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De-Wei An^1,2,3,4, Gontse G Mokwatsi^5,6, Dong-Yan Zhang^1,2,3

¹Department of Cardiovascular Medicine, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.

|July 15, 2025

概括

估计的膜过率 (eGFR) 的非种族方程式显示了黑人和非黑人的变化. 在CKD查和死亡率预测中,推使用基于cystatin C的eGFR (eGFR_cys) 和联合eGFR (eGFR_cr-cys).

科学领域:

腎臟病學 (nephrology) 是一種醫學專業.
流行病学流行病学
生物统计学生物统计学

背景情况:

推用于估计膜过率 (eGFR) 的非种族方程,以确定慢性病 (CKD) 的阶段.
这些方程使用血清肌素 (eGFR_cr),囊素C (eGFR_cys),或两者 (eGFR_cr-cys).
之前的研究已经强调了不同种族群体对eGFR估计的潜在差异.

研究的目的:

为了比较非种族的eGFR方程,用于查黑人和非黑人人群体中低度的CKD.
评估这些eGFR方程与所有原因和心血管死亡率的关联.
评估由不同的eGFR估计引入的一致性和潜在错误分类.

主要方法:

在四个不同的队列中评估无种族的eGFR方程:非洲PREDICT,FLEMENGHO,NHANES和刚果医院队列.
使用类内相关系数和布兰德-阿尔特曼统计数据评估eGFR方程之间的一致性.
用多变量逻辑或考克斯回归模型来确定与死亡结果的关联.

主要成果:

观察到EGFR估计值之间存在显著的个体内不一致,特别是在黑人参与者中.
将eGFR_cr-cys替换为eGFR_cr导致大量参与者错误分类CKD阶段.
与单独使用eGFR_cr相比,eGFR_cys和eGFR_cr-cys在死亡率预测模型中表现出更好的精细化.

结论:

来自NHANES的死亡数据支持使用eGFR_cys和eGFR_cr-cys进行CKD评估.
在eGFR估计值之间存在很大的变化,因此在查无症状个体时需要谨慎,以避免KDIGO阶段错误分类.
需要进一步的研究来优化无种族的eGFR方程,以便在不同人群中准确的CKD分期和风险分层.

关键词:

生物医学分析生物医学分析慢性脏疾病慢性脏疾病估计的淋巴膜过率.死亡率死亡率人口科学人口科学竞争竞争竞争竞争

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