Drug Resistance Analysis and Prediction Model Construction of Carbapenem-Resistant <i>Acinetobacter baumannii</i>

This study analyzed the antimicrobial resistance profiles and risk factors for carbapenem-resistant Acinetobacter baumannii (CRAB) in a tertiary hospital and developed a predictive model for infection control. Among 64 Acinetobacter baumannii isolates collected in 2024 from the First People's Hospital of Chuzhou, CRAB accounted for 40.63% (26/64), with sputum being the most common specimen source (85.94%) and the highest isolation rate observed in respiratory wards. CRAB exhibited significantly higher resistance to most antibiotics compared to carbapenem-sensitive strains (CSAB), except for polymyxin and tigecycline (<i>P</i> < 0.05). Multivariate analysis identified ≥3 underlying diseases, prior use of compound antibiotics, and tracheal intubation/incision as independent risk factors for CRAB infection. A nomogram prediction model constructed with R software demonstrated high predictive accuracy (C-index: 0.985). The findings highlight a concerning prevalence and multidrug resistance of CRAB in this setting, underscoring the need to enhance monitoring, early risk factor identification, and targeted interventions to reduce transmission and optimize antimicrobial stewardship.