The Role of Automation for Early Diagnosis of Non-fermenter Superbugs in Critically Ill Septicemic Hospitalized Patients

Abstract

Introduction Non-fermenting Gram-negative bacilli (NFGNB) are emerging superbugs of bloodstream infections (BSI), causing increased mortality in hospitalized patients. NFGNB are challenging to identify using conventional identification techniques. Hence, automation is beneficial for accurate and fast diagnosis; it also facilitates rapid treatment and recovery of patients. This study aims to isolate/identify NFGNB from BSI and determine its antimicrobial susceptibility pattern. Material and methods This study was conducted in the Department of Microbiology, LLRMMC, Meerut, for a period of six months (June to November 2022). The samples were processed using automated blood culture (BD BACTEC) and an identification/sensitivity testing system (BD Phoenix). Results Out of 1340 blood cultures, 347 (25.7%) were flagged positive for microbial growth. A total of 103 (7.6%) NFGNB were isolated, showing their strong association with BSI. The NFGNB isolates were Pseudomonas species 23 (22.3%), Acinetobacter baumannii 19 (18.4%), Salmonella spp. 19 (18.4%), Sphingomonas paucimobilis 17 (16.5%), Aeromonas hydrophila 5 (4.8%), Rhizobium radiobacter sp. 4 (3.8%), Stenotrophomonas maltophila 3 (2.9%), Burkholderia cepacian 3 (2.9%), Proteus mirabilis 2 (1.9%), Achromobacter xylosoxidans 2 (1.9%), Elizabethkingia meningoseptica 2 (1.9%), Ochromobacter anthropic 2 (1.9%), Cuprivadus pauculus 1 (0.9%), and Ralstonia mannitolilytica 1 (0.9%). Conclusions Automation helps in the prompt reporting of NFGNB and their antibiogram pattern by microbiology laboratories, facilitating the early and accurate management of patients with BSI.