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Application of the Intelligent High-Throughput Antimicrobial Sensitivity Testing/Phage Screening System and Lar Index of Antimicrobial Resistance
Published on: July 21, 2023
Hospital-Based Surveillance and Resistance Index Analysis of Antimicrobial Resistance Trends: A Three-Year Study from
Elnaz Vafadar Moradi1, Faeze Sadat Hoseini2, Seyed Mohammad Mousavi1
1Department of Emergency Medicine, Faculty of Medicine, Mashhad University of Medical Science, Mashhad, Iran.
Background:
Antimicrobial resistance (AMR) poses an escalating global health crisis, yet institution-level temporal analyses that integrate both resistance trends and composite indices remain scarce.
Methods:
We performed a three-year retrospective analysis (2021-2023) of all culture-positive bacterial isolates from a tertiary referral hospital in Iran. Antimicrobial susceptibility testing (AST) followed CLSI M02/M07/M100 standards. Annual resistance rates (%R) were calculated for six priority pathogens, and linear regression was used to model temporal changes (slopes, p-values). A composite Resistance Index (RI) was derived to capture cumulative resistance pressure.
Results:
Among 38,514 specimens, 3109 (8.1%) yielded bacterial growth. E. coli declined significantly (45.0%→29.7%, p=0.02), while A. baumannii increased (17.6%→26.8%, p=0.03). Regression analysis revealed pronounced upward resistance slopes in A. baumannii (eg, amikacin +8.6%/year, p<0.001; ciprofloxacin +8.0%/year, p<0.001) and K. pneumoniae to nalidixic acid (+17.6%/year, p<0.001). In contrast, significant declines were observed in S. aureus (trimethoprim-sulfamethoxazole -27.8%/year, p<0.001), Enterobacter spp. (ampicillin -42.5%/year, p<0.001), and carbapenem resistance in K. pneumoniae and P. aeruginosa. The RI highlighted persistently extreme resistance in A. baumannii (>90%) and high levels in P. aeruginosa (>70%), with moderate but variable indices in E. coli and K. pneumoniae (50-70%).
Conclusion:
This single-center study demonstrates shifting AMR epidemiology with A. baumannii emerging as the dominant multidrug-resistant threat, sustained high resistance in P. aeruginosa, and encouraging declines in certain resistance patterns among E. coli, K. pneumoniae, and S. aureus. By integrating slope-based trends with a composite RI, we provide a scalable framework to convert routine antibiogram data into actionable antimicrobial stewardship programs (ASPs) and infection prevention strategies.
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