[Detecting impaired glucose tolerance based on medical decision making]

Area of Science:

• Endocrinology and Metabolism
• Preventive Medicine
• Diagnostic Biomarkers

Context:

• Impaired glucose tolerance (IGT) is a critical preclinical stage of diabetes mellitus (DM).
• Routine health examinations face time constraints, making the standard oral glucose tolerance test (OGTT) impractical for widespread IGT screening.
• Developing alternative, efficient methods for IGT detection is essential for early intervention and diabetes prevention strategies.

Purpose:

• To establish an effective and time-efficient procedure for detecting impaired glucose tolerance (IGT) without relying on the oral glucose tolerance test (OGTT).
• To identify optimal cut-off values for serum fructosamine (FRA), glycosylated hemoglobin (HbA1C), and fasting plasma glucose (FPG) in IGT screening.
• To develop and validate a logistic regression model incorporating age, body mass index (BMI), FPG, and HbA1C for improved IGT diagnosis.

Summary:

• A study involving 422 males analyzed serum fructosamine (FRA), glycosylated hemoglobin (HbA1C), and fasting plasma glucose (FPG) alongside OGTT.
• Receiver operating characteristic (ROC) analysis suggested optimal cut-off values: FPG ≥ 100 mg/dl, HbA1C ≥ 5.3%, and FRA ≥ 240 µmol/l.
• A logistic function incorporating age, BMI, FPG, and HbA1C demonstrated a sensitivity of 0.755 and specificity of 0.753 for IGT detection when the function value was ≥ 0.2.

Impact:

• Provides a validated, non-OGTT-based logistic model for identifying individuals with impaired glucose tolerance (IGT).
• Enhances the feasibility of IGT screening within standard health check-ups, facilitating earlier intervention for pre-diabetes.
• Contributes to preventive medicine by offering a more accessible approach to identifying individuals at risk of developing diabetes mellitus (DM).