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慢性肾脏病 3 期患者皮肤自发荧光与心血管事件及全因死亡率的相关性:一项前瞻性队列研究。

The association of skin autofluorescence with cardiovascular events and all-cause mortality in persons with chronic kidney disease stage 3: A prospective cohort study.

机构信息

Centre for Kidney Research and Innovation, Division of Medical Sciences and Graduate Entry Medicine, School of Medicine, University of Nottingham, Derby, United Kingdom.

Renal Unit, Royal Derby Hospital, Derby, United Kingdom.

出版信息

PLoS Med. 2020 Jul 13;17(7):e1003163. doi: 10.1371/journal.pmed.1003163. eCollection 2020 Jul.

DOI:10.1371/journal.pmed.1003163
PMID:32658890
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7357739/
Abstract

BACKGROUND

Tissue advanced glycation end product (AGE) accumulation has been proposed as a marker of cumulative metabolic stress that can be assessed noninvasively by measurement of skin autofluorescence (SAF). In persons on haemodialysis, SAF is an independent risk factor for cardiovascular events (CVEs) and all-cause mortality (ACM), but data at earlier stages of chronic kidney disease (CKD) are inconclusive. We investigated SAF as a risk factor for CVEs and ACM in a prospective study of persons with CKD stage 3.

METHODS AND FINDINGS

Participants with estimated glomerular filtration rate (eGFR) 59 to 30 mL/min/1.73 m2 on two consecutive previous blood tests were recruited from 32 primary care practices across Derbyshire, United Kingdom between 2008 and 2010. SAF was measured in participants with CKD stage 3 at baseline, 1, and 5 years using an AGE reader (DiagnOptics). Data on hospital admissions with CVEs (based on international classification of diseases [ICD]-10 coding) and deaths were obtained from NHS Digital. Cox proportional hazards models were used to investigate baseline variables associated with CVEs and ACM. A total of 1,707 of 1,741 participants with SAF readings at baseline were included in this analysis: The mean (± SD) age was 72.9 ± 9.0 years; 1,036 (60.7%) were female, 1,681 (98.5%) were of white ethnicity, and mean (±SD) eGFR was 53.5 ± 11.9 mL/min/1.73 m2. We observed 319 deaths and 590 CVEs during a mean of 6.0 ± 1.5 and 5.1 ± 2.2 years of observation, respectively. Higher baseline SAF was an independent risk factor for CVEs (hazard ratio [HR] 1.12 per SD, 95% CI 1.03-1.22, p = 0.01) and ACM (HR 1.16, 95% CI 1.03-1.30, p = 0.01). Additionally, increase in SAF over 1 year was independently associated with subsequent CVEs (HR 1.11 per SD, 95% CI 1.00-1.22; p = 0.04) and ACM (HR 1.24, 95% CI 1.09-1.41, p = 0.001). We relied on ICD-10 codes to identify hospital admissions with CVEs, and there may therefore have been some misclassification.

CONCLUSIONS

We have identified SAF as an independent risk factor for CVE and ACM in persons with early CKD. These findings suggest that interventions to reduce AGE accumulation, such as dietary AGE restriction, may reduce cardiovascular risk in CKD, but this requires testing in prospective randomised trials. Our findings may not be applicable to more ethnically diverse or younger populations.

摘要

背景

组织晚期糖基化终产物 (AGE) 的积累被认为是一种累积代谢应激的标志物,可以通过测量皮肤自发荧光 (SAF) 进行非侵入性评估。在血液透析患者中,SAF 是心血管事件 (CVE) 和全因死亡率 (ACM) 的独立危险因素,但在慢性肾脏病 (CKD) 的早期阶段的数据尚无定论。我们研究了 SAF 作为 CKD 3 期患者发生 CVE 和 ACM 的危险因素。

方法和发现

在 2008 年至 2010 年间,我们从英国德比郡的 32 个基层医疗机构招募了两次连续血液检查中估计肾小球滤过率 (eGFR) 为 59 至 30 mL/min/1.73 m2 的参与者。在基线、1 年和 5 年时,使用 AGE 读取器(DiagnOptics)在 CKD 3 期患者中测量 SAF。通过 NHS Digital 获取关于基于国际疾病分类(ICD-10 编码)的 CVE 住院和死亡的数据。使用 Cox 比例风险模型研究与 CVE 和 ACM 相关的基线变量。共有 1707 名基线有 SAF 读数的 1741 名参与者被纳入本分析:平均(±SD)年龄为 72.9 ± 9.0 岁;1036 名(60.7%)为女性,1681 名(98.5%)为白种人,平均(±SD)eGFR 为 53.5 ± 11.9 mL/min/1.73 m2。我们观察到平均 6.0 ± 1.5 年和 5.1 ± 2.2 年的分别发生了 319 例死亡和 590 例 CVE。基线 SAF 较高是 CVE(危险比 [HR] 1.12/SD,95%CI 1.03-1.22,p=0.01)和 ACM(HR 1.16,95%CI 1.03-1.30,p=0.01)的独立危险因素。此外,SAF 在 1 年内的增加与随后的 CVE(HR 1.11/SD,95%CI 1.00-1.22;p=0.04)和 ACM(HR 1.24,95%CI 1.09-1.41,p=0.001)独立相关。我们依赖 ICD-10 代码来识别 CVE 的住院患者,因此可能存在一些分类错误。

结论

我们发现 SAF 是 CKD 早期患者发生 CVE 和 ACM 的独立危险因素。这些发现表明,减少 AGE 积累的干预措施,如饮食限制 AGE,可能会降低 CKD 的心血管风险,但这需要在前瞻性随机试验中进行测试。我们的研究结果可能不适用于种族更加多样化或更年轻的人群。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a713/7357739/24b9412cc93a/pmed.1003163.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a713/7357739/5ff7fd879e97/pmed.1003163.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a713/7357739/30b689c36651/pmed.1003163.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a713/7357739/24b9412cc93a/pmed.1003163.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a713/7357739/5ff7fd879e97/pmed.1003163.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a713/7357739/30b689c36651/pmed.1003163.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a713/7357739/24b9412cc93a/pmed.1003163.g003.jpg

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