Comparison of estimated glomerular filtration rate equations on prediction of mortality, kidney failure, and acute kidney injury.

IF 4.8 2区 医学 Q1 TRANSPLANTATION
Denise M J Veltkamp, Maarten B Rookmaaker, Mark C H de Groot, Marianne C Verhaar, Wouter W van Solinge, Saskia Haitjema, Robin W M Vernooij
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引用次数: 0

Abstract

Background: The CKD-EPIASR-NB2009 estimated glomerular filtration rate (eGFR) equation has shown substantial overestimation of GFR in Europeans, hence new equations have been developed. We examined the effect of introducing the European Kidney Function Consortium (EKFC) or Lund-Malmö revised (LMR) eGFR equations on KDIGO eGFR-category classification in a large cohort. We compared the EKFC and LMR equations with the CKD-EPIASR-NB2009 formula in view of discriminative ability of all-cause mortality, kidney failure with replacement therapy (KFRT), and acute kidney injury (AKI) risks across eGFR-categories.

Methods: Individuals ≥18y with a SCr measurement (December 2006-July 2024) at University Medical Center Utrecht, were included. Hazard ratios (HRs) were analysed for all outcomes per eGFR-category, per equation. Harrell's Concordance index (C-index) was used to assess the ability of risk discrimination across eGFR-categories. Whether reclassification between eGFR-categories was justified by the occurrence of events, was assessed with net reclassification improvement analysis.

Results: In total, 285,686 individuals were included. Compared with the CKD-EPIASR-NB2009 equation, the EKFC and LMR estimated GFR lower (mean -6.3(SD5.3) and -10.7(SD6.5)ml/min/1.732, respectively). The number of individuals with eGFR <60ml/min/1.73m2 increased 29.0%(EKFC) and 36.4%(LMR). The EKFC predominantly reclassified older individuals, and the LMR older men, to worse eGFR-categories. HRs of reclassified individuals to worse eGFR-categories were mainly higher compared with the non-reclassified. The EKFC and LMR equations showed equal/improved C-index for mortality (EKFC 0.584/LMR 0.588/CKD-EPIASR-NB2009 0.570), KFRT (0.895/0.900/0.897), and AKI (0.606/0.609/0.599). The LMR equation reclassified more individuals without an event to worse eGFR-categories.

Conclusion: eGFR-category classification was substantially different when using the EKFC or LMR equation compared with the CKD-EPIASR-NB2009 formula. Both equations showed equal to improved ability of risk stratification across eGFR-categories. Shifts in eGFR-category classification might significantly impact clinical decisions. Given that we have identified variation between equations, a careful consideration of the advantages and disadvantages of different eGFR equations is essential.

估计肾小球滤过率方程预测死亡率、肾衰竭和急性肾损伤的比较。
背景:CKD-EPIASR-NB2009估计的肾小球滤过率(eGFR)方程在欧洲显示出严重高估了GFR,因此开发了新的方程。我们在一个大型队列中研究了引入欧洲肾功能联盟(EKFC)或Lund-Malmö修订(LMR) eGFR方程对KDIGO eGFR类别分类的影响。我们将EKFC和LMR公式与CKD-EPIASR-NB2009公式进行了比较,以区分不同egfr类别的全因死亡率、替代治疗肾衰竭(KFRT)和急性肾损伤(AKI)风险。方法:纳入乌得勒支大学医学中心(Utrecht University Medical Center) 2006年12月至2024年7月进行SCr测量的年龄≥18岁的个体。对每个egfr类别、每个方程的所有结果进行风险比(hr)分析。使用Harrell’s Concordance index (C-index)来评估egfr类别之间的风险区分能力。事件的发生是否证明了egfr类别之间的重新分类是合理的,采用净重新分类改善分析进行评估。结果:共纳入285686人。与CKD-EPIASR-NB2009方程相比,EKFC和LMR估计GFR较低(平均分别为-6.3(SD5.3)和-10.7(SD6.5)ml/min/1.732)。结论:与CKD-EPIASR-NB2009公式相比,EKFC或LMR公式对eGFR的分类有很大不同。这两个方程都显示了跨egfr类别的风险分层能力的提高。egfr分类的变化可能会显著影响临床决策。鉴于我们已经确定了方程之间的差异,仔细考虑不同eGFR方程的优缺点是必不可少的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nephrology Dialysis Transplantation
Nephrology Dialysis Transplantation 医学-泌尿学与肾脏学
CiteScore
10.10
自引率
4.90%
发文量
1431
审稿时长
1.7 months
期刊介绍: Nephrology Dialysis Transplantation (ndt) is the leading nephrology journal in Europe and renowned worldwide, devoted to original clinical and laboratory research in nephrology, dialysis and transplantation. ndt is an official journal of the [ERA-EDTA](http://www.era-edta.org/) (European Renal Association-European Dialysis and Transplant Association). Published monthly, the journal provides an essential resource for researchers and clinicians throughout the world. All research articles in this journal have undergone peer review. Print ISSN: 0931-0509.
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