NHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin, China.
Department of Epidemiology and Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China.
Diabetes Care. 2020 Apr;43(4):925-933. doi: 10.2337/dc19-1897.
Identifying patients at high risk of diabetic kidney disease (DKD) helps improve clinical outcome.
To establish a model for predicting DKD.
The derivation cohort was from a meta-analysis. The validation cohort was from a Chinese cohort.
Cohort studies that reported risk factors of DKD with their corresponding risk ratios (RRs) in patients with type 2 diabetes were selected. All patients had estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m and urinary albumin-to-creatinine ratio (UACR) <30 mg/g at baseline.
Risk factors and their corresponding RRs were extracted. Only risk factors with statistical significance were included in our DKD risk prediction model.
Twenty cohorts including 41,271 patients with type 2 diabetes were included in our meta-analysis. Age, BMI, smoking, diabetic retinopathy, hemoglobin A, systolic blood pressure, HDL cholesterol, triglycerides, UACR, and eGFR were statistically significant. All these risk factors were included in the model except eGFR because of the significant heterogeneity among studies. All risk factors were scored according to their weightings, and the highest score was 37.0. The model was validated in an external cohort with a median follow-up of 2.9 years. A cutoff value of 16 was selected with a sensitivity of 0.847 and a specificity of 0.677.
There was huge heterogeneity among studies involving eGFR. More evidence is needed to power it as a risk factor of DKD.
The DKD risk prediction model consisting of nine risk factors established in this study is a simple tool for detecting patients at high risk of DKD.
识别患有糖尿病肾病（DKD）风险较高的患者有助于改善临床结局。
建立预测 DKD 的模型。
推导队列来自荟萃分析。验证队列来自中国队列。
选择了报告 2 型糖尿病患者 DKD 危险因素及其相应风险比（RR）的队列研究。所有患者在基线时的估计肾小球滤过率（eGFR）≥60 mL/min/1.73 m 和尿白蛋白与肌酐比值（UACR）<30 mg/g。
提取了危险因素及其相应的 RR。仅纳入具有统计学意义的危险因素纳入我们的 DKD 风险预测模型。
我们的荟萃分析纳入了 20 项队列研究，共 41271 例 2 型糖尿病患者。年龄、BMI、吸烟、糖尿病视网膜病变、血红蛋白 A、收缩压、高密度脂蛋白胆固醇、甘油三酯、UACR 和 eGFR 具有统计学意义。除 eGFR 外，所有这些危险因素均纳入模型，因为研究之间存在显著异质性。所有危险因素均根据权重进行评分，最高得分为 37.0。该模型在中位随访 2.9 年的外部队列中得到验证。选择截断值为 16，其敏感性为 0.847，特异性为 0.677。
涉及 eGFR 的研究存在很大异质性。需要更多证据来支持它作为 DKD 的危险因素。
本研究建立的由九个危险因素组成的 DKD 风险预测模型是一种简单的工具，可用于检测 DKD 风险较高的患者。
