5 Key Takeaways

• 1

  Pathnostics developed a machine-learning model to predict antibiotic susceptibility for urinary tract infections using PCR results and demographic data.

• 2

  The Guidance UTI predictive report aims to reduce empiric therapy and treatment failures by providing patient-specific probabilities for effective antibiotics.

• 3

  The model utilizes 20 algorithms, reporting only antibiotics with a predicted effectiveness probability above 60% to ensure clinical relevance.

• 4

  Initial results indicate the model's predictions align closely with phenotypic results for first-line and high-sensitivity antibiotics.

• 5

  Pathnostics plans to pilot the predictive model in 2026, aiming to enhance clinical decision-making for complex or recurrent UTIs.