Hospital-Based Surveillance and Resistance Index Analysis of Antimicrobial Resistance Trends: A Three-Year Study from a Tertiary Hospital in Iran (2021–2023)

Elnaz Vafadar Moradi,1 Faeze Sadat Hoseini,2 Seyed Mohammad Mousavi,1 Seyed Reza Ahmadi Koupaei,1 Abbas Izadi,3 Davood Soroosh,4 Mohammad Sadegh Damavandi5,6 1Department of Emergency Medicine, Faculty of Medicine, Mashhad University of Medical Science, Mashhad, Iran; 2Faculty of Medicine, Mashhad University of Medical Science, Mashhad, Iran; 3Department of Management Sciences and Health Economics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran; 4Department of Forensic Medicine, Faculty of Medicine, Shahid Hasheminejad Hospital, Mashhad University of Medical Sciences, Mashhad, Iran; 5Antimicrobial Resistance Research Center, Basic Sciences Research Institute, Mashhad University of Medical Sciences, Mashhad, Iran; 6Department of Microbiology and Virology, Faculty of Medicine, Shahid Hasheminejad Hospital, Mashhad University of Medical Sciences, Mashhad, IranCorrespondence: Mohammad Sadegh Damavandi, Antimicrobial Resistance Research Center, Basic Sciences Research Institute, Mashhad University of Medical Sciences, Mashhad, Iran, Email [email protected]: 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.Keywords: antimicrobial resistance, temporal trends, resistance index, hospital stewardship, infection prevention and control