Abstract

Objectives: • Understand the role of Demodex within the skin microbiome and ecosystem • Recognize clinical patterns of Demodex-associated dermatoses • Apply practical diagnostic and management strategies in daily practice • Explore the potential of AI and digital tools in dermatologic diagnosis Introduction: Demodex mites are common inhabitants of the human skin ecosystem and have traditionally been regarded as harmless commensals. However, increasing evidence suggests that Demodex folliculorum may play a significant role in inflammatory facial dermatoses, including acneiform eruptions and rosacea. In the context of treatment-resistant cases, Demodex has emerged as a potential contributing factor within the broader framework of skin microbiome imbalance and host–microbe interaction. Materials / method: This study integrates findings from my clinical observational studies, case series, research and recent real-world data evaluating the association between Demodex density and facial dermatoses. Diagnostic approaches included clinical assessment, dermoscopy, and standardized skin surface biopsy (SSSB). In addition, outcomes of therapeutic interventions using topical and systemic acaricidal agents were reviewed. Emerging tools such as digital dermoscopy and AI-assisted image analysis were also considered in the context of improving diagnostic accuracy. Results: Increased Demodex density was consistently observed in patients with acneiform eruptions, papulopustular rosacea, and treatment-resistant facial dermatoses compared to healthy cont Clinical patterns associated with Demodex included papulopustular lesions without comedones, central facial distribution, and poor response to conventional therapies. Treatment with acaricidal agents, particularly ivermectin-based regimens, demonstrated significant clinical improvement in a subset of patients. These findings support the role of Demodex as a contributing factor in inflammation and treatment failure. Conclusion: Demodex should be considered a relevant component of the skin ecosystem that may contribute to inflammatory dermatoses in selected patients. Recognizing its role can improve diagnostic accuracy and guide targeted therapy, particularly in treatment-resistant cases. Integrating clinical evaluation with emerging diagnostic technologies, including AI-assisted tools, may further enhance early detection and personalized management in modern clinical dermatology.