From microbiology to antimicrobial stewardship
How microbiological diagnosis, result interpretation, resistance surveillance, antimicrobial use and evaluation of clinical and economic outcomes fit together.
How microbiological diagnosis, result interpretation, resistance surveillance, antimicrobial use and evaluation of clinical and economic outcomes fit together.
EUCAST has published an updated assessment of whole-genome sequencing for predicting bacterial antimicrobial susceptibility. We examine how far genotype can replace phenotype today and why linking both types of data is increasingly important.
From random forests and convolutional neural networks to genomic language models: how machine learning is used to predict bacterial antimicrobial resistance, and why data remain the central challenge.
A review from CMAC (2025) compares WHO GLASS, CLSI M39, ESCMID, AMRcloud guidance and Russian MR 3.1.0346-24–highlighting key contradictions that matter for local antibiograms, data quality, and stewardship decisions.
How susceptibility testing accuracy, prescribing errors, and AMR diagnostics translate into measurable economic losses–and why even a 10% error rate can cost millions of rubles.