Using data from thousands of patients with wound infections and urinary tract infections, researchers in Science built a new machine learning approach that can predict and minimize risk of treatment-induced antibiotic resistance.
A serious infection may initially be diagnosed as antibiotic susceptible but subsequently become drug resistant—and life threatening. Rather than de novo resistance mutation occurring, it is more likely that a resistant strain or species persisting in the patient’s gut or skin replaced the susceptible strain. From this starting point, Stracy.
—CATreatment of bacterial infections currently focuses on choosing an antibiotic that matches a pathogen’s susceptibility, with less attention paid to the risk that even susceptibility-matched treatments can fail as a result of resistance emerging in response to treatment.
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