关键词: 皮肤真菌病, 皮肤真菌感染, 耐药性, 分子诊断, 人工智能, 个体化治疗, 监测网络

Abstract: 【Abstract】 Cutaneous fungal infections are clinically common diseases with a complex pathogenic spectrum. Significant changes in their epidemiological trends and pathogen distribution have been observed due to alterations in immune status, antifungal drug use, and environmental factors. This article systematically reviews the current status of, core challenges in, and future optimization strategies for the diagnosis and treatment of cutaneous fungal infections in China and other countries. Current diagnostic techniques include traditional fungal microscopy, fungal cultures, and molecular methods. Although molecular methods have significantly improved the sensitivity and timeliness of diagnosis, they cannot completely replace conventional approaches. Artificial intelligence-assisted fungal image recognition technology shows promising potential for application. Their treatment primarily relies on topical and oral antifungal agents, but the emergence of drug-resistant strains and refractory infections in immunocompromised patients pose clinical challenges. Novel drugs and nanocarrier technologies offer new therapeutic options. A national surveillance network for dermatophytoses has been established in China, but challenges persist, such as inadequate diagnostic and therapeutic capabilities at the primary care level and poor patient compliance. Future efforts should focus on promoting molecular diagnostics, implementing dynamic antifungal resistance surveillance, advancing personalized treatment, strengthening primary care capabilities, establishing a multidisciplinary collaborative system, and enhancing international cooperation to control the global transmission of antifungal resistance.

Key words: Dermatomycoses, Cutaneous fungal infection, Drug resistance, Molecular diagnosis, Artificial intelligence, Personalized treatment, Surveillance network