Department of Laboratory Medicine, Beijing Tongren Hospital, Capital Medical University, No. 1 Dongjiaominxiang, Beijing, 100730, Dongcheng District, China.
Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Science Key Laboratory, No. 1 Dongjiaominxiang, Beijing, 100730, Dongcheng District, China.
BMC Nephrol. 2020 Apr 6;21(1):120. doi: 10.1186/s12882-020-01787-9.
Few chronic kidney disease (CKD) risk prediction models have been investigated in low- and middle-income areas worldwide. We developed new risk scores for predicting incident CKD in low- and middle-income rural Chinese populations.
Data from the Handan Eye Study, which was a village-based cohort study and conducted from 2006 to 2013, were utilized as part of this analysis. The present study utilized data generated from 3266 participants who were ≥ 30 years of age. Two risk models for predicting incident CKD were derived using two-thirds of the sample cohort (selected randomly) using stepwise logistic regression, and were subsequently validated using data from the final third of the sample cohort. In addition, two simple point systems for incident CKD were generated according to the procedures described in the Framingham Study. CKD was defined as reduced renal function (estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73m) or the presence of albuminuria (urinary albumin-to-creatinine ratio (UACR) ≥30 mg/g).
The Simple Risk Score included waist circumference, systolic blood pressure (SBP), diabetes, sex, and education. The Best-fit Risk Score included urinary albumin-to-creatinine ratio, SBP, C-reactive protein, triglyceride, sex, education, and diabetes. In the validation sample, the areas under the receiver operating curve of the Simple Risk Score and Best-fit Risk Score were 0.717 (95% CI, 0.689-0.744) and 0.721 (95% CI, 0.693-0.748), respectively; the discrimination difference between the score systems was not significant (P = 0.455). The Simple Risk Score had a higher Youden index, sensitivity, and negative predictive value, with an optimal cutoff value of 14.
Our Simple Risk Score for predicting incident CKD in a low- and middle-income rural Chinese population will help identify individuals at risk for developing incident CKD.
全球范围内，仅有少数慢性肾脏病 (CKD) 风险预测模型在中低收入地区进行了研究。我们开发了新的风险评分系统，用于预测中国中低收入农村人群的 CKD 事件。
本研究利用了 2006 年至 2013 年开展的一项以村庄为基础的队列研究——邯郸眼病研究的数据。本分析纳入了 3266 名年龄≥30 岁的参与者。使用二阶段逻辑回归，从三分之二的样本队列（随机选择）中提取两个用于预测 CKD 事件的风险模型，然后使用样本队列的最后三分之一数据进行验证。此外，根据弗雷明汉研究中描述的程序，生成了两个用于 CKD 事件的简单评分系统。CKD 定义为肾功能下降（估算肾小球滤过率（eGFR）<60 mL/min/1.73m）或白蛋白尿（尿白蛋白与肌酐比值（UACR）≥30mg/g）。
简单风险评分包括腰围、收缩压（SBP）、糖尿病、性别和教育程度。最佳拟合风险评分包括尿白蛋白与肌酐比值、SBP、C 反应蛋白、甘油三酯、性别、教育程度和糖尿病。在验证样本中，简单风险评分和最佳拟合风险评分的受试者工作特征曲线下面积分别为 0.717（95%置信区间，0.689-0.744）和 0.721（95%置信区间，0.693-0.748）；评分系统之间的鉴别差异无统计学意义（P=0.455）。简单风险评分的约登指数、敏感度和阴性预测值更高，最佳截断值为 14。
我们的简单风险评分系统可用于预测中国中低收入农村人群的 CKD 事件，有助于识别出发生 CKD 事件的高危个体。
