Healthcare-Associated Infections and Antimicrobial Resistance in Hospitalized Burn Patients: Incidence Density, Device-Associated Rate, and Predictors among a Single Center Cohort - Hussein, Suzan Radhi (American Journal of Bioscience and Clinical Integrity, 2026)
Background: Healthcare associated infections (HAIs) are a leading cause of illness in the burn patient population, which is caused by extensive tissue damage, extended time spent in the hospital, invasive device exposure and high pressure of antibiotics. This study assessed the burden, clinical correlates, microbiological profile and antimicrobial resistance patterns of HAIs among burn patients receiving care at the hospitals. Methods: An observational study was undertaken at a hospital located in the burn care setting. Standardized surveillance definitions were used to assess patients admitted during the study period for HAIs. Clinical and exposure variables (indicate of burn severity, ICU admission, invasive devices, surgery, previous antibiotic exposure and length of stay) were collected. HAI incidence density was calculated and episodes per 1,000 patient-days. Device associated infection rates (VAP, CAUTI, CLABSI) were defined on a per 1000 device-day basis. Microbiological isolates were summarized by using first isolate per episode. The resistance phenotypes (MDR/XDR) were categorized by using standard criteria. Multivariable logistic regression model was performed to determine independent predictors of HAI. Results: out of 51 patients, 43 (84.3%) had developed at least 1 HAI. A total of 60 episodes of HAI occurred for 780 patient-days, resulting in a rate of 76.9 per 1,000 patient-days. Pneumonia 46.7%, followed by UTI 33.3% and BSI 13.3% and wound/SSI 6.7% accounted for 57.3% of the episodes. Culture positivity was 91.7%. Gram-negative organisms were predominant such as Pseudomonas aeruginosa (27.3%) and Klebsiella pneumoniae (18.2%). MDR and XDR rates were 61.8% and 20.0% respectively but the greatest burden of resistance was found among non-fermenters. In the multivariable analysis, both of these predictors, higher TBSA and previous antibiotic exposure, had the strongest associations with risk of HAI. Conclusion: The working results show a high HAI burden showing a preponderance of pneumonia/UTI to be considered with a high burden of MDR/XDR, which favors the implementation of device bundles with the subsidiary of strengthened surveillance with severity-adjusted implementation of antibiogram-guided antimicrobial therapeutic. Final estimates and model coefficients need to be remodeled upon locking on real denominators and patient-level data.