评估高血压和左心室肥厚患者心血管事件风险的积分系统表:LIFE研究

D. Hille, S. Kjeldsen, S. Julius, K. Wachtell, P. Okin, R. Devereux
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引用次数: 1

摘要

我们的目的是评估一些容易获得的患者特征,如尿白蛋白排泄作为高血压和左心室肥厚患者心肌梗死、脑中风和心血管死亡的主要复合事件的预测因子,并为结果制定风险算法。在氯沙坦干预降低高血压终点(LIFE)研究中,“Cox比例风险”模型确定了对9193例老年高血压左室肥厚患者复合终点发生显著影响的基线变量。我们开发了一个风险分数表,通过调整从Framingham数据中开发的积分系统算法,将分数分配给各种风险因素,包括重要的年龄-性别相互作用项。Cox模型确定了终点风险的12个预测因子。由于年龄与性别的相互作用,年龄分值分别对女性和男性进行了计算。将由总分定义的风险估计值与由Cox模型确定的风险估计值进行比较,一致性的加权κ值为0.89。因此,一些患者特征预测高血压和左心室肥厚患者的心血管事件,其中年龄、性别和尿白蛋白排泄是最重要的。风险点表是一种直观的方法,可以比较心血管风险预测因子的相对贡献,并向患者和医生解释复杂的统计模型,如相互作用项。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Point System Table to Estimate the Risk of Cardiovascular Events in Patients with Hypertension and Left Ventricular Hypertrophy: The LIFE Study
We aimed to assess some readily available patient characteristics such as urinary albumin excretion as predictors of a primary composite event of myocardial infarction, cerebral stroke, and cardiovascular death among patients with hypertension and left ventricular hypertrophy, and develop risk algorithms for the outcomes. A “Cox proportional hazards” model identified the baseline variables that significantly affected the occurrence of the composite endpoint in 9193 elderly hypertensive patients with left ventricular hypertrophy in the Losartan Intervention For Endpoint reduction in hypertension (LIFE) study. We developed a risk point table, which assigned points to various risk factors, including the important age-gender interaction term, by adapting the point system algorithm developed from Framingham data. The Cox model identified 12 predictors of risk for the endpoint. Points for age were calculated separately for females and males due to the age-gender interaction. The risk estimates that were defined by total points were compared to those that were determined by the Cox model, and the weighted κ value for the agreement was 0.89. Thus, several patient characteristics predicted cardiovascular events in patients with hypertension and left ventricular hypertrophy, with age, gender, and urinary albumin excretion being the most important. The risk point table is an intuitive method to compare the relative contribution of the cardiovascular risk predictors and explain complicated statistical models such as the interaction term to patients and their physicians.
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