DIABETES AND PERIODONTAL DISEASE: INTERCONNECTED PATHOPHYSIOLOGY AND CLINICAL IMPLICATIONS: A COMPREHENSIVE REVIEW
Journal: International Journal of Advanced Research (Vol.12, No. 07)Publication Date: 2024-07-15
Authors : Abdulrahman Abdulaziz Aldawish Nawaf Mohammed Alzaben Lulya Mohammed Alzain Haitham Saad Alsumaihan Saud Abdulaziz Alhubaish Turki Saqer Almutairi Dalal Munwikh Al Shammari Al Hanouf Saleh AlGoudah Alanoud Saleh Alturki;
Page : 452-464
Keywords : Diabetes Mellitus Periodontal Diseases Biomarkers Inflammation Interdisciplinary Care Early Detection;
Abstract
The bidirectional relationship between diabetes mellitus (DM) and periodontal disease is well-documented, with poor glycemic control exacerbating periodontal inflammation and vice versa. Novel therapies, including anti-inflammatory agents, antioxidants, and biologics, show promise in reducing systemic inflammation and improving glycemic control. Advances in identifying salivary biomarkers such as miRNAs 146a/b and 155, IL-1β, MMP8, and IL-6 have improved early detection of periodontitis in diabetic patients. Additionally, innovative imaging techniques like Raman spectroscopy and multiplex hand-held biosensors have enhanced diagnostic accuracy. Longitudinal studies and clinical trials remain essential to validate the long-term benefits and safety of new biomarkers and therapies. Recent studies highlight the importance of integrated care and interdisciplinary collaboration between dental and medical professionals to effectively manage these interrelated conditions. Future research should focus on understanding the biological pathways linking DM and periodontal disease, with a particular emphasis on the roles of inflammatory cytokines, oxidative stress, and the microbiome. Public health initiatives should aim to increase awareness of the bidirectional relationship between DM and periodontal disease through educational campaigns and community-based screening programs. Policy recommendations should encourage integrated health services and interdisciplinary training programs. The integration of artificial intelligence and machine learning in diagnostic tools offers potential for early detection and personalized treatment plans, further improving patient outcomes. Addressing these research gaps through continued investigation and technological innovation is crucial for enhancing the prevention, diagnosis, and management of diabetes and periodontal disease. These efforts will ultimately lead to better health outcomes and quality of life for affected individuals.
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