Improving Oral and Systemic Health in Individuals With Prediabetes Through Personalized Oral Hygiene Advice Provided by Dentists or by AI

Prediabetes is an intermediate stage before the development of diabetes, characterized by elevated blood glucose levels but lower than the diagnostic criteria of diabetes and is associated with multiple long-term complications. This systemic disease is mutually linked to inflammatory gum diseases through circulating inflammatory mediators. The relation between oral health and prediabetes management has long been under-appreciated. People with prediabetes have a 2-3-fold greater risk for periodontitis compared to people without prediabetes. The progression and severity of periodontitis are also greater in prediabetic patients. According to the National Health and Nutrition Examination Survey, the severity of periodontitis is positively associated with the risk as well as the prevalence of prediabetes. A growing body of data indicates that oral inflammation has an impact on general diseases. Controlling inflammatory gum diseases improves blood glucose levels and reduces long-term complications. While maintaining good oral hygiene through home care is essential for managing inflammatory gum diseases, close supervision of patients' home care is labor-intensive and expensive.

Nowadays, artificial intelligence (AI) can readily assist in the self-detection of diseases, including gum disease, allowing older adults to identify diseases early and prevent further complications. The use of AI-based mHealth has become increasingly effective in promoting periodontal health by adopting simple, AI-driven self-tests using smartphones. Another systematic review done by investigators' team found that AI-based mHealth for oral hygiene and gum disease monitoring showed clinical effectiveness across different clinical scenarios. The investigators' team has already launched an AI system for the detection of gum disease using smartphone intraoral photography, in which the system can detect colour changes of gum inflammation in specific sites in intraoral photography and diagnose as three simple situations (severe, mild and no inflammation). The AI system have high sensitivity 92% to identify disease from sites that have gingivitis, and high specificity 94% to identify healthy tissue from sites that have no gingivitis using professional intraoral photography. Moreover, the investigators have tested that the accuracy of colour captured by a smartphone is comparable to that captured by a professional single-lens reflective camera. The investigators' team already have applied the AI-powered smartphone photography among 38 older adults in 5 day-care centres of Hong Kong to test participants' gum health. The result is promising with accuracy of 96% sensitivity and 82% specificity. The present study will apply AI technology on disease detection and giving personalized oral health instruction (OHI) closely to the patients to maintain periodontal health and consequently prediabetic control.

In this study, the hypothesis is that the use of AI can improve home care, thereby enhancing both gum health and systemic health, similar to human dental professionals.

• C-reactive protein level at baseline, 3-month and 9-month follow-ups [Срок оценки: at baseline, 3-month and 9-month follow-ups]
• IL6 level at baseline, 3-month and 9-month follow-ups [Срок оценки: at baseline, 3-month and 9-month follow-ups]
• IL8 level at baseline, 3-month and 9-month follow-ups [Срок оценки: at baseline, 3-month and 9-month follow-ups]
• Body weight at baseline, 3-month and 9-month follow-ups [Срок оценки: at baseline, 3-month and 9-month follow-ups]
• Percentage body fat at baseline, 3-month and 9-month follow-ups [Срок оценки: at baseline, 3-month and 9-month follow-ups]
• Shannon diversity index of oral and gut microbiota at baseline, 3-month and 9-month follow-ups [Срок оценки: at baseline, 3-month and 9-month follow-ups]
• Concentration of short chain fatty acid in stool samples at baseline, 3-month and 9-month follow-ups [Срок оценки: at baseline, 3-month and 9-month follow-ups]
• 3-day food record at baseline, 3-month and 9-month follow-ups [Срок оценки: at baseline, 3-month and 9-month follow-ups]
• Chinese version of Chrono-nutrition Profile Questionnaire at baseline, 3-month and 9-month follow-ups [Срок оценки: at baseline, 3-month and 9-month follow-ups]
• Chinese version of Munich Chronotype Questionnaire at baseline, 3-month and 9-month follow-ups [Срок оценки: at baseline, 3-month and 9-month follow-ups]
• Chinese version of international physical activity questionnaire short form at baseline, 3-month and 9-month follow-ups [Срок оценки: at baseline, 3-month and 9-month follow-ups]