Study Explores Why Heart Disease Risk Is Difficult to Predict in Type 1 Diabetes - Video

What if your weight looks normal-but your heart risk tells a completely different story?

A new study in Nature Communications suggests that traditional measures like body mass index (BMI) may miss hidden cardiovascular dangers in people with Type 1 diabetes. Researchers analyzed data from nearly 44,000 patients across Europe and found that combining BMI with deeper metabolic markers can significantly improve how doctors predict the risk of cardiovascular disease.

People with Type 1 diabetes already face a higher risk of heart disease, even when their blood sugar appears well controlled. This makes early and accurate risk detection especially important. Instead of relying on BMI alone, the study used a “discordance” model—essentially comparing a person’s weight with what their internal biomarkers, such as cholesterol, blood pressure, and blood sugar, reveal about their health.

The findings were striking. A “hyperglycemic” profile—where blood sugar levels are high regardless of body weight—was far more common in Type 1 diabetes than in the general population. In fact, it appeared in over half of the patients studied. This group showed higher levels of HbA1c, a key marker of long-term blood sugar control, and carried a higher cardiovascular risk.

When researchers added these profiles to existing prediction tools like SCORE2, the accuracy of identifying major heart-related events improved in several groups, particularly among men. Even small improvements mattered: the model helped identify more high-risk individuals while reducing unnecessary treatments in others.

The study highlights a crucial shift in thinking—cardiovascular risk isn’t just about weight. For people with Type 1 diabetes, what’s happening inside the body may matter far more. By refining risk prediction, doctors could better target prevention strategies and catch complications earlier, ultimately improving long-term outcomes.

REFERENCE: Pazmino, S., Schmid, S., Blanch, J., et al. (2026). Precision cardiovascular risk prediction in type 1 diabetes: An IMI2 SOPHIA analysis. Nature Communications. DOI: https://doi.org/10.1038/s41467-026-72029-z. https://www.nature.com/articles/s41467-026-72029-z