Heatmap-Based and Regression Analysis of Antibiotic Co-Resistance Networks Among Gram-Positive Bacterial Isolates in a Tertiary Care Hospital
Abstract
Abstract Background Antimicrobial resistance (AMR) among Gram-positive bacteria is an escalating global health concern, increasingly complicated by the emergence of multidrug resistance (MDR). Traditional resistance surveillance often evaluates antibiotics individually, failing to capture co-resistance patterns that critically influence empirical therapy and clinical outcomes. Methods We conducted a retrospective observational study of Gram-positive bacterial isolates recovered from adult patients at a tertiary care hospital in Palestine between January 2021 and May 2025. Non-duplicate clinical isolates with complete antimicrobial susceptibility testing data were included. Resistance profiles were analyzed using pairwise phi-correlation matrices and visualized through hierarchical clustering heatmaps to identify antibiotic co-resistance patterns. Multidrug resistance was defined as non-susceptibility to at least one agent in three or more antimicrobial classes. Univariable and multivariable logistic regression analyses were performed to identify clinical and demographic predictors of MDR. Results A total of 2,364 unique Gram-positive isolates were analyzed. Strong positive co-resistance was observed between fluoroquinolones, particularly ciprofloxacin and levofloxacin, as well as between β-lactam agents such as penicillin and amoxicillin/clavulanic acid. Distinct co-resistance patterns were identified across inpatient and outpatient settings, with overall consistency…
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