Tracking the Invisible War: Automated Profiling of Multidrug-Resistant Pathogens in a Tertiary Care Teaching Hospital in Central India

  • Mohod S
  • Gedam D
  • Rajan A
  • et al.
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Abstract

Background Automated systems such as VITEK 2 Compact have revolutionized microbial diagnostics by offering rapid identification and antimicrobial susceptibility testing (AST). This study aimed to evaluate the spectrum of bacterial and fungal isolates and their resistance profiles using the VITEK 2 system. Material and methods A retrospective cross-sectional analysis was conducted over one year (January 2024 to December 2024) in the Department of Microbiology of a tertiary care hospital in Central India. The present study included only those clinical specimens that were initially processed using conventional methods but proved difficult to identify based on biochemical reactions alone. These included blood, sputum, wound swab, pus, cervicovaginal swab, endotracheal aspirate, pleural fluid, bronchoalveolar lavage, stool, corneal scraping, and cerebrospinal fluid. Such samples were subsequently subjected to identification by the VITEK 2 Compact system to ensure rapid and accurate results. The resistance patterns of Gram-negative organisms including Enterobacterales and non-fermenters, gram-positive cocci, and yeasts were analyzed. These findings were entered into the Microsoft Excel Version 2010. Statistical analysis was carried out using SPSS Version 20 for Windows package (IBM Corp., Armonk, NY, USA). Observed association of multidrug resistant (MDR) isolates from ICU with observed multidrug resistance from non-ICU was tested by calculating the p-value using the chi-square test (p-value of 0.00055, i.e.,p < 0.05 was considered significant). Results Out of 284 isolates, Klebsiella pneumoniae 35 (12%), Pseudomonas aeruginosa 24 (8%), Staphylococcus aureus 33 (11%), and Candida albicans 14 (5%) were predominant. Isolated organisms were found more in the ICU, 195 (69%), than non-ICU, 89 (31%), setting. The proportion of MDRisolates is significantly higher in the ICU (92.82%, 181/195) compared to the non-ICU setting (78.65%, 70/89). High resistance was noted among Enterobacterales against beta-lactams (100%) and fluoroquinolones (87.5%). Non-fermenters such as Acinetobacter baumannii showed 100% resistance to multiple drugs, indicating pan-drug resistance in some strains. Among gram-positive organisms, penicillin, erythromycin, levofloxacin, ciprofloxacin, and chloramphenicol were tested for Enterococcus faecalis. Enterococcus faecalis showed 100% resistance to penicillin, erythromycin, and chloramphenicol. Yeasts exhibited varied resistance, with Candida tropicalis and Cryptococcus laurentii showing higher resistance to fluconazole, 4 (57%) and 1 (100%), respectively. Conclusion The study reveals a significant rising occurrence of multidrug-resistant organisms, particularly in critical care areas. The VITEK 2 Compact system enabled rapid and precise identification of resistance profiles, including rare and highly resistant strains. Its use is crucial for timely, targeted therapy and reinforces the need for robust diagnostic and antimicrobial stewardship practices.

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Mohod, S. V., Gedam, D. S., Rajan, A. L., Khadse, R. K., & John, R. (2025). Tracking the Invisible War: Automated Profiling of Multidrug-Resistant Pathogens in a Tertiary Care Teaching Hospital in Central India. Cureus. https://doi.org/10.7759/cureus.85778

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