Identifying Undiagnosed Diabetes and Prediabetes in the Dental Setting in an Asian Population-A Clinical Risk Model

Area of Science:

• Oral health
• Endocrinology
• Public health

Background:

• Diabetes mellitus (DM) is a global health concern with significant oral health implications.
• Assessing glycaemic status in diverse patient populations is crucial for early diagnosis and management.
• Tertiary care dental settings offer a unique opportunity to identify individuals at risk for undiagnosed DM.

Purpose of the Study:

• To evaluate the glycaemic status among Asian patients within a tertiary dental care environment.
• To develop and validate a predictive risk model for identifying undiagnosed diabetes mellitus (DM).
• To explore the association between oral health indicators and DM risk.

Main Methods:

• A cohort of 1074 Asian participants underwent a diabetes risk assessment questionnaire, comprehensive periodontal examination, and point-of-care HbA1c testing.
• Univariable and multivariable logistic regression analyses were utilized to identify predictors of DM.
• A predictive risk model was developed using stepwise variable selection.

Main Results:

• The study identified 6.1% with medically confirmed type 2 diabetes mellitus (T2DM) and 7.7% with prediabetes.
• A predictive model incorporating body mass index (BMI), family history of diabetes, smoking, and severe periodontitis demonstrated good predictive accuracy (AUC ≈ 0.72).
• The inclusion of oral health status (severe periodontitis) marginally improved the model's predictive capability.

Conclusions:

• Advanced periodontitis in dental patients, when combined with risk factors like high BMI, family history of DM, and smoking, indicates a high likelihood of undiagnosed DM.
• These high-risk individuals should be prioritized for diabetes screening and subsequent medical evaluation and management.
• Integrating oral health assessments into routine care can aid in the early detection of systemic diseases like diabetes.