Emulation of a Target Trial to Estimate the Effect of Selective Serotonin Reuptake Inhibitors on the Development of Antimicrobial-Resistant Infections using Electronic Health Record Data and Causal Machine Learning

Abstract

Antimicrobial resistance is a significant public health concern. The use of selective serotonin reuptake inhibitors (SSRIs), medications commonly prescribed to treat depression, anxiety, and other psychiatric disorders, is increasing. Previous in vitro studies have shown that bacteria can become resistant to antibiotics when exposed to SSRIs. In this study, we emulated a target trial to estimate the effect of SSRI usage on the incidence of antibiotic-resistant infection. Our study population consisted of patients with mood, anxiety, or stress-related disorders, and a record of previous antimicrobial susceptibility testing or diagnosis of bacterial infection. Univariable, multivariable survival regression, and causal survival forest analyses all showed that patients treated with SSRIs had a higher risk of developing an antibiotic-resistant infection than those not treated with SSRIs. This study confirms the in vitro findings and may provide insights for future studies exploring the relationship of treatment with SSRIs and subsequent antibiotic-resistant infection.