مقالات پذیرفته شده در نهمین کنگره بین المللی زیست پزشکی
Methods for controlling hospital infections caused by fungi
Methods for controlling hospital infections caused by fungi
Amirhossein Khorramian,1,*Arman Moradi,2Robab Bayrami,3
1. Department of Microbiology,La.C., Islamic Azad University, Lahijan , Iran 2. Department of Microbiology,La.C., Islamic Azad University, Lahijan , Iran 3. Department of Microbiology,La.C., Islamic Azad University, Lahijan , Iran
Introduction: Nosocomial fungal infections are a major issue in healthcare facilities and their control and prevention as fungal pathogens become increasingly resistant to antifungal drugs are increasingly significant. Fungal infections acquired in hospitals are a growing concern, especially among people with compromised immune systems. Early and precise diagnosis, combined with effective prevention strategies, is essential to improving recovery outcomes and reducing mortality.
Methods: The integration of cutting-edge diagnostic tools with artificial intelligence (AI) opens up new possibilities for more efficient detection and management of these infections. Studies show that hospital environments have a greater incidence of fungi including Candida auris, Aspergillus species, and others, mostly because of their high resistance and easy transmission through direct or indirect interaction. Control of fungal infections therefore calls for a range of methods, including rigorous compliance with hygiene norms, thorough training of healthcare professionals, and careful application of disinfectants. A vital part of infection control is the quick and accurate detection of infectious organisms utilizing molecular techniques and laboratory cultures. Quarantining of the infected and limiting patients' access to common medical equipment lowers transmission risk considerably. Also Artificial intelligence is playing an increasingly vital role in infection management. By analyzing large datasets from laboratory tests, patient medical histories, and environmental monitoring, AI can predict potential outbreaks and identify high-risk patients. Machine learning models are especially valuable in interpreting complex molecular data, offering more reliable diagnoses than traditional approaches.
Results: Moreover, it's critical to develop and follow strict medication management guidelines and monitor hospital infection patterns using infection control programs. Regular education for healthcare professionals is absolutely essential to reduce infection rates and improve patient outcomes.
Conclusion: Managing hospital fungal infections finally calls for interdisciplinary cooperation among several hospital departments and the integration of modern diagnostic and control approaches. These programs are vital in medical facilities for avoiding fungal epidemics together with raising healthcare personnel awareness and upgrading healthcare infrastructure.