External validation of predictive models for antibiotic susceptibility of urine culture.

Journal: BJU international
PMID: 39710428

Abstract

OBJECTIVE: To develop, externally validate, and test a series of computer algorithms to accurately predict antibiotic susceptibility test (AST) results at the time of clinical diagnosis, up to 3 days before standard urine culture results become available, with the goal of improving antibiotic stewardship and patient outcomes.

Authors

  • Glenn T Werneburg
    Department of Urology, Glickman Urological and Kidney Institute, Cleveland Clinic Foundation, Cleveland, OH, USA; Department of Urology, University of Michigan, Ann Arbor, MI, USA. Electronic address: wernebg@ccf.org.
  • Daniel D Rhoads
    Department of Pathology, Case Western Reserve University, Cleveland, Ohio, USA daniel.rhoads@case.edu.
  • Alex Milinovich
    Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH.
  • Sean McSweeney
    ESRF, 6 Rue Jules Horowitz, 38000 Grenoble, France.
  • Jacob Knorr
    Department of Urology, Glickman Urological Institute, Cleveland Clinic Foundation, Cleveland, OH, USA.
  • Lyla Mourany
    Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
  • Alex Zajichek
    Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH.
  • Howard B Goldman
  • Georges-Pascal Haber
    Cleveland Clinic Foundation, Cleveland, OH.
  • Sandip P Vasavada
    Department of Urology, Glickman Urological and Kidney Institute, Cleveland Clinic Foundation, Cleveland, OH, USA. Electronic address: vasavas@ccf.org.

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