Characterizing Antimicrobial Resistance in a Regional Hospital’s Enteric Bacteria Case Study

Thesis Abstract

In the face of rising antimicrobial resistance (AMR) among enteric bacteria, regional hospitals face challenges in effective clinical management, infection control, and public health surveillance, underscoring the need for locally contextualized AMR profiling. This study aims to characterize antimicrobial resistance patterns, determinants, and transmission dynamics of enteric bacteria isolates obtained from patients at a regional hospital, to inform targeted stewardship and infection prevention strategies. The specific objectives are (1) to determine the prevalence and distribution of key enteric bacterial species (Escherichia coli, Salmonella spp., Shigella spp., and Campylobacter spp.) from stool and blood culture isolates over a 12-month period; (2) to assess antimicrobial susceptibility profiles against a panel of 14 antibiotics representing major classes (?-lactams, fluoroquinolones, aminoglycosides, macrolides, tetracyclines, sulfonamides) using standardized disk diffusion and minimum inhibitory concentration (MIC) testing per CLSI guidelines; (3) to identify phenotypic and genotypic determinants of resistance, including extended-spectrum ?-lactamase (ESBL) production and gyrA/parC mutations, via confirmatory phenotypic tests and multiplex PCR assays; (4) to examine clinical and environmental risk factors associated with resistant infections through multivariate logistic regression; (5) to explore potential clonal relationships and transmission using pulsed-field gel electrophoresis (PFGE) and/or multi-locus sequence typing (MLST) on resistant isolates; and (6) to develop a locally tailored AMR profile dashboard for the hospital antimicrobial stewardship program. The methodological framework adopts a convergent mixed-methods design to integrate quantitative resistance data with qualitative insights from clinicians and infection control staff. The population comprises all enteric bacteria isolates collected from patients at the regional hospital’s microbiology laboratory over 12 months, with estimated sample size 300–350 isolates based on prior surveillance data. Instrumentation includes standardized laboratory assays for species identification, disk diffusion and broth microdilution for antibiotic susceptibility, ESBL confirmation using combined disk tests, PCR assays targeting blaCTX-M, blaTEM, blaSHV, and gyrA/parC loci, and epidemiological data collection forms capturing demographics, preceding antibiotic exposure, hospitalization history, and exposure risks. Validity and reliability are ensured through participation in external quality assessment schemes, duplicate testing for 10% of isolates, and pre-testing of data collection instruments. Data analysis proceeds in two parallel tracks. Quantitative data will be analyzed using descriptive statistics to summarize species distribution and resistance frequencies, chi-square tests for initial associations, and multivariate logistic regression to identify independent predictors of multidrug-resistant (MDR) infections. MIC distributions will be analyzed to determine resistance phenotypes, with ESBL producers characterized by confirmatory tests. Molecular data will be interpreted to determine prevalence of resistance genes and clonality, with PFGE/MLST results used to infer possible transmission networks. The qualitative dimension will be explored through thematic analysis of interviews with clinicians and infection control personnel, with theories of behavioral change and adoption of antimicrobial stewardship guiding coding and interpretation. Expected findings include high prevalence of MDR enteric pathogens, with significant proportions of ESBL-producing E. coli and fluoroquinolone-resistant Salmonella and Campylobacter species. Genotypic analyses are anticipated to reveal blaCTX-M dominance among ESBL producers and prevalent gyrA mutations correlating with fluoroquinolone resistance. Regression analyses are expected to identify key risk factors such as prior antimicrobial exposure, recent hospitalization, and community-acquired infections with prolonged community antibiotic use. Clonal analyses may detect distinct transmission clusters within inpatient wards, suggesting both horizontal gene transfer and nosocomial spread. The study will generate a locally contextual AMR profile and an actionable dashboard highlighting high-risk antibiotics, ward-level trends, and emerging resistance determinants to guide stewardship interventions. The research contributes to knowledge by providing granular, hospital- and community-relevant AMR data on enteric pathogens in a regional healthcare setting, linking phenotypic resistance with molecular mechanisms and transmission context. It advances methodological integration by combining traditional microbiology with molecular epidemiology and behavioral insights to inform targeted infection prevention and antibiotic stewardship, thereby bridging gaps between laboratory surveillance and clinical practice. Recommended actions include reinforcing antibiotic stewardship with local formulary adjustments, enhancing infection prevention in high-risk wards, implementing routine resistance gene monitoring, and establishing ongoing genomic surveillance to promptly detect emerging resistance. The study also emphasizes the need for community education to curb inappropriate antibiotic use and supports regional collaboration for AMR data sharing.