MODERN APPROACHES TO EARLY DIAGNOSTICS OF TYPE 2 DIABETES - Khusanboev I.O. (Uzbekistan Open Conference, 2026)
Early diagnosis of Type 2 diabetes mellitus (T2DM) is crucial for prevention of longterm complications, improving prognosis, and reducing healthcare burden. Recent advances in diagnostic biomarkers, predictive algorithms, and non-invasive screening strategies promise earlier identification of at-risk individuals. This paper reviews and analyses emerging diagnostic tools – including HbA1c thresholds, continuous glucose monitoring, machine learning models, and combined clinicalelectrocardiographic risk stratification – and evaluates their sensitivity, specificity, and practicality in diverse populations. Findings indicate that multimodal and algorithmic approaches yield superior predictive performance compared to traditional fasting plasma glucose or oral glucose tolerance tests alone, although cost, access, and standardization remain challenges. The study suggests integrating predictive models and novel biomarkers into routine screening programs, particularly for high-risk cohorts.
Keywords: Type 2 diabetes mellitus; early diagnosis; predictive model; biomarker; screening; machine learning