A simple algorithm to predict incident kidney disease.
A simple algorithm to predict incident kidney disease.
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DOI：
10.1001/archinte.168.22.2466
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发表时间：
2008-12-08
影响因子：
--
通讯作者：
August, Phyllis A.
中科院分区：
文献类型：
--
作者：
Kshirsagar, Abhijit V.;Bang, Heejung;Bomback, Andrew S.;Vupputuri, Suma;Shoham, David A.;Kern, Lisa M.;Klemmer, Philip J.;Mazumdar, Madhu;August, Phyllis A.
尽管慢性肾脏疾病(CKD)的负担越来越大，但(据我们所知)还没有算法来量化并发危险因素对发病发展的影响。在45岁或以上的男性和女性中形成了一个由2项基于社区的研究组成的联合队列(N=14155)，这两项研究是动脉粥样硬化风险研究和心血管健康研究，估计肾小球滤过率(GFR)在基线时超过60毫升/分钟/1.73平方米。主要结果是在长达9年的随访期内，肾小球滤过率低于60毫升/分钟/1.73平方米。从开发数据集中得出的三种预测算法在验证数据集中进行了评估。这3种预测算法分别是包含10个预测因子的连续分类最佳拟合模型和包含8个预测因子的简化分类模型。受试者工作特征曲线下面积在0.69~0.70范围内均表现出辨别能力。在简化模型中，年龄、贫血、女性、高血压、糖尿病、外周血管疾病和充血性心力衰竭或心血管疾病病史与GFR<60mL/min/1.73m2相关。使用简化算法的数值得分至少为3可捕获大约70%的事件病例(敏感性)，并准确预测发生CKD的17%的风险(阳性预测值)。一种包含普遍理解的变量的算法有助于对未来CKD高危的中老年个体进行分层。该模型可用于指导人群层面的预防工作，并启动从业者和患者之间关于肾脏疾病风险的讨论。
Despite the growing burden of chronic kidney disease (CKD), there are no algorithms (to our knowledge) to quantify the effect of concurrent risk factors on the development of incident disease. A combined cohort (N = 14 155) of 2 community-based studies, the Atherosclerosis Risk in Communities Study and the Cardiovascular Health Study, was formed among men and women 45 years or older with an estimated glomerular filtration rate (GFR) exceeding 60 mL/min/1.73 m2 at baseline. The primary outcome was the development of a GFR less than 60 mL/min/1.73 m2 during a follow-up period of up to 9 years. Three prediction algorithms derived from the development data set were evaluated in the validation data set. The 3 prediction algorithms were continuous and categorical best-fitting models with 10 predictors and a simplified categorical model with 8 predictors. All showed discrimination with area under the receiver operating characteristic curve in a range of 0.69 to 0.70. In the simplified model, age, anemia, female sex, hypertension, diabetes mellitus, peripheral vascular disease, and history of congestive heart failure or cardiovascular disease were associated with the development of a GFR less than 60 mL/min/1.73 m2. A numeric score of at least 3 using the simplified algorithm captured approximately 70% of incident cases (sensitivity) and accurately predicted a 17% risk of developing CKD (positive predictive value). An algorithm containing commonly understood variables helps to stratify middle-aged and older individuals at high risk for future CKD. The model can be used to guide population-level prevention efforts and to initiate discussions between practitioners and patients about risk for kidney disease.
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影响因子：
13.6
作者：
McClellan, William;Warnock, David G.;Howard, George
通讯作者：
Howard, George
影响因子：
--
作者：
Bang, Heejung;Vupputuri, Suma;Kshirsagar, Abhijit V.
通讯作者：
Kshirsagar, Abhijit V.
影响因子：
6.8
作者：
AKAIKE, H
通讯作者：
AKAIKE, H
影响因子：
19.6
作者：
Muntner, P;Coresh, J;Klag, MJ
通讯作者：
Klag, MJ
影响因子：
13.2
作者：
Nickolas, TL;Frisch, GD;Radhakrishnan, J
通讯作者：
Radhakrishnan, J