基于生物标志物与列线图快速筛查2型糖尿病肾病老年患者内在能力下降的研究^*

Research on rapid screening for declining intrinsic capacity in elderly patients with type 2 diabetic kidney disease based on biomarkers and nomograms

摘要

目的 分析影响2型糖尿病肾病(T2DKD)老年患者内在能力(IC)下降的因素,并基于生物标志物构建列线图预测模型。方法 采用便利抽样法,选取2024年10月—2025年5月新疆维吾尔自治区人民医院接受治疗的468例T2DKD老年患者作为研究对象,按照7∶3随机分为训练集328例,验证集140例;根据IC受损情况将训练集分为IC受损组257例,IC稳定组71例。比较训练集与验证集、IC稳定组与IC受损组的临床资料;采用二元logistic回归分析导致患者IC受损的危险因素,基于分析结果运用R软件绘制列线图模型,并对模型进行验证。结果 训练集中IC稳定组与IC受损组临床资料单因素分析结果显示:年龄、性别、握力值、居住方式、慢性病数量、社会参与度得分、疾病进展恐惧得分、25-羟基维生素D、糖化血红蛋白比较,差异均有统计学意义(P＜0.05)。二元logistic回归分析结果显示:年龄、居住方式(独居)、握力值、慢性病数量、社会参与度得分及25-羟基维生素D是T2DKD老年患者IC下降的影响因素(P＜0.05)。列线图模型验证结果显示,模型预测性能良好:训练集与验证集的ROC曲线下面积分别为0.899(95%CI:0.861~0.937,P＜0.001)和0.855(95%CI:0.784~0.926,P＜0.001),均处于较高水平。校准曲线结果显示模型预测概率与实际观测结果之间的一致性良好(P＞0.05),表明模型具有较好的诊断性能。结论 研究识别了T2DKD老年患者IC下降的多个危险因素,并据此开发了一个稳健且易于测量的列线图模型。该模型有助于临床医护人员快速筛查IC下降的高风险患者,为早期干预提供依据。

Abstract

Objective To analyze the factors influencing the decline of intrinsic capacity(IC)in elderly patients with Type 2 Diabetic Kidney Disease(T2DKD) and to construct a nomogram prediction model based on biomarkers. Methods Using a convenience sampling method, 468 elderly patients with T2DKD who received treatment at the People's Hospital of Xinjiang Uygur Autonomous Region between October 2024 and May 2025 were enrolled as study subjects. They were randomly divided into a training set (328 cases) and a validation set (140 cases) in a 7∶3 ratio. The training set was divided into 257 cases in the IC impaired group and 71 cases in the IC stable group based on IC impairment status. Clinical characteristics were compared between the training set and the validation set, as well as between the IC stable group and the IC impaired group. Binary logistic regression was employed to identify risk factors for IC impairment; based on the results, a nomogram was developed using R software, and the model was subsequently validated. Results The results of univariate analysis of clinical data between the IC stable group and the IC impaired group in the training set showed that there were significant differences in age, gender, grip strength, living arrangement, number of chronic diseases, social participation score, fear of disease progression score, 25-hydroxyvitamin D, and glycosylated hemoglobin(P＜0.05). Binary logistic regression analysis revealed that age, living arrangement (Living alone), grip strength, number of chronic diseases, social participation score, and 25-hydroxyvitamin D level were influencing factors for IC decline in elderly T2DKD patients(P<0.05). Nomogram prediction model validation results showed good predictive performance of the model, the areas under the ROC curve for the training set and validation set were 0.899 (95% CI: 0.861-0.937,P<0.001) and 0.855 (95% CI: 0.784-0.926,P<0.001), respectively, both at high levels. The calibration curve results indicated good consistency between the model's predicted probabilities and the actual observed outcomes(P>0.05), demonstrating the model's good diagnostic performance. Conclusion This study identified multiple risk factors for IC decline in elderly T2DKD patients and subsequently developed a robust and easily measurable nomogram model. This model can assist clinical healthcare staff in rapidly screening patients at high risk for IC decline, providing a basis for early intervention.

关键词

2型糖尿病肾病 / 生物标志物 / 内在能力 / 列线图 / 人口老龄化

Key words

Type 2 diabetic kidney disease / Biomarkers / Intrinsic capacity / Nomogram / Population aging