Predicting risk of cardiovascular events 1 to 3 years post‐myocardial infarction using a global registry

Background Risk prediction tools are lacking for patients with stable disease some years after myocardial infarction (MI). Hypothesis A practical long‐term cardiovascular risk index can be developed. Methods The long‐Term rIsk, Clinical manaGement and healthcare Resource utilization of stable coronary artery dISease in post‐myocardial infarction patients prospective global registry enrolled patients 1 to 3 years post‐MI (369 centers; 25 countries), all with ≥1 risk factor (age ≥65 years, diabetes mellitus requiring medication, second prior MI, multivessel coronary artery disease, or chronic non‐end‐stage kidney disease [CKD]). Self‐reported health was assessed with EuroQoL‐5 dimensions. Multivariable Poisson regression models were used to determine key predictors of the primary composite outcome (MI, unstable angina with urgent revascularization [UA], stroke, or all‐cause death) over 2 years. Results The primary outcome occurred in 621 (6.9%) of 9027 eligible patients: death 295 (3.3%), MI 195 (2.2%), UA 103 (1.1%), and stroke 58 (0.6%). All events accrued linearly. In a multivariable model, 11 significant predictors of primary outcome (age ≥65 years, diabetes, second prior MI, CKD, history of major bleed, peripheral arterial disease, heart failure, cardiovascular hospitalization (prior 6 months), medical management (index MI), on diuretic, and poor self‐reported health) were identified and combined into a user‐friendly risk index. Compared with lowest‐risk patients, those in the top 16% had a rate ratio of 6.9 for the primary composite, and 18.7 for all‐cause death (overall c‐statistic; 0.686, and 0.768, respectively). External validation was performed using the Australian Cooperative National Registry of Acute Coronary Care, Guideline Adherence and Clinical Events registry (c‐statistic; 0.748, and 0.849, respectively). Conclusions In patients >1‐year post‐MI, recurrent cardiovascular events and deaths accrue linearly. A simple risk index can stratify patients, potentially helping to guide management.