• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

个体内肾脏指标的变异性。

Within-person variability in kidney measures.

机构信息

Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21287, USA.

出版信息

Am J Kidney Dis. 2013 May;61(5):716-22. doi: 10.1053/j.ajkd.2012.11.048. Epub 2013 Jan 20.

DOI:10.1053/j.ajkd.2012.11.048
PMID:23337799
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3628297/
Abstract

BACKGROUND

Our objective was to quantify short-term total within-person variability in standard and nontraditional kidney measures using national data.

STUDY DESIGN

Repeated examination study of serum and urine kidney measures.

SETTING & PARTICIPANTS: Participants 18 years or older in the Third National Health and Nutrition Examination Survey (NHANES III) who had repeated blood and urine samples collected during visits occurring approximately 18 days apart.

MEASUREMENTS

Standardized serum creatinine, standardized cystatin C, β-trace protein (BTP), β(2)-microglobulin (B2M), and urine albumin and creatinine. We calculated the within-person coefficient of variation (CV(w)), which includes both biological and analytical variability. We also evaluated the impact of variability on estimates of the prevalence of reduced estimated glomerular filtration rate and albuminuria.

RESULTS

Serum cystatin C level demonstrated the lowest short-term within-person variability (CV(w) = 6.8%). Serum creatinine and B2M levels (CV(w) = 7.6% and 8.4%, respectively) also had low variability. BTP level had the most variability of the serum markers (CV(w) = 11.6%). As expected, urine albumin and urine creatinine measurements showed high variability (CV(w) >30% for both); however, albumin-creatinine ratio performed much better than either measure alone, with CV(w) of 11.3%. The effect of short-term variability on the prevalence of reduced estimated glomerular filtration rate was moderate, with an ~20% lower prevalence when defined based on single measurements compared to repeated application of the same test approximately 18 days apart. Repeated testing for albuminuria had a larger effect, showing a 33% lower prevalence of albuminuria when repeated testing was applied.

LIMITATIONS

Only 2 measurements available. General population with low prevalence of kidney disease.

CONCLUSIONS

Our results suggest that creatinine, cystatin C, and B2M levels have similarly low short-term variability. BTP level was more variable compared with the other serum filtration markers. Urine albumin and creatinine levels were highly variable and may benefit from repeated assessments to reduce the misclassification of albuminuria.

摘要

背景

本研究旨在利用国家数据量化标准和非传统肾脏指标的短期个体内总变异性。

研究设计

血清和尿液肾脏指标的重复检测研究。

设置和参与者

在第三次全国健康和营养调查(NHANES III)中,年龄在 18 岁或以上的参与者,他们在大约相隔 18 天的访问中重复采集血液和尿液样本。

测量

标准化血清肌酐、标准化胱抑素 C、β-痕迹蛋白(BTP)、β(2)-微球蛋白(B2M)以及尿液白蛋白和肌酐。我们计算了个体内变异系数(CV(w)),它包括生物学和分析变异性。我们还评估了变异性对估算肾小球滤过率降低和蛋白尿患病率估计的影响。

结果

血清胱抑素 C 水平的个体内短期变异性最低(CV(w) = 6.8%)。血清肌酐和 B2M 水平(CV(w)分别为 7.6%和 8.4%)的变异性也较低。BTP 水平的血清标志物变异性最大(CV(w) = 11.6%)。正如预期的那样,尿液白蛋白和尿液肌酐测量值显示出很高的变异性(两者的 CV(w)均大于 30%);然而,白蛋白-肌酐比值的表现明显优于单独使用任何一种测量值,其 CV(w)为 11.3%。短期变异性对估算肾小球滤过率降低的患病率的影响适中,与基于单次测量定义的患病率相比,大约 18 天重复应用相同的测试时,患病率降低约 20%。反复检测蛋白尿的效果更大,当应用重复检测时,蛋白尿的患病率降低 33%。

局限性

只有 2 次测量值可用。具有低肾脏疾病患病率的一般人群。

结论

我们的研究结果表明,肌酐、胱抑素 C 和 B2M 水平具有相似的短期变异性低。BTP 水平与其他血清滤过标志物相比更具变异性。尿液白蛋白和肌酐水平高度可变,可能受益于重复评估以减少蛋白尿的错误分类。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6b7/3628297/cf7c9ceb92ab/nihms438024f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6b7/3628297/cf7c9ceb92ab/nihms438024f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6b7/3628297/cf7c9ceb92ab/nihms438024f1.jpg

相似文献

1
Within-person variability in kidney measures.个体内肾脏指标的变异性。
Am J Kidney Dis. 2013 May;61(5):716-22. doi: 10.1053/j.ajkd.2012.11.048. Epub 2013 Jan 20.
2
Biological Variability of Estimated GFR and Albuminuria in CKD.估算肾小球滤过率和蛋白尿在慢性肾脏病中的生物学变异性。
Am J Kidney Dis. 2018 Oct;72(4):538-546. doi: 10.1053/j.ajkd.2018.04.023. Epub 2018 Jul 18.
3
GFR Estimation Using β-Trace Protein and β2-Microglobulin in CKD.在慢性肾脏病中使用β-微量蛋白和β2-微球蛋白估算肾小球滤过率
Am J Kidney Dis. 2016 Jan;67(1):40-8. doi: 10.1053/j.ajkd.2015.07.025. Epub 2015 Sep 9.
4
Non-GFR Determinants of Low-Molecular-Weight Serum Protein Filtration Markers in CKD.慢性肾脏病中低分子量血清蛋白滤过标志物的非肾小球滤过率决定因素
Am J Kidney Dis. 2016 Dec;68(6):892-900. doi: 10.1053/j.ajkd.2016.07.021. Epub 2016 Sep 20.
5
Glomerular Filtration Rate Estimation Using β-Microglobulin and β-Trace Protein in Adults With Solid Tumors: A Prospective Cross-Sectional Study.利用β-微球蛋白和β-痕迹蛋白估算成人实体瘤患者的肾小球滤过率:一项前瞻性横断面研究。
Am J Kidney Dis. 2024 Sep;84(3):339-348.e1. doi: 10.1053/j.ajkd.2024.01.532. Epub 2024 Mar 26.
6
Non-GFR Determinants of Low-Molecular-Weight Serum Protein Filtration Markers in the Elderly: AGES-Kidney and MESA-Kidney.老年人低分子量血清蛋白滤过标志物的非肾小球滤过率决定因素:AGES-肾脏研究和MESA-肾脏研究
Am J Kidney Dis. 2017 Sep;70(3):406-414. doi: 10.1053/j.ajkd.2017.03.021. Epub 2017 May 24.
7
Novel markers of kidney function as predictors of ESRD, cardiovascular disease, and mortality in the general population.新型肾功能标志物对一般人群终末期肾病、心血管疾病和死亡的预测作用。
Am J Kidney Dis. 2012 May;59(5):653-62. doi: 10.1053/j.ajkd.2011.11.042. Epub 2012 Feb 4.
8
Association of kidney function and albuminuria with prevalent and incident hypertension: the Atherosclerosis Risk in Communities (ARIC) study.肾功能及蛋白尿与高血压患病率和发病率的关联:社区动脉粥样硬化风险(ARIC)研究
Am J Kidney Dis. 2015 Jan;65(1):58-66. doi: 10.1053/j.ajkd.2014.06.025. Epub 2014 Aug 21.
9
Filtration Markers as Predictors of ESRD and Mortality: Individual Participant Data Meta-Analysis.滤过标志物作为终末期肾病和死亡的预测因子:个体参与者数据荟萃分析。
Clin J Am Soc Nephrol. 2017 Jan 6;12(1):69-78. doi: 10.2215/CJN.03660316. Epub 2016 Nov 10.
10
Novel filtration markers as predictors of all-cause and cardiovascular mortality in US adults.新型滤过标志物可预测美国成年人全因和心血管死亡率。
Am J Kidney Dis. 2013 Jul;62(1):42-51. doi: 10.1053/j.ajkd.2013.01.016. Epub 2013 Mar 19.

引用本文的文献

1
Biomarkers of Kidney Function and Injury Across Fire Seasons and During a Mid-Season Fire Incident in the Wildland Firefighter Exposure and Health Effect (WFFEHE) Study.在野外消防员暴露与健康效应(WFFEHE)研究中,跨火灾季节及火灾季中期火灾事件期间的肾功能和损伤生物标志物。
Am J Ind Med. 2025 Aug 3. doi: 10.1002/ajim.70006.
2
Elevated Exposure to Air Pollutants Accelerates Primary Glomerular Disease Progression.暴露于空气污染物增加会加速原发性肾小球疾病进展。
Kidney Int Rep. 2024 May 18;9(8):2527-2536. doi: 10.1016/j.ekir.2024.05.013. eCollection 2024 Aug.
3
Accuracy of glomerular filtration rate estimation using creatinine and cystatin C for identifying and monitoring moderate chronic kidney disease: the eGFR-C study.

本文引用的文献

1
Calibration of cystatin C in the National Health and Nutrition Examination Surveys (NHANES).国家健康与营养检查调查(NHANES)中胱抑素C的校准
Am J Kidney Dis. 2013 Feb;61(2):353-4. doi: 10.1053/j.ajkd.2012.09.013. Epub 2012 Nov 21.
2
Estimating glomerular filtration rate from serum creatinine and cystatin C.基于血清肌酐和胱抑素 C 估算肾小球滤过率。
N Engl J Med. 2012 Jul 5;367(1):20-9. doi: 10.1056/NEJMoa1114248.
3
The effects of freeze-thaw on β-trace protein and β2-microglobulin assays after long-term sample storage.
应用肌酐和胱抑素 C 估算肾小球滤过率识别和监测中度慢性肾脏病的准确性:eGFR-C 研究。
Health Technol Assess. 2024 Jul;28(35):1-169. doi: 10.3310/HYHN1078.
4
The relationship between low levels of albuminuria and mortality among adults without major cardiovascular risk factors.无主要心血管危险因素的成年人中微量白蛋白尿与死亡率之间的关系。
Eur J Prev Cardiol. 2024 Dec 4;31(17):2046-2055. doi: 10.1093/eurjpc/zwae189.
5
Biological variation in the estimated glomerular filtration rate of healthy individuals within 24 h calculated using 2021CKD-EPI equations.2021CKD-EPI 方程计算的 24 小时内健康个体估算肾小球滤过率的生物学变异。
Ir J Med Sci. 2024 Jun;193(3):1613-1620. doi: 10.1007/s11845-024-03621-9. Epub 2024 Feb 3.
6
The relationship between low levels of albuminuria and cardiovascular mortality among apparently healthy adults.看似健康的成年人中低水平蛋白尿与心血管死亡率之间的关系。
medRxiv. 2023 Dec 24:2023.12.21.23300378. doi: 10.1101/2023.12.21.23300378.
7
Biological variation in the serum and urine kidney injury markers of a healthy population measured within 24 hours.在 24 小时内测量的健康人群血清和尿液肾损伤标志物的生物学变异。
BMC Nephrol. 2022 May 24;23(1):195. doi: 10.1186/s12882-022-02819-2.
8
Impact of random variation in albuminuria and estimated glomerular filtration rate on patient enrolment and duration of clinical trials in nephrology.白蛋白尿和估计肾小球滤过率的随机变异对肾脏病学临床试验入组患者和持续时间的影响。
Diabetes Obes Metab. 2022 Jun;24(6):983-990. doi: 10.1111/dom.14660. Epub 2022 Feb 21.
9
Graft Function Variability and Slope and Kidney Transplantation Outcomes.移植肾功能变异性、斜率与肾移植结局
Kidney Int Rep. 2021 Mar 30;6(6):1642-1652. doi: 10.1016/j.ekir.2021.03.880. eCollection 2021 Jun.
10
Effect of estimating equations for glomerular filtration rate on novel surrogate markers for renal outcome.肾小球滤过率估算方程对肾脏结局新型替代标志物的影响。
Kidney Res Clin Pract. 2021 Jun;40(2):220-230. doi: 10.23876/j.krcp.20.210. Epub 2021 Jun 9.
长期储存后冻融对β-痕迹蛋白和β2-微球蛋白检测的影响。
Clin Biochem. 2012 Jun;45(9):694-6. doi: 10.1016/j.clinbiochem.2012.02.027. Epub 2012 Mar 9.
4
Comparison of measured GFR, serum creatinine, cystatin C, and beta-trace protein to predict ESRD in African Americans with hypertensive CKD.比较测量肾小球滤过率、血清肌酐、胱抑素 C 和β-痕迹蛋白在预测非裔美国人高血压性慢性肾脏病终末期肾病中的作用。
Am J Kidney Dis. 2011 Dec;58(6):886-93. doi: 10.1053/j.ajkd.2011.07.018. Epub 2011 Sep 22.
5
Expressing the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) cystatin C equations for estimating GFR with standardized serum cystatin C values.使用标准化血清胱抑素C值表达用于估算肾小球滤过率(GFR)的CKD-EPI(慢性肾脏病流行病学协作组)胱抑素C方程。
Am J Kidney Dis. 2011 Oct;58(4):682-4. doi: 10.1053/j.ajkd.2011.05.019. Epub 2011 Aug 19.
6
Chronic kidney disease.慢性肾脏病。
Lancet. 2012 Jan 14;379(9811):165-80. doi: 10.1016/S0140-6736(11)60178-5. Epub 2011 Aug 15.
7
Temporal trends in the prevalence of diabetic kidney disease in the United States.美国糖尿病肾病患病率的时间趋势。
JAMA. 2011 Jun 22;305(24):2532-9. doi: 10.1001/jama.2011.861.
8
β-trace protein versus cystatin C: which is a better surrogate marker of renal function versus prognostic indicator in cardiovascular diseases?β-微球蛋白与胱抑素C:在心血管疾病中,哪一个是更好的肾功能替代标志物和预后指标?
J Am Coll Cardiol. 2011 Feb 15;57(7):859-60. doi: 10.1016/j.jacc.2010.09.052.
9
The definition, classification, and prognosis of chronic kidney disease: a KDIGO Controversies Conference report.慢性肾脏病的定义、分类和预后:KDIGO 争议会议报告。
Kidney Int. 2011 Jul;80(1):17-28. doi: 10.1038/ki.2010.483. Epub 2010 Dec 8.
10
Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis.估算肾小球滤过率和白蛋白尿与普通人群全因和心血管死亡率的关系:荟萃分析协作研究。
Lancet. 2010 Jun 12;375(9731):2073-81. doi: 10.1016/S0140-6736(10)60674-5. Epub 2010 May 17.