Buxton Alfred E, Lee Kerry L, Hafley Gail E, Pires Luis A, Fisher John D, Gold Michael R, Josephson Mark E, Lehmann Michael H, Prystowsky Eric N
Department of Medicine, Cardiology Division, Brown Medical School and Lifespan Academic Medical Center, Providence, Rhode Island 02905, USA.
J Am Coll Cardiol. 2007 Sep 18;50(12):1150-7. doi: 10.1016/j.jacc.2007.04.095. Epub 2007 Sep 4.
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.
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.
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.
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 < or =30% have a predicted 2-year arrhythmic death risk <5%.
Multiple variables influence arrhythmic death and total mortality risk. Patients with EF < or =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 < or =30%. Thus, risk of sudden death in patients with coronary disease depends on multiple variables in addition to EF.
我们确定了多个变量对冠心病合并左心室功能不全患者心律失常性死亡和总死亡风险预测的贡献。然后构建了一种算法来预测死亡和猝死风险。
除射血分数（EF）外，许多因素影响冠心病患者的预后。然而，几乎没有工具可利用这些信息来指导临床决策。
我们评估了参加多中心非持续性心动过速试验（MUSTT）且未接受抗心律失常治疗的674例患者中25个变量与总死亡率和心律失常性死亡之间的关系。然后构建风险分层算法，以权衡每个变量对心律失常性死亡和总死亡风险的预后影响。
多变量分析中具有最大预后影响的变量为心功能分级、心力衰竭病史、与搭桥手术无关的非持续性室性心动过速、EF、年龄、左心室传导异常、可诱发的持续性室性心动过速、住院登记以及心房颤动。该模型表明，仅危险因素为EF≤30%的患者预测2年心律失常性死亡风险<5%。
多个变量影响心律失常性死亡和总死亡风险。EF≤30%但无其他危险因素的患者预测死亡风险较低。EF>30%且有其他危险因素的患者可能比一些EF≤30%的患者有更高的死亡率和猝死风险。因此，冠心病患者的猝死风险除EF外还取决于多个变量。
