denmark.
  • Martin Sillesen
    Department of Organ Surgery and Transplantation, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.

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