In vitro Bactericidal Activities of Combination Antibiotic Therapies Against Carbapenem-Resistant Klebsiella pneumoniae With Different Carbapenemases and Sequence Types

Carbapenem-resistant (CRKP) is becoming increasingly problematic due to the limited effectiveness of new antimicrobials or other factors such as treatment cost. Thus, combination therapy remains a suitable treatment option. We aimed to evaluate the bactericidal activity of various antibiotic combinations against CRKP with different carbapenemase genotypes and sequence types (STs). Thirty-seven CRKP with various STs and carbapenemases were exposed to 11 antibiotic combinations (polymyxin B or tigecycline in combination with β-lactams including aztreonam, cefepime, piperacillin/tazobactam, doripenem, meropenem, and polymyxin B with tigecycline) in static time-kill studies (TKS) using clinically achievable concentrations. Out of the 407 isolate-combination pairs, only 146 (35.8%) were bactericidal (≥3 log CFU/mL decrease from initial inoculum). Polymyxin B in combination with doripenem, meropenem, or cefepime was the most active, each demonstrating bactericidal activity in 27, 24, and 24 out of 37 isolates, respectively. Tigecycline in combination with β-lactams was rarely bactericidal. Aside from the lower frequency of bactericidal activity in the dual-carbapenemase producers, there was no apparent difference in combination activity among the strains with other carbapenemase types. In addition, bactericidal combinations were varied even in strains with similar STs, carbapenemases, and other genomic characteristics. Our findings demonstrate that the bactericidal activity of antibiotic combinations is highly strain-specific likely owing to the complex interplay of carbapenem-resistance mechanisms, i.e., carbapenemase genotype alone cannot predict bactericidal activity. The availability of WGS information can help rationalize the activity of certain combinations. Further studies should explore the use of genomic markers with phenotypic information to predict combination activity.