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Vancomycin-Induced DRESS Syndrome: A Systematic Review of Case Reports
Siva Krishna Adithya Bhumireddy1, Sai Shashank Gudla1, Anil Kumar Vadaga1
1GIET School of Pharmacy, Rajahmundry, Andhra Pradesh, India.
Abstract:
Background: Vancomycin-induced Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) syndrome is a severe hypersensitivity reaction. It presents with rash, eosinophilia, fever, lymphadenopathy, and multi-organ involvement, most often leading to misdiagnosis and delayed treatment. This systematic review aims to identify risk factors, clinical presentations, and optimal management strategies for vancomycin-induced DRESS. Methods: Systematic search with PRISMA 2020 was conducted in PubMed, Scopus, Web of Science, and Google Scholar. Case reports from 2015 to 2025 were screened and demographic information, clinical presentation, risk factors, diagnostic assessment, and outcomes were extracted. Quality of included reports was evaluated with Joanna Briggs Institute (JBI) Critical Appraisal Checklist. Report: The most common symptoms were rash, fever, eosinophilia, and hepatic/renal dysfunction, which typically appeared 2 to 9 weeks following exposure. Genetic predisposition (HLA associations), renal dysfunction, concomitant medications, and viral reactivation were significant risk factors. Rise of AST was shown after a time, and so diagnosis was difficult. Discontinuing vancomycin, administering corticosteroids, and supportive care were the most preferable interventions, with severe conditions requiring IVIG, plasmapheresis and immunosuppressants. Despite interventions, mortality remains high in elderly and immunocompromised patients. Conclusion: Vancomycin is one of the most frequent causes of antibiotic-induced DRESS syndrome, rarely accompanied by severe organ failure and mortality. Early detection, following consistent diagnosing criteria, and tailored treatment regimens are needed to improve patient outcomes and reduce the risk of mortality and improve wellbeing. More research is needed to explore genetic patterns and develop optimal treatment regimens.
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