Improving Oral and Systemic Health in Individuals With Prediabetes Through Personalized Oral Hygiene Advice Provided by Dentists or by AI
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: AI OHI group, Dental professionals OHI group.
- Who it may be relevant to
- Registry conditions: Gum Disease, Prediabetes. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Hong Kong
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Improving Oral and Systemic Health in Individuals With Prediabetes Through Personalized Oral Hygiene Advice Provided by Dentists or by Artificial Intelligence: A Randomized Clinical Trial
Overview
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. 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. Artificial Intelligence (AI) has been used to provide personalized advice on the adequacy of patients' home care (oral hygiene). The investigators hypothesize that the use of AI can improve home care, thereby enhancing both gum health and systemic health, similar to human dental professionals.
Detailed description
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.
Interventions
- Behavioral AI OHI group
The participants will receive personalized OHI such as toothbrush and interdental cleaning to specific areas provided by AI. An mHealth system will be used to detect intraoral photograph of anterior teeth and analysis of the photograph and label the gum condition as Healthy (green)/questionable (yellow)/diseased (red) within 2 minutes by AI. Then specific OHI to each particular site would be provided by AI according to tested results on the photograph - Behavioral Dental professionals OHI group
ll participants will receive personalized OHI by dental professionals. This instruction includes brushing and interdental cleaning in each particular dental site. If they have any personal concern or unclear points regarding oral hygiene practice, they can ask.
Primary outcome measures
- Gum inflammation at baseline [Time frame: baseline]
- Gingival health at baseline [Time frame: baseline]
- Oral hygiene status at baseline [Time frame: baseline]
- HbA1c level at baseline [Time frame: baseline]
- FPG level at baseline [Time frame: baseline]
- 2-h PG during 75-g OGTT level at baseline [Time frame: baseline]
- Gum inflammation at 3-month [Time frame: 3-month]
- Gingival health at 3-month [Time frame: 3-month]
- Oral hygiene status at 3-month [Time frame: 3-month]
- HbA1c level at 3-month [Time frame: 3-month]
Secondary outcome measures (11)
- C-reactive protein level at baseline, 3-month and 9-month follow-ups [Time frame: at baseline, 3-month and 9-month follow-ups]
- IL6 level at baseline, 3-month and 9-month follow-ups [Time frame: at baseline, 3-month and 9-month follow-ups]
- IL8 level at baseline, 3-month and 9-month follow-ups [Time frame: at baseline, 3-month and 9-month follow-ups]
- Body weight at baseline, 3-month and 9-month follow-ups [Time frame: at baseline, 3-month and 9-month follow-ups]
- Percentage body fat at baseline, 3-month and 9-month follow-ups [Time frame: 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 [Time frame: 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 [Time frame: at baseline, 3-month and 9-month follow-ups]
- 3-day food record at baseline, 3-month and 9-month follow-ups [Time frame: 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 [Time frame: at baseline, 3-month and 9-month follow-ups]
- Chinese version of Munich Chronotype Questionnaire at baseline, 3-month and 9-month follow-ups [Time frame: 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 [Time frame: at baseline, 3-month and 9-month follow-ups]
Eligibility criteria
Inclusion criteria
- \- Subjects who are >18 years of age and able to give informed consent.
- \- Subjects who are mentally and cognitively healthy.
- \- Subjects who have at least 6 anterior maxillary or mandibular natural teeth including incisors and canine.
- \- Subjects who are with prediabetic state with impaired HbA1c 5.7% to 6.4%, impaired fasting plasma glucose level 5.6mmol/L to 6.9 mmol/L and/or impaired plasma glucose level after 2h OGTT 7.8 mmol/L to 11.0 mmol/L.
- \- Subjects who can speak, read, or understand Cantonese to complete the satisfaction questionnaire.
- \- Subjects who can practice oral hygiene procedure (regular tooth brushing and interdental cleansing/flossing/brushing) daily on their own independently.
Exclusion criteria
- \- Subjects who have less than 6 anterior maxillary or mandibular natural teeth with or without dental prostheses in those area.
- \- Subjects who are with a current diagnosis or clinical history of T2DM.
- \- Subjects who have mental illness, or similar problems that unable to complete the satisfaction questionnaire.
- \- Subjects who cannot perform oral hygiene procedure (regular tooth brushing and interdental cleansing/flossing/brushing) by any condition of oral cavity such as tumor or maxillomandibular fixation.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Triple blind
- Primary purpose
- Treatment
Study locations
Hong Kong · 1 center
- Prince Philip Dental Hospital — Hong Kong
Identifiers
NCT: NCT06980701 · UW 24-658