Using machine learning to improve the diagnostic accuracy of the modified Duke/ESC 2015 criteria in patients with suspected prosthetic valve endocarditis - a proof of concept study.

Journal: European journal of nuclear medicine and molecular imaging
PMID: 38904778

Abstract

INTRODUCTION: Prosthetic valve endocarditis (PVE) is a serious complication of prosthetic valve implantation, with an estimated yearly incidence of at least 0.4-1.0%. The Duke criteria and subsequent modifications have been developed as a diagnostic framework for infective endocarditis (IE) in clinical studies. However, their sensitivity and specificity are limited, especially for PVE. Furthermore, their most recent versions (ESC2015 and ESC2023) include advanced imaging modalities, e.g., cardiac CTA and [F]FDG PET/CT as major criteria. However, despite these significant changes, the weighing system using major and minor criteria has remained unchanged. This may have introduced bias to the diagnostic set of criteria. Here, we aimed to evaluate and improve the predictive value of the modified Duke/ESC 2015 (MDE2015) criteria by using machine learning algorithms.

Authors

  • D Ten Hove
    Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Medical Microbiology & Infection Prevention, Hanzeplein 1, Groningen, 9713 GZ, The Netherlands. d.ten.hove@umcg.nl.
  • R H J A Slart
    Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Medical Microbiology & Infection Prevention, Hanzeplein 1, Groningen, 9713 GZ, The Netherlands.
  • A W J M Glaudemans
    Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Medical Microbiology & Infection Prevention, Hanzeplein 1, Groningen, 9713 GZ, The Netherlands.
  • D F Postma
    Department of Internal Medicine and Infectious Diseases, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
  • A Gomes
    Department of Medical Microbiology and Infection Prevention, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
  • L E Swart
    Department of Cardiology, Spaarne Gasthuis, Haarlem, The Netherlands.
  • W Tanis
    Department of Cardiology, HagaZiekenhuis, The Hague, The Netherlands.
  • P P van Geel
    Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
  • G Mecozzi
    Department of Cardiothoracic Surgery, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
  • R P J Budde
    Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands.
  • K Mouridsen
    Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Medical Microbiology & Infection Prevention, Hanzeplein 1, Groningen, 9713 GZ, The Netherlands.
  • B Sinha
    University of Groningen, University Medical Center Groningen, Department of Medical Microbiology and Infection Prevention, Groningen, the Netherlands.

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