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高尿酸血症对动态血压国际研究中心血管事件的预测价值。

Added predictive value of high uric acid for cardiovascular events in the Ambulatory Blood Pressure International Study.

机构信息

University of Perugia, Perugia, Italy.

Hospital S. Maria della Misericordia, Perugia, Italy.

出版信息

J Clin Hypertens (Greenwich). 2019 Jul;21(7):966-974. doi: 10.1111/jch.13584. Epub 2019 Jun 6.

Abstract

The prognostic value of uric acid (UA) for cardiovascular events (CVE) is still debated. Our purpose was to investigate the association between UA and CVE in 5243 participants of the ABP-International study with the main aim of identifying optimal sex-specific cut-points. In multivariable Cox analyses, the relationship between CVE and UA as a continuous variable was modeled by including both linear and nonlinear terms. Survival models were also estimated with UA as a categorical variable. Optimal UA cut-points were determined using an outcome-oriented approach. During a median follow-up of 5.9 years, there were 423 CVE (93 fatal). In age- and sex-adjusted Cox models, UA as a continuous variable was a significant predictor of CVE in all individuals and in men and women considered separately. The relationship between UA and CVE was linear (P-value for nonlinearity 0.54 and 0.80 for men and women, respectively). For each 1 mg/dL increase in UA, the relative hazard increase was 16% in men and 19% in women. In fully adjusted models, UA remained a significant predictor of CVE in the whole study cohort. The optimal cut-point best separating patients at low and high risk of CVE was 6.3 mg/dL for men and 4.4 mg/dL for women. Subjects with high UA had a 38% greater risk of CVE. In a sex-specific analysis, the association remained significant only in men (hazard ratio, 1.47; P < 0.01). In conclusion, high UA is an independent predictor for subsequent CVE and significantly improves risk discrimination and reclassification over the baseline multivariable model.

摘要

尿酸(UA)对心血管事件(CVE)的预后价值仍存在争议。我们的目的是在 ABP-International 研究的 5243 名参与者中调查 UA 与 CVE 之间的关系,主要目的是确定最佳的性别特异性切点。在多变量 Cox 分析中,通过包含线性和非线性项,对 CVE 与 UA 作为连续变量之间的关系进行建模。还使用 UA 作为分类变量估计生存模型。使用面向结果的方法确定最佳 UA 切点。在中位数为 5.9 年的随访期间,有 423 例 CVE(93 例致死)。在年龄和性别调整的 Cox 模型中,UA 作为连续变量是所有个体以及单独考虑的男性和女性发生 CVE 的重要预测因素。UA 与 CVE 之间的关系是线性的(非线性的 P 值分别为 0.54 和 0.80,男性和女性)。UA 每增加 1mg/dL,男性和女性的相对危险度分别增加 16%和 19%。在完全调整的模型中,UA 仍然是整个研究队列中 CVE 的重要预测因素。最佳切点最好将低危和高危 CVE 的患者区分开来,男性为 6.3mg/dL,女性为 4.4mg/dL。UA 较高的患者发生 CVE 的风险增加 38%。在性别特异性分析中,这种关联仅在男性中仍然显著(危险比,1.47;P<0.01)。总之,高 UA 是随后发生 CVE 的独立预测因子,并且在基线多变量模型的基础上显著提高了风险区分和重新分类能力。

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