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Validation of The Health Improvement Network (THIN) database for epidemiologic studies of chronic kidney disease.

机译:验证用于慢性肾脏病流行病学研究的健康改善网络(THIN)数据库。

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PURPOSE: Chronic kidney disease (CKD) is a prevalent and important outcome and covariate in pharmacoepidemiology. The Health Improvement Network (THIN) in the UK represents a unique resource for population-based studies of CKD. We compiled a valid list of Read codes to identify subjects with moderate to advanced CKD. METHODS: A cross-sectional validation study was performed to identify codes that best define CKD Stages 3-5. All subjects with at least one non-zero measure of serum creatinine after 1 January 2002 were included. Estimated glomerular filtration rate (eGFR) was calculated according to the Schwartz formula for subjects aged < 18 years and the Modification of Diet in Renal Disease formula for subjects aged >/= 18 years. CKD was defined as an eGFR <60 mL/minute/1.73 m(2) on at least two occasions, more than 90 days apart. RESULTS: The laboratory definition identified 230,426 subjects with CKD, for a period prevalence in 2008 of 4.56% (95%CI, 4.54-4.58). A list of 45 Read codes was compiled, which yielded a positive predictive value of 88.9% (95%CI, 88.7-89.1), sensitivity of 48.8%, negative predictive value of 86.5%, and specificity of 98.2%. Of the 11.1% of subjects with a code who did not meet the laboratory definition, 83.6% had at least one eGFR <60. The most commonly used code was for CKD Stage 3. CONCLUSIONS: The proposed list of codes can be used to accurately identify CKD when serum creatinine data are limited. The most sensitive approach for the detection of CKD is to use this list to supplement creatinine measures.
机译:目的:慢性肾脏病(CKD)是普遍流行的重要结局,在药物流行病学中是协变量。英国的健康改善网络(THIN)为基于人群的CKD研究提供了独特的资源。我们编制了有效的阅读代码列表,以识别中度至高级CKD的受试者。方法:进行了一项横截面验证研究,以识别最能定义CKD 3-5期的规范。纳入所有在2002年1月1日之后进行至少一项非零血清肌酐测量的受试者。估计的肾小球滤过率(eGFR)是根据Schwartz公式计算的,适用于<18岁的受试者,根据饮食中肾脏疾病的饮食调节公式,用于≥/ = 18岁的受试者。 CKD被定义为至少两次间隔90天以上的eGFR <60 mL / min / 1.73 m(2)。结果:实验室定义确定了230426名CKD患者,2008年的患病率为4.56%(95%CI,4.54-4.58)。汇编了45个读码列表,得出阳性预测值为88.9%(95%CI,88.7-89.1),敏感性为48.8%,阴性预测值为86.5%和特异性为98.2%。在11.1%的代码不符合实验室定义的受试者中,83.6%的eGFR至少为60。最常用的代码是CKD第3阶段。结论:当血清肌酐数据有限时,建议的代码列表可用于准确识别CKD。检测CKD的最灵敏方法是使用此列表来补充肌酐测量值。

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