Impact of empiric antibiotics on risk of -a causal inference observational analysis.

BACKGROUND

infection (CDI) is a common and often nosocomial infection associated with increased mortality and morbidity. Antibiotic use is the most important modifiable risk factor, but many patients require empiric antibiotics. We estimated the increased risk of hospital-onset CDI with one daily dose-equivalent (DDE) of various empiric antibiotics compared to management without that daily dose-equivalent.

METHODS

Using a multicenter retrospective cohort of adults admitted between March 2, 2020 and February 11, 2021 for the treatment of SARS-CoV-2, we used a series of three-level logistic regression models to estimate the probability of receiving each of several antibiotics of interest. For each antibiotic, we then limited our data set to patient-days at intermediate probability of receipt and used augmented inverse-probability weighted models to estimate the average treatment effect of one daily dose-equivalent, compared to management without that daily dose-equivalent, on the probability of hospital-onset CDI.

RESULTS

In 24,406 patient-days at intermediate probability of receipt, parenteral vancomycin increased risk of hospital-onset CDI, with an average treatment effect of 0.0096 cases per daily dose-equivalent (95% CI: 0.0053-0.0138). In 38,003 patient-days at intermediate probability of receipt, cefepime also increased subsequent CDI risk, with an estimated effect of 0.0074 more cases per daily dose-equivalent (95% CI: 0.0022-0.0126).

CONCLUSIONS

Among common empiric antibiotics, parenteral vancomycin and cefepime appeared to increase risk of hospital-onset CDI. Causal inference observational study designs can be used to estimate patient-level harms of interventions such as empiric antimicrobials.