Identification of parameters and formulation of a statistical and machine learning model to identify Babesia canis infections in dogs using available ADVIA hematology analyzer data.

Journal: Parasites & vectors
Published Date:

Abstract

BACKGROUND: Canine babesiosis is an important tick-borne disease in endemic regions. One of the relevant subspecies in Europe is Babesia canis, and it can cause severe clinical signs such as hemolytic anemia. Apart from acute clinical symptoms dogs can also have a more chronic disease development or be asymptomatic carriers. Our objective was to identify readily available ADVIA hematology analyzer parameters suggestive of B. canis parasitemia in dogs and to formulate a predictive model.

Authors

  • Tera Pijnacker
    Department of Clinical Sciences, Utrecht University, Utrecht, The Netherlands. T.Pijnacker@uu.nl.
  • Richard Bartels
    Digital Health, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Martin van Leeuwen
    Department of Clinical Sciences, Utrecht University, Utrecht, The Netherlands.
  • Erik Teske
    Department of Clinical Sciences, Utrecht University, Utrecht, The Netherlands.