Redwood S R, Odemuyiwa O, Hnatkova K, Staunton A, Poloniecki I, Camm A J, Malik M
Department of Cardiological Sciences, St. George's Hospital Medical School, London, U.K.
Eur Heart J. 1997 Aug;18(8):1278-87. doi: 10.1093/oxfordjournals.eurheartj.a015439.
To evaluate the predictive value and optimum dichotomy limits for different combinations of prognostic indicators for the prediction of arrhythmic events and cardiac mortality in post-infarction patients.
Studies of new interventions based on risk stratification after myocardial infarction have often used a single variable as a predictor of risk. However, whether the dichotomy limits of these single variables, derived from univariate analyses, should be altered when such variables are combined for the prediction of risk after myocardial infarction has not been examined.
Left ventricular ejection fraction, signal-averaged electrocardiography, heart rate variability index, mean heart rate and ventricular extrasystole frequency were recorded pre-discharge in 439 survivors of their first myocardial infarction. Arrhythmic events and cardiac mortality were recorded during 1 year (range 1-6 years) follow-up.
During follow-up for at least 1 year, there were 25 cardiac deaths and 23 arrhythmic events. Different optimum dichotomy limits were obtained for the prediction of cardiac mortality vs arrhythmic events, for different combinations of variables, for different selected levels of sensitivity and for different numbers of variables abnormal before identification of those at risk. The dichotomy limit of the heart rate variability index for the prediction of events appeared to be the least affected by the inclusion of other variables. For example, when predicting arrhythmic events using combinations of left ventricular ejection fraction and/or heart rate variability, the optimum dichotomy limits when each variable was used alone was 32% and 18 units respectively; 43% and 18 units when either left ventricular ejection fraction or heart rate variability are required to be abnormal, and 52% and 19 units when both are required to be abnormal before identification of those at risk of arrhythmic events.
Dichotomy limits derived from univariate analyses do not optimally predict events when used in the multivariate setting. Risk stratification can be improved by using several variables in combination and is further improved by using dichotomy limits of these variables which are different from those used in or derived from univariate analyses.
评估不同组合的预后指标对心肌梗死后患者心律失常事件和心脏死亡率预测的预测价值及最佳二分法界限。
基于心肌梗死后风险分层的新干预措施研究通常使用单一变量作为风险预测指标。然而，当这些来自单变量分析的单一变量组合用于预测心肌梗死后风险时，其二分法界限是否应改变尚未得到研究。
在439例首次心肌梗死幸存者出院前记录左心室射血分数、信号平均心电图、心率变异性指数、平均心率和室性早搏频率。在1年（范围1 - 6年）随访期间记录心律失常事件和心脏死亡率。
在至少1年的随访期间，有25例心脏死亡和23例心律失常事件。对于心脏死亡率与心律失常事件的预测、不同变量组合、不同选定的敏感性水平以及在识别有风险者之前不同数量的异常变量，获得了不同的最佳二分法界限。心率变异性指数预测事件的二分法界限似乎受其他变量纳入的影响最小。例如，当使用左心室射血分数和/或心率变异性组合预测心律失常事件时，每个变量单独使用时的最佳二分法界限分别为32%和18单位；当左心室射血分数或心率变异性其中之一需要异常时为43%和18单位，当两者在识别心律失常事件风险者之前都需要异常时为52%和19单位。
单变量分析得出的二分法界限在多变量环境中使用时不能最佳地预测事件。通过组合使用多个变量可改善风险分层，并且通过使用与单变量分析中使用或推导的不同的这些变量的二分法界限可进一步改善。
