Why the study?
Cardiovascular disease limits quality of life and survival, and its accelerated course in type 1 diabetes may challenge standard risk prediction models.
Do traditional cardiovascular disease risk prediction models accurately predict 10-year CVD risk in patients with type 1 diabetes?
Population
1311 participants with type 1 diabetes in the EDIC study
Comparison
FRS vs ASCVD vs AHA PREVENT vs ST1RE risk prediction models, plus CAC and HbA1c
Design
Cohort study analysis
Follow-up
30 yrs
Key result
In type 1 diabetes, observed 10-year CVD risk was 1.43 times higher than predicted by FRS (95% CI 1.36-1.49) and >2-fold higher than ASCVD and PREVENT predictions.
Authors
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Standard models may underestimate CVD risk in type 1 diabetes; leaves open whether CAC-enhanced scores improve outcomes.
Cohort (n=1,311)
Do traditional cardiovascular disease risk prediction models accurately predict 10-year CVD risk in patients with type 1 diabetes?
Relative Risk: 1.43 (95% CI 1.36–1.49)
Traditional cardiovascular risk prediction models significantly underestimate risk in patients with type 1 diabetes, highlighting the need for tailored risk estimation incorporating enhancers like CAC and HbA1c.
Trapani et al. (2026) conducted a cohort in Type 1 Diabetes (n=1,311). Traditional CVD risk prediction models (FRS, ASCVD, PREVENT, ST1RE) vs. Observed CVD incidence was evaluated on 10-year cardiovascular disease incidence compared to model-predicted risk (RR 1.43, 95% CI 1.36-1.49). In type 1 diabetes, observed 10-year CVD risk was 1.43 times higher than predicted by FRS (95% CI 1.36-1.49) and >2-fold higher than ASCVD and PREVENT predictions.
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