Data_Sheet_1_A Validation Study on eGFR Equations in Chinese Patients With Diabetic or Non-diabetic CKD.docx

Aims: It remains controversial to choose the optimal equation to estimate glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients with diabetes.
Materials and Methods: Two hundred and fifteen diabetic CKD patients and 192 non-diabetic CKD patients were enrolled in this study. Iohexol GFR, serum creatinine (SCr), and Cystatin C(CysC) were measured simultaneously for each patient. SCr- and CysC-based estimated GFR (eGFR) were calculated through eight equations, including three CKD-EPI equations, Revised Lund-Malmö study equation (RLM), CAPA equation, and three Full Age Spectrum (FAS) equations. Bias, precision, and accuracy were compared among eGFR equations with iohexol-GFR serving as measured GFR (mGFR). Independent predictive factors of accuracy were explored using multivariate logistic regression analysis.
Results: In the diabetic group, CKD-EPISCr−CysC showed the best performance among three CKD-EPI equations (interquartile range of 13.88 ml/min/1.73 m2 and 30% accuracy of 72.56%). Compared to CKD-EPISCr−CysC, the other five equations did not significantly improve the performance of GFR estimates. Mostly, eGFR equations were less accurate in diabetic group than in non-diabetic group. Significant differences were found in different mGFR range (P < 0.001). The multivariate logistic regression analysis identified that BMI, mGFR, and diabetic kidney disease (DKD) status were independent predictors of accuracy of three equations in diabetic group. HbA1c was a predictor of accuracy of CKD-EPISCr and CKD-EPICysC in diabetic group.
Conclusions: This study showed that eGFR equations were less accurate in the diabetic group than in the non-diabetic group. CKD-EPIScr−CysC had the best performance among CKD-EPI equations in Chinese diabetic CKD patients. The other five equations did not significantly improve the performance of GFR estimates. BMI, mGFR, DKD status, and HbA1c were independent factors associated with accuracy in eGFR equations.

研究目的：针对合并糖尿病的慢性肾脏病（chronic kidney disease, CKD）患者，选择最优方程估算肾小球滤过率（glomerular filtration rate, GFR）仍存在争议。
材料与方法：本研究共纳入215例合并糖尿病的CKD患者及192例非糖尿病CKD患者。对所有受试者同步检测碘海醇（Iohexol）GFR、血清肌酐（serum creatinine, SCr）及胱抑素C（Cystatin C, CysC）。基于SCr与CysC的估算肾小球滤过率（estimated GFR, eGFR）通过8种方程计算得出，包括3种CKD-EPI方程（CKD-EPI equations）、修正隆德-马尔默研究方程（Revised Lund-Malmö study equation, RLM）、CAPA方程以及3种全年龄谱（Full Age Spectrum, FAS）方程。以碘海醇GFR作为实测肾小球滤过率（measured GFR, mGFR），对比各eGFR方程的偏倚、精密度与准确度。采用多变量logistic回归分析探索准确度的独立预测因素。
结果：在糖尿病组中，CKD-EPISCr−CysC在3种CKD-EPI方程中表现最优（四分位间距为13.88 ml/min/1.73 m²，30%准确度达72.56%）。相较于CKD-EPISCr−CysC，其余5种方程未能显著提升GFR估算性能。总体而言，糖尿病组的eGFR方程准确度低于非糖尿病组。不同mGFR范围的准确度存在显著差异（P < 0.001）。多变量logistic回归分析显示，体质量指数（Body Mass Index, BMI）、mGFR及糖尿病肾病（diabetic kidney disease, DKD）状态是糖尿病组中3种eGFR方程准确度的独立预测因素。糖化血红蛋白（glycated hemoglobin A1c, HbA1c）是糖尿病组中CKD-EPISCr与CKD-EPICysC准确度的预测因素。
结论：本研究表明，糖尿病组的eGFR方程准确度低于非糖尿病组。在中国合并糖尿病的CKD患者中，CKD-EPIScr−CysC在CKD-EPI方程中表现最优。其余5种方程未能显著改善GFR估算性能。BMI、mGFR、DKD状态及HbA1c是与eGFR方程准确度相关的独立影响因素。