Colonization With Levofloxacin-resistant Extended-spectrum β-Lactamase-producing Enterobacteriaceae and Risk of...

Bacteremia caused by extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae (ESBL-E) is associated with inadequate empirical therapy and substantial mortality in neutropenic patients. Strategies are needed to identify neutropenic patients at high risk of these infections.

From April 2014 to September 2016, we collected perianal swabs, both at admission and weekly thereafter, from patients undergoing hematopoietic stem cell transplantation (HSCT). Patients received prophylactic levofloxacin while neutropenic. Swabs were plated onto selective agar, colonies were identified and underwent antimicrobial susceptibility testing, and phenotypic ESBL testing and polymerase chain reaction for β-lactamase genes were performed on ceftriaxone-resistant Enterobacteriaceae. We then determined the prevalence of pre-transplant ESBL-E colonization and risk of ESBL-E bacteremia. Colonizing and bloodstream isolates from patients with ESBL-E bacteremia underwent multilocus sequence typing and pulsed-field gel electrophoresis.

We analyzed 312 patients, including 212 allogeneic and 100 autologous HSCT recipients. Ten percent (31/312) of patients had pre-transplant ESBL-E colonization. Susceptibility rates of colonizing ESBL-E were: levofloxacin, 25%; cefepime, 9%; piperacillin-tazobactam, 84%; and meropenem, 97%. Of 31 patients colonized with ESBL-E pre-transplant, 10 (32%) developed ESBL-E bacteremia during their transplant admission, compared to 1 (0.4%) of 281 patients not colonized with ESBL-E (P < .001). All bloodstream ESBL-E were levofloxacin-resistant and colonizing and bloodstream isolates from individual patients had identical genotypic profiles.

HSCT recipients who are colonized with levofloxacin-resistant ESBL-E pre-transplant and receive levofloxacin prophylaxis have high rates of bacteremia from their colonizing strain during neutropenia. Assessing for ESBL-E colonization in neutropenic patients could lead to optimization of empirical antibacterial therapy.