A Better Way to Tell Type 1 and Type 2 Apart in Adults

Type 1 and Type 2 diabetes are fundamentally different diseases. Type 1 is autoimmune—the body's immune system attacks insulin-producing cells. Type 2 is metabolic, usually linked to insulin resistance and lifestyle factors. The treatments are different too: Type 1 requires insulin from day one, while Type 2 is typically managed with lifestyle changes and non-insulin medications, at least initially.

Both conditions, however, cause abnormal blood sugar levels. Combined with the widespread misconception that Type 1 only happens in children, this similarity leads to a serious problem: up to 20% of adults with Type 1 diabetes are initially misdiagnosed with Type 2. Since nearly half of all new Type 1 diagnoses occur in adults, this means many people are getting the wrong treatment plan—with potentially serious consequences.

Researchers at Breakthrough T1D and IQVIA, a global provider of clinical research and analytics services, recently tested whether artificial intelligence could spot Type 1 cases hiding in medical records labeled as Type 2. The team trained machine learning models using a large database of ambulatory electronic medical records, looking for patients initially diagnosed with Type 2 diabetes who were later found to have Type 1.

The results, now published, show promise for using AI as a safety net. By analyzing patterns in patient data, these algorithms can flag cases that warrant a second look—potentially catching misdiagnoses before wrong treatment causes harm.

Researchers have also validated a more direct diagnostic tool: a urine test measuring urinary C-peptide creatinine ratio (UCPCR). C-peptide is a marker of insulin production; people with Type 1 produce little to none, while those with Type 2 typically produce more.

A study published in 2025 found that UCPCR accurately distinguished Type 1 from Type 2 in adult patients. The test is non-invasive—just a urine sample—and costs 90% less than traditional blood tests like serum C-peptide or autoantibody panels. A UCPCR value below 0.25 nmol/mmol reliably identified Type 1 diabetes, making it a practical option for clinical settings seeking accurate, affordable diagnosis.

Better diagnostic tools address a real gap in adult diabetes care. Whether through AI algorithms that review medical records or simple urine tests done in the clinic, the goal is the same: ensuring adults with Type 1 diabetes receive the insulin therapy they need—and avoiding years of ineffective Type 2 management.

If you were diagnosed with Type 2 diabetes as an adult and feel your treatment isn't working well, it's worth asking your doctor whether a Type 1 misdiagnosis is possible. These new tools make that conversation easier to have.

Origin: breakthrought1d.org (News report). Evidence: News report, corroborated with 4 indexed studies. Type1Cure is an information and intelligence hub, not a medical advice service. This article summarizes published research and does not provide diagnosis, treatment, or personal medical guidance. Always talk to your own care team before changing anything about your Type 1 diabetes management.