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胱抑素 C 和基于肌酐的慢性肾脏病定义对 20 个人群队列和 3 个疾病队列中的心血管风险评估的贡献:BiomarCaRE 项目。

Contribution of cystatin C- and creatinine-based definitions of chronic kidney disease to cardiovascular risk assessment in 20 population-based and 3 disease cohorts: the BiomarCaRE project.

机构信息

Institute of Epidemiology and Medical Biometry, Ulm University, Helmholtzstr. 22, 89081, Ulm, Germany.

Division of Clinical Epidemiology and Aging Research C070, German Cancer Research Center (DKFZ), Heidelberg, Germany.

出版信息

BMC Med. 2020 Nov 9;18(1):300. doi: 10.1186/s12916-020-01776-7.

DOI:
10.1186/s12916-020-01776-7
PMID:33161898
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7650190/
Abstract

BACKGROUND

Chronic kidney disease has emerged as a strong cardiovascular risk factor, and in many current guidelines, it is already considered as a coronary heart disease (CHD) equivalent. Routinely, creatinine has been used as the main marker of renal function, but recently, cystatin C emerged as a more promising marker. The aim of this study was to assess the comparative cardiovascular and mortality risk of chronic kidney disease (CKD) using cystatin C-based and creatinine-based equations of the estimated glomerular filtration rate (eGFR) in participants of population-based and disease cohorts.

METHODS

The present study has been conducted within the BiomarCaRE project, with harmonized data from 20 population-based cohorts (n = 76,954) from 6 European countries and 3 cardiovascular disease (CVD) cohorts (n = 4982) from Germany. Cox proportional hazards models were used to assess hazard ratios (HRs) for the various CKD definitions with adverse outcomes and mortality after adjustment for the Systematic COronary Risk Evaluation (SCORE) variables and study center. Main outcome measures were cardiovascular diseases, cardiovascular death, and all-cause mortality.

RESULTS

The overall prevalence of CKD stage 3-5 by creatinine- and cystatin C-based eGFR, respectively, was 3.3% and 7.4% in the population-based cohorts and 13.9% and 14.4% in the disease cohorts. CKD was an important independent risk factor for subsequent CVD events and mortality. For example, in the population-based cohorts, the HR for CVD mortality was 1.72 (95% CI 1.53 to 1.92) with creatinine-based CKD and it was 2.14 (95% CI 1.90 to 2.40) based on cystatin-based CKD compared to participants without CKD. In general, the HRs were higher for cystatin C-based CKD compared to creatinine-based CKD, for all three outcomes and risk increased clearly below the conventional threshold for CKD, also in older adults. Net reclassification indices were larger for a cystatin-C based CKD definition. Differences in HRs (between the two CKD measures) in the disease cohorts were less pronounced than in the population-based cohorts.

CONCLUSION

CKD is an important risk factor for subsequent CVD events and total mortality. However, point estimates of creatinine- and cystatin C-based CKD differed considerably between low- and high-risk populations. Especially in low-risk settings, the use of cystatin C-based CKD may result in more accurate risk estimates and have better prognostic value.

摘要

背景

慢性肾脏病已成为心血管疾病的一个强有力的危险因素,在许多现行指南中,它已被视为冠心病(CHD)的等同物。目前,肌酐通常被用作肾功能的主要标志物,但最近,胱抑素 C 已成为一种更有前途的标志物。本研究旨在评估基于胱抑素 C 和基于肌酐的肾小球滤过率(eGFR)估算方程的慢性肾脏病(CKD)在人群队列和疾病队列中的心血管和死亡率风险的比较。

方法

本研究在 BiomarCaRE 项目中进行,该项目的数据来自 6 个欧洲国家的 20 个人群队列(n=76954)和德国的 3 个心血管疾病(CVD)队列(n=4982)。使用 Cox 比例风险模型评估各种 CKD 定义的风险比(HRs)与不良结局和死亡率之间的关系,这些结局和死亡率在调整了系统性冠状动脉风险评估(SCORE)变量和研究中心后进行评估。主要观察终点为心血管疾病、心血管死亡和全因死亡率。

结果

在人群队列中,基于肌酐和胱抑素 C 的 eGFR 的 CKD 第 3-5 期的总体患病率分别为 3.3%和 7.4%,在疾病队列中分别为 13.9%和 14.4%。CKD 是随后发生 CVD 事件和死亡的重要独立危险因素。例如,在人群队列中,基于肌酐的 CKD 的 CVD 死亡率 HR 为 1.72(95%CI 1.53 至 1.92),而基于胱抑素的 CKD 的 HR 为 2.14(95%CI 1.90 至 2.40),与无 CKD 的参与者相比。一般来说,基于胱抑素 C 的 CKD 的 HR 高于基于肌酐的 CKD,对于所有三个结局,风险在 CKD 的传统阈值以下明显增加,在老年人中也是如此。基于胱抑素 C 的 CKD 定义的净重新分类指数较大。疾病队列中两种 CKD 指标(之间)的 HR 差异小于人群队列。

结论

CKD 是随后发生 CVD 事件和总死亡率的重要危险因素。然而,基于肌酐和胱抑素 C 的 CKD 的点估计值在低风险和高风险人群之间存在显著差异。特别是在低风险环境中,使用基于胱抑素 C 的 CKD 可能会产生更准确的风险估计,并具有更好的预后价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/852e/7650190/8cc9017e3db4/12916_2020_1776_Fig5_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/852e/7650190/8cc9017e3db4/12916_2020_1776_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/852e/7650190/c23322adb353/12916_2020_1776_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/852e/7650190/96bc87f67fe4/12916_2020_1776_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/852e/7650190/06ad15aa0b77/12916_2020_1776_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/852e/7650190/9aee9e795ae9/12916_2020_1776_Fig4_HTML.jpg
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