Staphylococcus aureus is a Gram-positive coccus and a major human pathogen responsible for a broad spectrum of infections, ranging from superficial skin and soft-tissue infections to life-threatening bacteremia, endocarditis, pneumonia, and septic arthritis [1]. In the hospital setting, it consistently ranks among the most frequently isolated pathogens from blood cultures, surgical wounds, and intensive care unit (ICU) patients globally [2].

The landmark emergence of methicillin-resistant S. aureus (MRSA) following the introduction of methicillin in the 1960s marked a turning point in clinical microbiology. MRSA strains carry the mecA gene (or its homolog mecC), which encodes the penicillin-binding protein PBP2a — a modified transpeptidase with low affinity for all β-lactam antibiotics, conferring broad resistance to the entire class [3]. This single genetic acquisition typically co-occurs with resistance determinants for aminoglycosides, fluoroquinolones, and macrolides, yielding multidrug-resistant (MDR) phenotypes that are exceedingly difficult to treat [4].

The global burden of MRSA is substantial. The WHO has classified MRSA as a high-priority pathogen, and estimates attribute over 100,000 deaths annually to MRSA bloodstream infections in Europe alone [5]. In tertiary care settings, MRSA prevalence can exceed 50%, and the economic burden — from prolonged hospitalization, increased antibiotic costs, and higher mortality — is immense [6]. Healthcare-associated MRSA (HA-MRSA) strains are historically distinct from community-associated MRSA (CA-MRSA), differing in their clonal lineages (e.g., ST239, ST5 for HA-MRSA vs. ST8, ST30 for CA-MRSA), virulence factors, and resistance profiles, though the boundaries have become increasingly blurred [7].

Beyond methicillin resistance, the emergence of MDR and extensively drug-resistant (XDR) S. aureus strains poses a critical therapeutic challenge. Vancomycin has served as the cornerstone of MRSA therapy for decades; however, reduced vancomycin susceptibility — manifested as vancomycin-intermediate S. aureus (VISA) and heterogeneous VISA (hVISA) — has been increasingly reported [8]. Alternative agents such as daptomycin, linezolid, tedizolid, and ceftaroline are now in clinical use, but resistance to these agents, though currently uncommon, has emerged in clinical settings [9].

Local surveillance data are indispensable for guiding empiric antibiotic therapy, refining hospital infection control policies, and monitoring temporal trends in resistance. Without institution-specific antibiograms, clinicians risk either under-treating serious infections or over-utilizing broad-spectrum agents — both of which drive resistance further [10]. Despite this recognized need, comprehensive, methodologically rigorous local surveillance studies remain scarce in many middle- and low-income countries.

This study aimed to determine the prevalence of MRSA among clinical S. aureus isolates in a tertiary care hospital, characterize their antibiotic resistance profiles across multiple drug classes, identify multidrug-resistant and extensively drug-resistant phenotypes, and evaluate patient-level factors associated with MRSA acquisition.

2.1 Study Design and Setting A cross-sectional, laboratory-based study was conducted at a 600-bed tertiary care university hospital over a period of 1 year. The hospital serves as a regional referral center, comprising general medicine, surgery, cardiology, oncology, neurology, and a 30-bed mixed medical-surgical ICU. 2.2 Bacterial Isolates S. aureus isolates were collected from clinical specimens submitted to the clinical microbiology laboratory as part of routine patient care. These included blood cultures, wound swabs, tracheal aspirates, urine specimens, and catheter tips. One isolate per patient per admission was included to avoid duplication. Environmental isolates and isolates from outpatient specimens were excluded. All isolates were stored at −80°C in tryptic soy broth supplemented with 15% glycerol until further analysis. 2.3 Species Identification and MRSA Detection Isolates were identified to the species level using MALDI-TOF mass spectrometry (Bruker Biotyper, Bremen, Germany), with a score ≥2.0 accepted for species-level identification. MRSA status was confirmed by the presence of the mecA gene using a validated multiplex PCR assay, with nuc gene amplification serving as an internal S. aureus-specific control [11]. Phenotypic confirmation was performed using cefoxitin disk diffusion (30 µg) per CLSI 2020 criteria, with zones of ≤21 mm interpreted as MRSA. 2.4 Antimicrobial Susceptibility Testing Antimicrobial susceptibility was tested for 11 antibiotics across 7 drug classes using the Kirby-Bauer disk diffusion method on Mueller-Hinton agar (Oxoid, UK), supplemented by broth microdilution for minimum inhibitory concentration (MIC) determination using the TREK Sensititre system (Thermo Fisher Scientific). Antibiotics tested included oxacillin, ciprofloxacin, erythromycin, clindamycin, tetracycline, co-trimoxazole, rifampicin, linezolid, vancomycin, and daptomycin. All results were interpreted per Clinical and Laboratory Standards Institute (CLSI) M100-ED33 breakpoints [12]. Multidrug resistance (MDR) was defined as non-susceptibility to ≥1 agent in ≥3 antimicrobial categories. Extensive drug resistance (XDR) was defined as non-susceptibility to ≥1 agent in all but ≤2 categories, per the Magiorakos et al. (2012) consensus definitions [13]. Quality control was performed using S. aureus ATCC 29213 for susceptibility testing. 2.5 Data Collection Patient demographic and clinical data — including age, sex, ward of admission, ICU stay, prior antibiotic use within 90 days, comorbidities, length of hospital stay, and clinical outcome — were extracted from the electronic medical record system by two trained research associates, blinded to microbiological results. 2.6 Statistical Analysis Data were analyzed using SPSS Statistics v28 (IBM, Armonk, NY). Continuous variables were expressed as mean ± standard deviation (SD) and compared using the independent samples t-test. Categorical variables were expressed as frequencies and percentages and compared using Pearson's chi-square test or Fisher's exact test as appropriate. A p-value <0.05 was considered statistically significant. Logistic regression was performed to identify independent predictors of MRSA acquisition, with results expressed as odds ratios (OR) and 95% confidence intervals (CI).

3.1 Study Population and Isolate Distribution

A total of 200 non-duplicate S. aureus isolates were collected from 200 patients during the 24-month study period. The majority were obtained from wound cultures (34.5%), blood cultures (27.0%), tracheal aspirates (18.5%), urine cultures (12.5%), and catheter tips (7.5%). Of the 200 isolates, 87 (43.5%) were confirmed as MRSA by both PCR and cefoxitin disk diffusion. The MRSA rate was highest in ICU patients (62.1%) compared to surgical wards (41.3%) and medical wards (34.6%).

3.2 Patient Demographics and Clinical Characteristics

Baseline patient demographics and clinical characteristics stratified by MRSA versus MSSA are presented in Table 1. MRSA patients were significantly older (mean 54.3 vs. 49.7 years; p=0.042), more likely to have been admitted to the ICU (43.7% vs. 25.7%; p=0.007), had more frequent prior antibiotic use (70.1% vs. 47.8%; p=0.002), and had significantly longer hospital stays (18.4 vs. 11.2 days; p<0.001).

Table 1. Demographic and Clinical Characteristics of Patients with MRSA vs. MSSA Infections

SD = Standard Deviation. Statistically significant p-values (p<0.05) are shown in bold.

3.3 Antibiotic Resistance Profiles

Complete antibiotic resistance profiles with MIC₅₀ and MIC₉₀ values are presented in Table 2. Among MRSA isolates, the highest resistance rates were observed for ciprofloxacin (78.2%), erythromycin (74.7%), and tetracycline (51.7%). Clindamycin resistance was detected in 48.3% of MRSA and 19.5% of MSSA isolates; of note, inducible clindamycin resistance (positive D-zone test) was confirmed in an additional 11.5% of erythromycin-resistant, clindamycin-susceptible isolates. Co-trimoxazole resistance was present in 43.7% of MRSA strains, limiting its utility as an oral step-down option. Rifampicin resistance remained relatively low (14.9% in MRSA), preserving its potential for use in combination regimens. Critically, all 200 isolates remained fully susceptible to vancomycin (MIC₉₀ = 1 µg/mL) and daptomycin (MIC₉₀ = 0.5 µg/mL). Linezolid resistance was observed in only 2.3% of MRSA isolates.

Table 2. Antimicrobial Resistance Rates and MIC Values for S. aureus Isolates

MIC₅₀/MIC₉₀ = minimum inhibitory concentration inhibiting 50%/90% of isolates. µg/mL = micrograms per milliliter.

3.4 Multidrug and Extensively Drug-Resistant Phenotypes

The distribution of MDR and XDR phenotypes is shown in Table 3. MDR was identified in 42.0% of all isolates (n=84), with MRSA accounting for 54.0% of MDR cases. XDR phenotypes — defined as resistance to ≥5 antibiotic classes — were detected in 25.5% of all isolates (n=51). The proportion of XDR was significantly higher among MRSA isolates (39.1%) compared to MSSA (15.0%; p<0.001). No pandrug-resistant (PDR) isolate was identified. The most common MDR pattern involved concurrent resistance to β-lactams, fluoroquinolones, macrolides, and tetracyclines.

Table 3. Distribution of Multidrug and Extensively Drug-Resistant (MDR/XDR) Phenotypes

MDR = multidrug-resistant (resistance to ≥3 antibiotic classes); XDR = extensively drug-resistant (resistance to ≥5 antibiotic classes).

3.5 Predictors of MRSA Acquisition

On multivariate logistic regression, independent predictors of MRSA acquisition included prior antibiotic use within 90 days (OR 2.61; 95% CI 1.38–4.94; p=0.003), ICU admission (OR 2.19; 95% CI 1.12–4.29; p=0.022), and immunocompromised status (OR 2.44; 95% CI 1.08–5.51; p=0.032). Age >50 years showed a trend toward significance (OR 1.52; 95% CI 0.84–2.74; p=0.163). Prior hospitalization within 12 months was also significantly associated with MRSA (OR 1.89; 95% CI 1.03–3.47; p=0.040).

This study provides a comprehensive, institution-specific characterization of antibiotic resistance patterns in clinical S. aureus isolates from a tertiary care hospital. The 43.5% MRSA prevalence is broadly consistent with rates reported from similar settings in South Asia and the Middle East, where published estimates range from 30% to 60% [14,15]. The rate substantially exceeds European averages (approximately 16–18% in many countries per ECDC data), reflecting the compounding effects of higher antibiotic consumption, limited stewardship infrastructure, and crowded clinical environments in resource-constrained settings [5].

The high co-resistance rates we observed — particularly for fluoroquinolones (78.2%), macrolides (74.7%), and tetracyclines (51.7%) among MRSA strains — are clinically and epidemiologically significant. Fluoroquinolone resistance in MRSA is well-documented and is attributed primarily to mutations in gyrA and parC genes encoding DNA gyrase and topoisomerase IV, respectively [16]. This pattern renders empiric fluoroquinolone treatment of suspected MRSA infections unreliable and potentially harmful through selection pressure. Similarly, high erythromycin resistance — predominantly mediated by erm genes encoding ribosomal methylation — raises concern for inducible clindamycin resistance; our finding of D-zone positivity in 11.5% of isolates underscores the need for routine inducible clindamycin resistance testing in clinical laboratories [17].

The preservation of complete susceptibility to vancomycin and daptomycin across all 200 isolates is reassuring, as these agents remain first-line therapies for serious MRSA infections. However, these findings should not invite complacency: both VISA and hVISA, which may not be detected by routine MIC testing, have been associated with vancomycin treatment failure in the absence of elevated MICs [8]. Institutions should maintain robust vancomycin MIC surveillance and consider population analysis profiling (PAP) when treatment failure is suspected. Linezolid resistance in 2.3% of MRSA isolates, though numerically small, is notable given its relatively recent introduction and represents an emerging concern.

The prevalence of XDR phenotypes in 39.1% of MRSA isolates is particularly alarming. XDR S. aureus leaves clinicians with extremely limited therapeutic options, often restricted to vancomycin, daptomycin, and linezolid — agents that require intravenous administration, carry significant toxicity profiles, and may not be universally available in resource-limited settings [9]. The identification of XDR as a significant problem in our institution reinforces the urgency of antimicrobial stewardship programs (ASPs) that prioritize de-escalation, optimal dosing, and restriction of broad-spectrum agents.

Our multivariate analysis identified prior antibiotic use, ICU admission, and immunocompromised status as independent predictors of MRSA acquisition. These findings align with an extensive body of literature and have direct implications for clinical decision-making and infection control. Patients with these risk factors should trigger heightened surveillance, contact precautions, and consideration of decolonization strategies. Notably, prior hospitalization was also independently associated with MRSA, reflecting the well-documented role of healthcare exposure in MRSA transmission [18].

Several limitations of this study merit acknowledgment. First, the cross-sectional design precludes causal inference and temporal trend analysis. Second, molecular typing (e.g., MLST, spa typing, whole-genome sequencing) was not performed, limiting our ability to characterize dominant clonal lineages or track nosocomial transmission clusters. Third, clinical outcome data, including 30-day mortality and treatment response, were not systematically analyzed in this report, though a focused outcomes study is planned. Despite these limitations, this study represents one of the most methodologically rigorous local surveillance analyses at this institution to date.

Staphylococcus aureus isolates from hospitalized patients at this tertiary care center exhibit high MRSA prevalence and alarming rates of multidrug and extensive drug resistance. Vancomycin and daptomycin retain full activity and remain the agents of choice for serious MRSA infections. Fluoroquinolones, macrolides, and tetracyclines are highly unreliable for empiric MRSA therapy in this setting. The significant burden of XDR phenotypes underscores the urgent need for comprehensive antimicrobial stewardship programs, rigorous contact precautions, active surveillance cultures in high-risk patients, and systematic molecular epidemiology. Continuous, methodologically standardized surveillance is essential to detect emerging resistance threats — particularly reduced glycopeptide susceptibility — and to ensure that empiric treatment guidelines remain evidence-based and locally informed.

[1] Tong SYC, Davis JS, Eichenberger E, et al. Staphylococcus aureus infections: epidemiology, pathophysiology, clinical manifestations, and management. Clin Microbiol Rev. 2015;28(3):603–661.

[2] Cassini A, Högberg LD, Plachouras D, et al. Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU, 2015: a population-level modelling analysis. Lancet Infect Dis. 2019;19(1):56–66.

[3] Lakhundi S, Zhang K. Methicillin-resistant Staphylococcus aureus: molecular characterization, evolution, and epidemiology. Clin Microbiol Rev. 2018;31(4):e00020-18.

[4] David MZ, Daum RS. Treatment of Staphylococcus aureus infections. Curr Top Microbiol Immunol. 2017;409:325–383.

[5] European Centre for Disease Prevention and Control. Antimicrobial Resistance in the EU/EEA (EARS-Net): Annual Epidemiological Report 2020. Stockholm: ECDC; 2020.

[6] Nathwani D, Varghese D, Stephens J, et al. Value of hospital resources for effective diagnosis and treatment of methicillin-resistant Staphylococcus aureus (MRSA) disease: a systematic review. J Antimicrob Chemother. 2014;69(12):3250–3260.

[7] Limbago BM, Rasheed JK, Anderson KF, et al. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies for community-associated MRSA. J Clin Microbiol. 2009;47(11):3534–3544.

[8] Howden BP, Davies JK, Johnson PDR, Stinear TP, Grayson ML. Reduced vancomycin susceptibility in Staphylococcus aureus, including vancomycin-intermediate and heterogeneous vancomycin-intermediate strains: resistance mechanisms, laboratory detection, and clinical implications. Clin Microbiol Rev. 2010;23(1):99–139.

[9] Boucher HW, Corey GR. Epidemiology of methicillin-resistant Staphylococcus aureus. Clin Infect Dis. 2008;46(Suppl 5):S344–S349.

[10] Barlam TF, Cosgrove SE, Abbo LM, et al. Implementing an antibiotic stewardship program: guidelines by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. Clin Infect Dis. 2016;62(10):e51–e77.

[11] Hiramatsu K, Katayama Y, Matsuo M, et al. Multi-drug-resistant Staphylococcus aureus and future chemotherapy. J Infect Chemother. 2014;20(10):593–601.

[12] Clinical and Laboratory Standards Institute. Performance Standards for Antimicrobial Susceptibility Testing, 33rd ed. CLSI supplement M100. Wayne, PA: CLSI; 2020.

[13] Magiorakos A-P, Srinivasan A, Carey RB, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect. 2012;18(3):268–281.

[14] Sader HS, Farrell DJ, Flamm RK, Jones RN. Antimicrobial susceptibility of Gram-positive organisms isolated from European medical centres: results of the Antimicrobial Testing Leadership and Surveillance program (ATLAS), 2011–2016. J Antimicrob Chemother. 2018;73(4):1081–1091.

[15] Rao Q, Shang W, Hu X, Rao X. Staphylococcus aureus ST121: a globally disseminated hypervirulent community-associated methicillin-resistant lineage. Open Biol. 2020;10(10):200213.

[16] Schmitz FJ, Fluit AC, Hafner D, et al. Development of resistance to ciprofloxacin, rifampin, and mupirocin in methicillin-susceptible and -resistant Staphylococcus aureus isolates. Antimicrob Agents Chemother. 2000;44(11):3229–3231.

[17] Siberry GK, Tekle T, Carroll K, Dick J. Failure of clindamycin treatment of methicillin-resistant Staphylococcus aureus expressing inducible clindamycin resistance in vitro. Clin Infect Dis. 2003;37(9):1257–1260.

[18] Wertheim HFL, Melles DC, Vos MC, et al. The role of nasal carriage in Staphylococcus aureus infections. Lancet Infect Dis. 2005;5(12):751–762.