Predicting cardiovascular disease risk across the atherosclerotic disease continuum

Aims Cardiovascular disease (CVD) guidelines dichotomize populations into primary and secondary prevention. We sought to develop a risk equation for secondary prevention of CVD that complements existing equations for primary prevention of CVD, and to describe the distributions of CVD risk across the population. Methods and results Adults aged 30-79 years who had routine CVD risk assessment in 2007-16 were identified from a large primary care cohort (PREDICT) with linkage to national and regional datasets. The 5-year risk of developing CVD among people without atherosclerotic CVD (ASCVD) was calculated using published equations (PREDICT-1 degrees). A new risk equation (PREDICT-2 degrees) was developed from Cox regression models to estimate the 5-year risk of CVD event recurrence among patients with known ASCVD. The outcome for both equations was hospitalization for a CVD event or cardiovascular death. Of the 475 161 patients, 12% (57 061) had ASCVD. For those without ASCVD, median (interquartile range) 5-year risks with the PREDICT-1 degrees score were women 2.2% (1.2-4.2%), men 3.5% (2.0-6.6%), and whole group 2.9% (1.6-5.5%). For those with ASCVD, the 5-year risks with the new PREDICT-2 degrees equation were women 21% (15-33%), men 23% (16-35%), and whole group 22% (16-34%). Conclusion We developed CVD risk scores for people with ASCVD (PREDICT-2 degrees) to complement the PREDICT-1 degrees scores. Median CVD risk is eight-fold higher among those with ASCVD than those without; however, there was overlap and the widest distribution of CVD risk was among people with ASCVD. This study describes a CVD risk continuum and the limitations of a 'one size fits all' approach to assessing risk in people with ASCVD.

Automated summary

This study developed a CVD risk score for individuals with ASCVD to complement existing scores for primary prevention. The median CVD risk for those with ASCVD is eight times higher than those without, but there is overlap and the widest distribution of CVD risk is among individuals with ASCVD.