Bang Heejung, Vupputuri Suma, Shoham David A, Klemmer Philip J, Falk Ronald J, Mazumdar Madhu, Gipson Debbie, Colindres Romulo E, Kshirsagar Abhijit V
Department of Public Health, Division of Biostatistics and Epidemiology, Weill Medical College of Cornell University, New York, NY, USA.
Arch Intern Med. 2007 Feb 26;167(4):374-81. doi: 10.1001/archinte.167.4.374.
Despite the wide availability and low cost of serum creatinine measurement, at-risk populations are not routinely tested for chronic kidney disease (CKD).
We used a cross-sectional analysis of a nationally representative, population-based survey to develop a system, SCORED (SCreening for Occult REnal Disease), that uses routinely available demographic and medical information to identify individuals with an increased likelihood of CKD. The analysis included 8530 adult participants in the National Health and Nutrition Examination Surveys conducted from 1999 to 2000 and 2001 to 2002 in the United States. Chronic kidney disease was defined as a glomerular filtration rate less than 60 mL/min per 1.73 m(2). Univariate and multivariate associations between a comprehensive set of risk factors and CKD were examined to develop a prediction model. The optimal characteristics of the model were examined with internal measures. External validation was performed using the Atherosclerosis Risk in Communities study. A model-based numeric scoring system was developed.
Age (P<.001), female sex (P = .02), and various health conditions (hypertension [P = .03], diabetes [P = .03], and peripheral vascular disease [P = .008]; history of cardiovascular disease [P = .001] and congestive heart failure [P = .04]; and proteinuria [P<.001] and anemia [P = .003]) were associated with CKD. The multivariate model was well validated in the internal and external data sets (area under the receiver operating characteristic curve of 0.88 and 0.71, respectively). A score of 4 or greater was chosen by internal validation as a cutoff point for screening based on the diagnostic characteristics (sensitivity, 92%; specificity, 68%; positive predictive value, 18%; and negative predictive value, 99%).
This scoring system, weighted toward common variables associated with CKD, may be a useful tool to identify individuals with a high likelihood of occult kidney disease.
尽管血清肌酐检测广泛可用且成本低廉，但高危人群并未常规接受慢性肾脏病（CKD）检测。
我们对一项具有全国代表性的基于人群的调查进行横断面分析，以开发一个名为SCORED（隐匿性肾脏疾病筛查）的系统，该系统利用常规可得的人口统计学和医学信息来识别CKD患病可能性增加的个体。分析纳入了1999至2000年以及2001至2002年在美国进行的国家健康与营养检查调查中的8530名成年参与者。慢性肾脏病定义为肾小球滤过率低于每分钟60毫升每1.73平方米。研究了一组综合风险因素与CKD之间的单变量和多变量关联，以建立一个预测模型。使用内部指标检查模型的最佳特征。利用社区动脉粥样硬化风险研究进行外部验证。开发了一个基于模型的数字评分系统。
年龄（P<0.001）、女性（P = 0.02）以及各种健康状况（高血压[P = 0.03]、糖尿病[P = 0.03]和外周血管疾病[P = 0.008]；心血管疾病史[P = 0.001]和充血性心力衰竭[P = 0.04]；以及蛋白尿[P<0.001]和贫血[P = 0.003]）与CKD相关。多变量模型在内部和外部数据集中均得到了良好验证（受试者操作特征曲线下面积分别为0.88和0.71）。根据诊断特征（敏感性92%、特异性68%、阳性预测值18%和阴性预测值99%），内部验证选择4分或更高作为筛查的截断点。
这个向与CKD相关的常见变量加权的评分系统，可能是识别隐匿性肾脏疾病高患病可能性个体的有用工具。
