Sterile body fluids infections: Profile of bacteria and their antimicrobial resistance pattern in a tertiary care hospital from Uttar Pradesh

Abstract

Infections of sterile body fluids are important and significant causes of mortality and morbidity, especially healthcare-associated infections. Species-level identification and antimicrobial resistance profile of bacteria are important determinants while selecting appropriate antimicrobials for empirical and targeted therapy. We conducted this study to observe the distribution of various bacteria and their antimicrobial resistance profile isolated from sterile body fluids. We conducted this study in a tertiary care teaching hospital from western Uttar Pradesh for a period of 2 years. All sterile body fluid samples were processed by conventional aerobic bacterial culture followed by their identification up to species level by conventional biochemicals following standard microbiological procedures. The antimicrobial susceptibility of the bacterial pathogens grown in culture was tested by Kirby–Bauer disk diffusion method and interpretation of susceptibility testing was done according to CLSI guidelines 2020. A total of 1980 sterile body fluid samples were collected during the study period and 192 samples were found positive on culture for bacterial pathogens. Gram-negative bacilli (GNB) were predominantly isolated comprising 83.33% in comparison to 16.67 % of Gram-positive cocci. Among Staphylococcus aureus isolates, 75% were methicillin-resistant S. aureus. All S. aureus isolates were sensitive against vancomycin and linezolid. Among GNB, 25% were extended-spectrum beta-lactamase producers while 62.5% were carbapenemase producers. All GNBs were sensitive to colistin. From this study, we concluded that the pathogenic bacteria implicated in infections of sterile body fluids are predominantly multidrug-resistant. There is a huge variation in data on the distribution of bacterial species isolated from sterile body fluids and their antimicrobial resistance patterns from different geographical locations and healthcare settings. Thus, data from a particular healthcare setting are important for empirical treatment in that healthcare setting.