External validation of prognostic models for chronic kidney disease among type 2 diabetes.
External validation of prognostic models for chronic kidney disease among type 2 diabetes.
复制标题
2型糖尿病患者慢性肾脏疾病预后模型的外部验证
DOI：
10.1007/s40620-021-01220-w
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发表时间：
2022-07
影响因子：
3.4
通讯作者：
Thakkinstian, Ammarin
中科院分区：
文献类型：
--
作者：
Saputro, Sigit Ari;Pattanateepapon, Anuchate;Pattanaprateep, Oraluck;Aekplakorn, Wichai;McKay, Gareth J.;Attia, John;Thakkinstian, Ammarin
已经推导出各种预后模型来预测2型糖尿病（T2 D）中慢性肾病（CKD）的发展。然而，它们在不同人群中的普遍性和预测性能在很大程度上仍然未经验证。本研究旨在外部验证T2 D泰国队列中CKD的几种预后模型。一项全国性的调查与医院数据库相关联，以创建一个糖尿病患者的前瞻性队列（n = 3416）。我们进行了一项系统回顾，以确定预后模型和传统指标（即，判别和校准），以比较CKD预测的模型性能。我们更新了预后模型，包括额外的临床参数，以优化模型在泰国设置的性能。确定了六个相关的先前公布的模型。基线时，CKD的C统计量范围为0.585（0.565-0.605）至0.786（0.765-0.806），终末期肾病（ESRD）的C统计量范围为0.657（0.610-0.703）至0.760（0.705-0.816）。所有原始CKD模型均显示出良好的校准，观察/预期（O/E）比值范围为0.999（0.975-1.024）至1.009（0.929-1.090）。Hosmer-Lemeshow检验表明，所有模型都拟合良好。增加常规临床因素（即，葡萄糖水平和口服糖尿病药物）通过改善C统计量（CKD的Low为0.114，ESRD的Elley为0.025）增强了模型预测。所有模型均显示出中等的区分度和公平的校准。更新模型，包括常规的临床因素大大提高了他们的准确性。Low的（在新加坡开发）和Elley的模型（在新西兰开发），优于其他模型评估。这些模型可以帮助临床医生在与泰国相似的地区改善糖尿病患者的CKD和/或ESRD风险分层。在线版本包含补充材料，可通过10.1007/s40620-021-01220-w获得。
Various prognostic models have been derived to predict chronic kidney disease (CKD) development in type 2 diabetes (T2D). However, their generalisability and predictive performance in different populations remain largely unvalidated. This study aimed to externally validate several prognostic models of CKD in a T2D Thai cohort. A nationwide survey was linked with hospital databases to create a prospective cohort of patients with diabetes (n = 3416). We undertook a systematic review to identify prognostic models and traditional metrics (i.e., discrimination and calibration) to compare model performance for CKD prediction. We updated prognostic models by including additional clinical parameters to optimise model performance in the Thai setting. Six relevant previously published models were identified. At baseline, C-statistics ranged from 0.585 (0.565–0.605) to 0.786 (0.765–0.806) for CKD and 0.657 (0.610–0.703) to 0.760 (0.705–0.816) for end-stage renal disease (ESRD). All original CKD models showed fair calibration with Observed/Expected (O/E) ratios ranging from 0.999 (0.975–1.024) to 1.009 (0.929–1.090). Hosmer–Lemeshow tests indicated a good fit for all models. The addition of routine clinical factors (i.e., glucose level and oral diabetes medications) enhanced model prediction by improved C-statistics of Low’s of 0.114 for CKD and Elley’s of 0.025 for ESRD. All models showed moderate discrimination and fair calibration. Updating models to include routine clinical factors substantially enhanced their accuracy. Low’s (developed in Singapore) and Elley’s model (developed in New Zealand), outperformed the other models evaluated. These models can assist clinicians to improve the risk-stratification of diabetic patients for CKD and/or ESRD in the regions settings are similar to Thailand. The online version contains supplementary material available at 10.1007/s40620-021-01220-w.
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影响因子：
8.1
作者：
George C;Mogueo A;Okpechi I;Echouffo-Tcheugui JB;Kengne AP
通讯作者：
Kengne AP
影响因子：
37.8
作者：
Cook, Nancy R.
通讯作者：
Cook, Nancy R.
影响因子：
7.2
作者：
Janssen, K. J. M.;Moons, K. G. M.;Vergouwe, Y.
通讯作者：
Vergouwe, Y.
影响因子：
5.1
作者：
Lee, C. H.;Shih, A. Z. L.;Lam, K. S. L.
通讯作者：
Lam, K. S. L.
影响因子：
4.6
作者：
Liao, Li-Na;Li, Tsai-Chung;Lin, Cheng-Chieh
通讯作者：
Lin, Cheng-Chieh