Molecular epidemiology of Carbapenemase-encoding genes and comparative evaluation of carbapenem MIC with genotypic carbapenem resistance in Klebsiella isolates from neonatal sepsis cases

Journal of Laboratory Physicians(2024)

引用 0|浏览0
暂无评分
摘要
Objectives: The objective of this study was to determine the molecular epidemiology of Carbapenemase-encoding genes in Klebsiella isolates from neonatal sepsis cases and comparative evaluation of carbapenem minimum inhibitory concentration (MIC) with genotypic carbapenem resistance. Materials and Methods: One hundred cases of neonatal sepsis with blood cultures positive for Klebsiella spp. were included in the study. MIC for imipenem and meropenem was determined by Epsilometer-test. Antimicrobial susceptibility testing (AST) was performed by modified Kirby Bauer disc diffusion method. All the isolates of Klebsiella spp. were tested for the presence of beta-lactamase Klebsiella pneumoniae carbapenemase (blaKPC ), beta-lactamase New Delhi metalloβ-lactamase-1(blaNDM-1), beta-lactamase imipenemase (blaIMP), beta-lactamase Verona imipenemas e (blaVIM) genes by multiplex polymerase chain reaction (PCR) and uniplex PCR for beta-lactamase oxacillinase-48 (blaOXA-48). Comparison of individual antibiotic susceptibility between carbapenemase-encoding gene positive and negative Klebsiella spp. isolates was performed. Statistical analysis: Statistical analysis was done using the Fisher’s exact test. P < 0.05 was considered significant. Results: The prevalence of carbapenemase-encoding genes in Klebsiella spp. was 16%. Most predominant carbapenemase-encoding gene was blaOXA-48 gene (12%) followed by blaNDM-1 gene (6%). Coexpression of both blaOXA-48 and blaNDM-1 was observed in 2% of isolates. All the Klebsiella spp. isolates harboring the carbapenemases gene (100%) had resistant MIC values for Meropenem, whereas, for imipenem, only 75% of isolates had resistant MIC values. Conclusions: Determination of prevalence of carbapenemase-encoding genes is of paramount importance in the development of effective antibiotic policies at various levels.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要