Optimization of Antimicrobial Use for Sepsis in Calves: Bayesian Evaluation of Existing and Novel Sepsis Scores

Early recognition and rapid appropriate antimicrobial treatment is essential for survival of sepsis. To date, it is unclear which sepsis score should be used for an early diagnosis in calves. The objective of this study was to evaluate two existing scores (Trefz and Fecteau), three novel calf sepsis screening models (CSS, CSS_A, CSS_B), and blood culture as diagnostic test for sepsis, using Bayesian latent class evaluation. A total of 131 sick calves were included in this study. Sepsis prevalence was 45%, 27%, 56%, 47%, and 55%, when using the Trefz score, Fecteau score, CSS, CSS_A, and CSS_B, respectively, and 22% had a relevant positive blood culture. The newly established models CSS (including ≥2 SIRS-criteria and abnormal mental state) and CSS_B (alternative model CSS for practice, substituting abnormal leukocyte count with mucosae) had the highest sensitivity, with 86% and 84%, respectively, and could be interesting screening tests for sepsis. Sensitivity of the existing Trefz and Fecteau score was 70% and 35-39%, respectively. The presented new sepsis scoring systems have potential as screening tests to identify calves at risk, after which a calf-side diagnostic test is advised to confirm the diagnosis. Its use might aid in the rationalization of antimicrobial use in critically ill calves.