Can routinely collected electronic health record (EHR) data help distinguish people with type 2 diabetes (T2DM) who face different rates of vascular complications at diagnosis? A large observational analysis published in Diabetologia evaluated this question in more than 700,000 adults across the United States. 

The study identified 727,076 adults aged 18 years or older with newly diagnosed T2DM from the Epic Cosmos research platform across all 50 states and the District of Columbia between 2012 and 2023. Classification models previously developed in cohort studies were applied to EHR data to assign individuals to four subtypes: severe insulin-deficient diabetes (SIDD), mild obesity-related diabetes (MOD), mild age-related diabetes, and a mixed subtype. Cox proportional hazards regression models adjusted for age and sex assessed rates of microvascular complications, including retinopathy, neuropathy, and nephropathy, and macrovascular complications, including severe atherosclerotic cardiovascular disease (ASCVD), other ASCVD, and heart failure. 

Among individuals with newly diagnosed T2DM (mean age 64.4 years; standard deviation 13.3; 52% female), 21.6% were classified as SIDD, 23.8% as MOD, 40.9% as mild age-related diabetes, and 13.7% as the mixed subtype. Compared with MOD, SIDD was associated with higher rates of retinopathy (HR 2.83; 95% confidence interval [CI] 2.73-2.93), neuropathy (HR 1.57; 95% CI 1.54-1.60), nephropathy (HR 1.34; 95% CI 1.32-1.37), severe ASCVD (HR 1.49; 95% CI 1.46-1.53), other ASCVD (HR 1.23; 95% CI 1.21-1.25), and heart failure (HR 1.17; 95% CI 1.15-1.20). SIDD and MOD were more prevalent among Hispanic and non-Hispanic Black individuals compared with non-Hispanic White individuals and were also more prevalent in the District of Columbia and Utah, respectively, compared with the rest of the country. 

Overall, EHR-defined T2DM subtypes were associated with differing rates of microvascular and macrovascular complications at diagnosis.