Impact of brachial-ankle pulse wave velocity and ankle-brachial blood pressure index on mortality in hemodialysis patients
Impact of brachial-ankle pulse wave velocity and ankle-brachial blood pressure index on mortality in hemodialysis patients
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DOI：
10.1053/j.ajkd.2005.06.016
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发表时间：
2005-10-01
影响因子：
13.2
通讯作者：
Nojima, Y
中科院分区：
文献类型：
--
作者：
Kitahara, T;Ono, K;Nojima, Y
背景：脉搏波速度（PWV）和踝肱血压指数（ABPI）是动脉粥样硬化的标志，两者都能预测血液透析患者的死亡率。然而，过去没有研究对这两个参数的临床有效性进行正面比较。与常规主动脉PWV相比，baPWV操作简单，易于临床应用。方法：为了明确baPWV与ABPI之间的关系并评估其预后价值，我们分析了785例血液透析患者，这些患者在基线时同时测量ABPI和baPWV，随访33.8 +/- 10.8个月。结果：785例患者中，131例死亡。Kaplan-Meier分析显示，从baPWV最低四分位数开始，全因死亡率逐渐显著增加（log-rank检验，41.8;P < 0.001）。然而，在Cox比例风险分析中，当ABPI作为协变量纳入时，baPWV的影响不显著。在该模型中，ABPI保持了较强的预测能力。当排除ABPI < 0.9的晚期外周动脉闭塞性疾病患者时，baPWV最高四分位数患者的全因死亡率风险比（风险比4.08,95%可信区间1.46 ~ 11.43,P < 0.007）和心血管死亡率风险比（风险比7.03,95%可信区间1.49 ~ 33.08,P < 0.014）显著增加。在该人群中，baPWV的预测能力独立于与动脉粥样硬化性疾病相关的其他协变量。结论：在头对头比较中，ABPI，而不是baPWV，在预测血液透析患者死亡率方面表现出很强的能力。然而，在ABPI大于0.9的患者中，baPWV可用于筛选高危人群。因此，通过baPWV和ABPI筛查血透患者为确定高危人群提供了补充信息。
Background: Pulse wave velocity (PWV) and ankle-brachial blood pressure index (ABPI) are markers for atherosclerosis, and each predicts mortality in patients undergoing hemodialysis. However, there have been no studies in the past that compared head-to-head the clinical validity of these 2 parameters. Compared with conventional aortic PWV, brachial-ankle PWV (baPWV) is considered simple and thereby easily applicable to clinical use. Methods: To clarify the relationship between baPWV and ABPI and assess their prognostic values, we analyzed 785 hemodialysis patients with a mean age of 60.2 +/- 12.5 (SD) years for whom ABPI and baPWV at baseline had been measured simultaneously and who were followed up for 33.8 +/- 10.8 months. Results: Of 785 patients, 131 deaths were recorded. In Kaplan-Meier analysis, all-cause mortality was progressively and significantly greater from the lowest quartile of baPWV onward (log-rank test, 41.8; P < 0.001). However, in Cox proportional hazards analysis, the impact of baPWV was insignificant when ABPI was included as a covariate. ABPI maintained strong predictive power in this model. When patients who had advanced peripheral arterial occlusive disease (ABPI < 0.9) were excluded from analysis, patients with the highest quartile of baPWV had significantly increased hazard ratios of all-cause (hazard ratio, 4.08; 95% confidence interval, 1.46 to 11.43; P < 0.007) and cardiovascular (hazard ratio, 7.03; 95% confidence interval, 1.49 to 33.08; P < 0.014) mortality. The predictive power of baPWV in this population was independent from other covariates associated with atherosclerotic disorders. Conclusion: In a head-to-head comparison, ABPI, but not baPWV, showed strong power in predicting the mortality of hemodialysis patients. However, baPWV was useful to pick a high-risk population in patients with ABPI greater than 0.9. Thus, screening hemodialysis patients by means of baPWV and ABPI provides complementary information in identifying a high-risk population.