Rethinking “Type 2”: Inside the 2026 AACE Diabetes Classification Algorithm

In this segment, Susan Samson, MD, opens the discussion by situating the 2026 AACE Algorithm for the Management of Adults With Type 2 Diabetes within the broader need to move beyond a default diagnosis of type 2 diabetes. She explains that the new update includes a dedicated diabetes classification algorithm, a conceptual addition intended to stand alongside traditional glycemic management pathways. According to Samson, the key question embedded in this framework is deceptively simple but clinically powerful: “Are you sure the patient has type 2 diabetes?” This reframing sets the stage for a more deliberate diagnostic approach in adults who present with hyperglycemia.

Guillermo Umpierrez, MD, underscores the significance of this change by contrasting the 2026 version with the 2023 algorithm, which did not include a discrete classification pathway. He notes that the new algorithm is designed to remind clinicians to consider etiologies beyond type 2 diabetes at both initial diagnosis and over the course of established disease. The panel emphasizes that obesity, insulin resistance, and weight gain are highly prevalent in patients with type 2 diabetes, but these features can be misleading when applied uncritically to every adult with hyperglycemia. The algorithm is therefore intended to prompt a systematic review of clinical features that might suggest alternative diagnoses.

Samson then highlights literature showing that misclassification of adult-onset type 1 diabetes as type 2 diabetes is common and clinically consequential. She cites data from the UK “DARE” cohort, in which nearly 40% of adults older than 30 years who met criteria for type 1 diabetes were treated as if they had type 2 diabetes and did not receive insulin at diagnosis. She also notes that a substantial proportion of type 1 diabetes is diagnosed in adulthood, with more than one-third of patients receiving a diagnosis after age 30.

Together, Samson and Umpierrez frame the new classification algorithm as a response to this misclassification burden, intended to help clinicians reassess presumed type 2 diabetes when the clinical course is atypical.