Objectives: We determined the contribution of multiple variables to predict arrhythmic death and total mortality risk in patients with coronary disease and left ventricular dysfunction. We then constructed an algorithm to predict risk of mortality and sudden death. Background: Many factors in addition to ejection fraction (EF) influence the prognosis of patients with coronary disease. However, there are few tools to use this information to guide clinical decisions. Methods: We evaluated the relationship between 25 variables and total mortality and arrhythmic death in 674 patients enrolled in the MUSTT (Multicenter Unsustained Tachycardia Trial) study that did not receive antiarrhythmic therapy. We then constructed risk-stratification algorithms to weight the prognostic impact of each variable on arrhythmic death and total mortality risk. Results: The variables having the greatest prognostic impact in multivariable analysis were functional class, history of heart failure, nonsustained ventricular tachycardia not related to bypass surgery, EF, age, left ventricular conduction abnormalities, inducible sustained ventricular tachycardia, enrollment as an inpatient, and atrial fibrillation. The model demonstrates that patients whose only risk factor is EF ≤30% have a predicted 2-year arrhythmic death risk <5%. Conclusions: Multiple variables influence arrhythmic death and total mortality risk. Patients with EF ≤30% but no other risk factor have low predicted mortality risk. Patients with EF >30% and other risk factors may have higher mortality and a higher risk of sudden death than some patients with EF ≤30%. Thus, risk of sudden death in patients with coronary disease depends on multiple variables in addition to EF.
ASJC Scopus subject areas
- Cardiology and Cardiovascular Medicine