PDF(Sci-hub)
Abstract：
OBJECTIVE: Measurement of residual kidney function is recommended for the adjustment of the dialysis prescription, but timed urine collections are difficult and prone to errors. Equations to calculate residual kidney function from serum concentrations of endogenous filtration markers and demographic parameters would simplify monitoring of residual kidney function. However, few equations to estimate residual kidney function using serum concentrations of small solutes and low-molecular-weight proteins have been developed and externally validated.
METHODS: Study of diagnostic test accuracy.
METHODS: 823 Chinese peritoneal dialysis (PD) patients (development cohort) and 826 PD and hemodialysis patients from the Netherlands NECOSAD study (validation cohort).
UNASSIGNED: Equations to estimate residual kidney function (estimated clearance [eCl]) using serum creatinine, urea nitrogen, cystatin C, β2-microglobulin (B2M), β-trace protein (BTP), and combinations, as well as demographic variables (age, sex, height, and weight). Equations were developed using multivariable linear regression analysis in the development cohort and then tested in the validation cohort. Equations were compared with published validated equations.
RESULTS: Residual kidney function measured as urinary clearance (mCl) of urea nitrogen (mClUN) and average of creatinine and urea nitrogen clearance (mClUN-cr).
RESULTS: In external validation, bias (difference between mCl and eCl) was within ± 1.0 unit for all equations. Accuracy (percent of differences within ± 2.0 units) was significantly better for eClBTP, eClB2M, and eClBTP-B2M than eClUN-cr for both mClUN (78%, 80%, and 81% vs 72%; P < 0.05 for all) and mClUN-cr (72%, 78%, and 79% vs 68%; P < 0.05 for all). The area under the curve for predicting mClUN > 2.0 mL/min was highest for eClB2M (0.853) and eClBTP-B2M (0.848). Results were similar for other validated equations.
CONCLUSIONS: Development cohort only consisted of PD patients, no gold-standard method for residual kidney function measurement.
CONCLUSIONS: These results confirm the validity and extend the generalizability of residual kidney function estimating equations from serum concentrations of low-molecular-weight proteins without urine collection.
METHODS: Study of diagnostic test accuracy.
METHODS: 823 Chinese peritoneal dialysis (PD) patients (development cohort) and 826 PD and hemodialysis patients from the Netherlands NECOSAD study (validation cohort).
UNASSIGNED: Equations to estimate residual kidney function (estimated clearance [eCl]) using serum creatinine, urea nitrogen, cystatin C, β2-microglobulin (B2M), β-trace protein (BTP), and combinations, as well as demographic variables (age, sex, height, and weight). Equations were developed using multivariable linear regression analysis in the development cohort and then tested in the validation cohort. Equations were compared with published validated equations.
RESULTS: Residual kidney function measured as urinary clearance (mCl) of urea nitrogen (mClUN) and average of creatinine and urea nitrogen clearance (mClUN-cr).
RESULTS: In external validation, bias (difference between mCl and eCl) was within ± 1.0 unit for all equations. Accuracy (percent of differences within ± 2.0 units) was significantly better for eClBTP, eClB2M, and eClBTP-B2M than eClUN-cr for both mClUN (78%, 80%, and 81% vs 72%; P < 0.05 for all) and mClUN-cr (72%, 78%, and 79% vs 68%; P < 0.05 for all). The area under the curve for predicting mClUN > 2.0 mL/min was highest for eClB2M (0.853) and eClBTP-B2M (0.848). Results were similar for other validated equations.
CONCLUSIONS: Development cohort only consisted of PD patients, no gold-standard method for residual kidney function measurement.
CONCLUSIONS: These results confirm the validity and extend the generalizability of residual kidney function estimating equations from serum concentrations of low-molecular-weight proteins without urine collection.
摘要：
目的：建议对透析处方进行残余肾功能测定，但是定时收集尿液很困难并且容易出错。从内源性过滤标记物的血清浓度和人口统计学参数计算残余肾功能的方程将简化对残余肾功能的监测。然而,使用小溶质和低分子量蛋白的血清浓度来估计残余肾功能的方程很少被开发和外部验证。
方法：研究诊断测试的准确性。
方法：823名中国腹膜透析（PD）患者（发展队列）和826名来自荷兰NECOSAD研究的PD和血液透析患者（验证队列）。
■使用血清肌酐估算残余肾功能（估算清除率[eCl]）的公式，尿素氮,胱抑素C,β2-微球蛋白(B2M),β-痕量蛋白(BTP),和组合，以及人口统计学变量(年龄，性别,高度,和重量）。在开发队列中使用多变量线性回归分析建立方程，然后在验证队列中进行测试。将方程与已发布的验证方程进行比较。
结果：残余肾功能测量为尿素氮（mClUN）的尿清除率（mCl）和肌酐和尿素氮清除率的平均值（mClUN-cr）。
结果：在外部验证中，所有方程的偏差(mCl和eCl之差)在±1.0单位内。eClBTP的准确性（±2.0单位内的差异百分比）明显更好，eClB2M,和eClBTP-B2M比eClUN-cr两个mClUN(78%，80%,和81%对72%；全部P<0.05）和mClUN-cr（72%，78%,和79%对68%；全部P<0.05）。预测mClUN>2.0mL/min的曲线下面积对于eClB2M(0.853)和eClBTP-B2M(0.848)最高。其他验证方程的结果相似。
结论：发展队列仅由PD患者组成，无金标准方法测定残余肾功能。
结论：这些结果证实了根据不收集尿液的低分子量蛋白的血清浓度估算残余肾功能方程的有效性并扩展了其普适性。
方法：研究诊断测试的准确性。
方法：823名中国腹膜透析（PD）患者（发展队列）和826名来自荷兰NECOSAD研究的PD和血液透析患者（验证队列）。
■使用血清肌酐估算残余肾功能（估算清除率[eCl]）的公式，尿素氮,胱抑素C,β2-微球蛋白(B2M),β-痕量蛋白(BTP),和组合，以及人口统计学变量(年龄，性别,高度,和重量）。在开发队列中使用多变量线性回归分析建立方程，然后在验证队列中进行测试。将方程与已发布的验证方程进行比较。
结果：残余肾功能测量为尿素氮（mClUN）的尿清除率（mCl）和肌酐和尿素氮清除率的平均值（mClUN-cr）。
结果：在外部验证中，所有方程的偏差(mCl和eCl之差)在±1.0单位内。eClBTP的准确性（±2.0单位内的差异百分比）明显更好，eClB2M,和eClBTP-B2M比eClUN-cr两个mClUN(78%，80%,和81%对72%；全部P<0.05）和mClUN-cr（72%，78%,和79%对68%；全部P<0.05）。预测mClUN>2.0mL/min的曲线下面积对于eClB2M(0.853)和eClBTP-B2M(0.848)最高。其他验证方程的结果相似。
结论：发展队列仅由PD患者组成，无金标准方法测定残余肾功能。
结论：这些结果证实了根据不收集尿液的低分子量蛋白的血清浓度估算残余肾功能方程的有效性并扩展了其普适性。
