Prediction of Diabetic Kidney Disease in Newly Diagnosed Type 2 Diabetes Mellitus.
Prediction of Diabetic Kidney Disease in Newly Diagnosed Type 2 Diabetes Mellitus.
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在新诊断的2型糖尿病中预测糖尿病肾脏疾病。
DOI：
10.2147/dmso.s417300
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Yang, Min
中科院分区：
文献类型：
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作者：
Mu, Xiaodie;Wu, Aihua;Hu, Huiyue;Zhou, Hua;Yang, Min
糖尿病肾病(DKD)是糖尿病(DM)常见的微血管并发症，发展到晚期一直无症状。因此，我们的目标是开发一种新诊断的2型糖尿病(T2 DM)进展为DKD的诺模图预测模型。这是一项对521名新诊断的T2 DM患者收集的前瞻性数据的单中心分析。纳入所有相关临床记录，包括甘油三酯-血糖指数(TYG指数)。采用最小绝对收缩选择算子(LASSO)建立预测模型。此外，对诺模图的区分性、校准和临床实用性进行了评估。在这项研究中，156名参与者被纳入验证集，而其余365名参与者被纳入训练集。个体化诺模图预测模型中包含的预测因素包括5个变量。预测模型的曲线下面积为0.826(95%可信区间为0.775~0.876)，具有良好的区分性。根据校准曲线和决策曲线分析，该模型在预测准确性和临床适用性方面表现得非常好。新诊断的T2 DM患者的DKD风险预测诺模图具有显著的区分性和校正性，有助于临床实践。
Diabetic kidney disease (DKD), a common microvascular complication of diabetes mellitus (DM), is always asymptomatic until it develops to the advanced stage. Thus, we aim to develop a nomogram prediction model for progression to DKD in newly diagnosed type 2 diabetes mellitus (T2DM). This was a single-center analysis of prospective data collected from 521 newly diagnosed patients with T2DM. All related clinical records were incorporated, including the triglyceride-glucose index (TyG index). The least absolute shrinkage and selection operator (LASSO) was used to build a prediction model. In addition, discrimination, calibration, and clinical practicality of the nomogram were evaluated. In this study, 156 participants were incorporated as the validation set, while the remaining 365 were incorporated into the training set. The predictive factors included in the individualized nomogram prediction model included 5 variables. The area under the curve (AUC) for the prediction model was 0.826 (95% CI 0.775 to 0.876), indicating excellent discrimination performance. The model performed exceptionally well in terms of predictive accuracy and clinical applicability, according to calibration curves and decision curve analysis. The predictive nomogram for the risk of DKD in newly diagnosed T2DM patients had outstanding discrimination and calibration, which could help in clinical practice.