Prediction of major vascular events after stroke: the stroke prevention by aggressive reduction in cholesterol levels trial.
BACKGROUND: Identifying patients with recent stroke or transient ischemic attack (TIA) at high risk of major vascular events (MVEs; stroke, myocardial infarction, or vascular death) may help optimize the intensity of secondary preventive interventions. We evaluated the relationships between the baseline Framingham Coronary Risk Score (FCRS) and a novel risk prediction model and with the occurrence of MVEs after stroke or TIA in subjects enrolled in the Stroke Prevention by Aggressive Reduction in Cholesterol Level (SPARCL) trial. METHODS: Data from the 4731 subjects enrolled in the SPARCL study were analyzed. Hazard ratios (HRs) from Cox regression models were used to determine the risk of subsequent MVEs based on the FCRS predicting 20% or more 10-year coronary heart disease risk. The novel risk model was derived based on multivariable modeling with backward selection. Model discrimination (c-statistics) was assessed using the areas under the receiver operating characteristic curves. RESULTS: Of 3969 subjects with complete data, 27% had a baseline FCRS of 20% or more. In multivariable analysis, an FCRS of 20% or more was associated with twice the risk of subsequent MVEs (HR = 1.92, 95% confidence interval [CI]: 1.63-2.27). The novel model based on a multivariable analysis included age (HR = 1.37, 95% CI: 1.25-1.51 per 10 years), diabetes (HR = 1.82, 95% CI: 1.51-2.18), male sex (HR = 1.35, 95% CI: 1.12-1.61), and an apolipoprotein (APO)-B/APO-A1 ratio (HR = 1.56, 95% CI: 1.16-2.11). The c-statistic was .58 (95% CI: .55-.60) for the FCRS of 20% or more and .65 (95% CI: .63-.67) for the novel model. CONCLUSIONS: Both a baseline FCRS of 20% or more and a novel predictive model were associated with future MVEs in SPARCL trial subjects. The novel model needs to be validated, and the benefits of using either the FCRS or the novel model in clinical practice needs to be assessed.
Ovbiagele, B; Goldstein, LB; Amarenco, P; Messig, M; Sillesen, H; Callahan, A; Hennerici, MG; Zivin, J; Welch, KMA; SPARCL Investigators,
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