Assessment of Susceptibility of Methicillin-Resistant Staphylococcus aureus Isolates to Ceftaroline and Other Antistaphylococcal Agents

Introduction Methicillin-resistant Staphylococcus aureus (MRSA) remains a major cause of healthcare-associated infections and is associated with limited treatment options owing to its widespread antimicrobial resistance. This study aimed to evaluate the in vitro susceptibility of clinical MRSA isolates to ceftaroline and determine susceptibility patterns across demographic and clinical variables. Methods This cross-sectional observational study included 250 non-duplicate clinical MRSA isolates obtained from various clinical specimens. Antimicrobial susceptibility testing was performed in accordance with the guidelines of the Clinical and Laboratory Standards Institute (CLSI) guidelines. Demographic and microbiological data were analyzed using descriptive statistics, Pearson’s chi-square test or Fisher's exact test, and Cramer's V effect-size measures. Pairwise comparisons between ceftaroline and each comparator antibiotic were conducted using McNemar's test. Results Among the 250 MRSA isolates, 158 (63.2%) were recovered from male patients and 92 (36.8%) from female patients. Overall, 212 (84.8%) isolates were susceptible to ceftaroline, 36 (14.4%) demonstrated intermediate susceptibility, and two (0.8%) were resistant. Ceftaroline susceptibility remained consistent across sexes (p=0.847), ages (p=0.312), hospital departments (p=0.862), and specimen types (p=0.931). Vancomycin showed 100% susceptibility, whereas linezolid showed 98.8% susceptibility. Complete resistance to several β-lactam antibiotics was observed. Conclusion Ceftaroline demonstrated substantial in vitro activity against clinical MRSA isolates, and remained effective across diverse demographic and clinical subgroups. These findings support its potential role as an additional therapeutic option for MRSA infections and highlight the importance of continued antimicrobial surveillance and susceptibility-guided therapy to monitor the emerging resistance patterns.