[1]王铖,王奕,许晓双,等.CKM2~3期的2型糖尿病患者中左心室亚临床收缩功能受损风险预测模型的构建及验证[J].陕西医学杂志,2026,(7):912-918.[doi:DOI:10.3969/j.issn.1000-7377.2026.07.007]
　WANG Cheng,WANG Yi,XU Xiaoshuang,et al.Construction and validation of a risk prediction model for subclinical left ventricularsystolic dysfunction in patients with type 2 diabetes mellitus with stage CKM2~3[J].,2026,(7):912-918.[doi:DOI:10.3969/j.issn.1000-7377.2026.07.007]
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CKM2~3期的2型糖尿病患者中左心室亚临床收缩功能受损风险预测模型的构建及验证

《陕西医学杂志》[ISSN:1000-7377/CN:61-1281/TN]

卷:
期数:
2026年7期
页码:
912-918
栏目:
临床研究
出版日期:
2026-07-05

文章信息/Info

Title:
Construction and validation of a risk prediction model for subclinical left ventricularsystolic dysfunction in patients with type 2 diabetes mellitus with stage CKM2~3
作者:
王铖; 王奕; 许晓双; 丁文华; 李梦颖; 王鑫; 程阳; 周洁
（空军军医大学第一附属医院内分泌代谢科，陕西 西安 710000）
Author(s):
WANG Cheng; WANG Yi; XU Xiaoshuang; DING Wenhua; LI Mengying; WANG Xin; CHENG Yang; ZHOU Jie
(Department of Endocrinology and Metabolism,First Affiliated Hospital of Air Force Medical University,Xi’an 710000，China)
关键词:
2型糖尿病; 左心室亚临床收缩功能受损; 心血管-肾脏代谢综合征; 预测模型; 列线图; 左心室整体纵向应变
Keywords:
Type 2 diabetes; Subclinical left ventricular systolic dysfunction; Cardiovascular-kidney-metabolic syndrome; Prediction model; Nomogram; Global longitudinal strain of the left ventricle
分类号:
R 587.1
DOI:
DOI:10.3969/j.issn.1000-7377.2026.07.007
文献标志码:
A
摘要:
目的：研究心血管-肾脏代谢综合征(CKM) 2~3期的2型糖尿病（T2DM）患者，发生左心室亚临床收缩功能受损的危险因素，并构建与验证相应的风险预测模型。方法：收集165例CKM 2~3期的T2DM患者一般情况、心脏超声、心电图指标及其他实验室检查指标。使用二维斑点超声对患者进行评估，并测量左心室整体纵向应变(GLS)。采用随机数字表法按7∶3的比例随机分为训练集和验证集，在训练集根据GLS水平将患者分为左室亚临床收缩功能正常组(GLS≥18%组，n=57)和左室亚临床收缩功能受损组(GLS<18%组，n=58)。在训练集中使用Lasso回归与多元Logistic回归分析来识别最重要的预测因子，并建立一个预测左心室亚临床收缩功能受损的列线图模型。利用ROC曲线来评估模型的区别能力，并结合校准曲线和决策曲线分析以进一步考量预测模型的精确性。结果：根据筛选结果，采用3个独立影响因素[糖化血红蛋白、估测肾小球滤过率、甘油三酯葡萄糖 -体重指数（TyG-BMI）]构建列线图预测模型。训练集和验证集列线图预测T2DM患者发生左心室亚临床收缩功能受损的ROC曲线下的面积（AUC）分别为0.727（95%CI：0.635~0.819）和0.717（95%CI：0.569~0.865），校准图表明模型预测结果与实际值较吻合，决策曲线分析显示模型的净收益率优良，临床实用性较强，且预测模型的AUC值均高于单一变量的AUC值。结论：本研究开发了一种列线图模型，用于预测T2DM患者的左心室潜在收缩功能受损。该模型表现出良好的辨识度和临床应用价值，能够帮助在早期识别患有这种心脏问题的T2DM患者。
Abstract:
Objective:To investigate the risk factors for impaired left ventricular subclinical systolic function in patients with stage 2~3 cardiovascular-kidney-metabolic syndrome (CKM) and type 2 diabetes mellitus (T2DM),and to construct and validate a corresponding risk prediction model.Methods：We collected general information,echocardiography,ECG indicators,and other laboratory test results from 165 hospitalized patients with stage 2~3 CKM and T2DM at the First Affiliated Hospital of Air Force Medical University from February to December 2023.Two-dimensional speckle tracking echocardiography was used to assess the patients,measuring global longitudinal strain (GLS) of the left ventricle.A random number table method was used to divide the patients into training and validation sets in a 7∶3 ratio.In the training set,patients were categorized into the normal left ventricular subclinical systolic function group (GLS≥18%,n=57) and the impaired left ventricular subclinical systolic function group (GLS<18%,n=58) based on their GLS levels.Lasso regression and multivariable logistic regression were utilized in the training set to identify the most significant predictors and establish a nomogram model for predicting impaired left ventricular subclinical systolic function.Receiver operating characteristic (ROC) curve analysis was used to evaluate the discriminatory ability of the model,and calibration curve and decision curve analysis were combined to further assess the accuracy of the prediction model.Results:Based on the screening results,a nomogram prediction model was constructed using three independent influencing factors (glycated hemoglobin,eGFR,TyG-BMI index).The AUC for predicting impaired left ventricular subclinical systolic function in T2DM patients in both the training and validation sets was 0.727 (95%CI：0.635~0.819) and 0.717 (95%CI：0.569~0.865),respectively.The calibration curve indicated that the model’s predictions were closely aligned with actual values,while the decision curve analysis showed that the model had excellent net benefit,demonstrating strong clinical applicability,with AUC values of the prediction model being higher than those of any single variable.Conclusion:This study developed a nomogram model for predicting potential left ventricular systolic function impairment in T2DM patients.The model exhibited good discrimination and clinical applicability,aiding in the early identification of T2DM patients with this cardiac issue and supporting physicians in formulating personalized treatment plans.

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备注/Memo

备注/Memo:
国家自然科学基金青年科学基金资助项目（8250120769）
更新日期/Last Update: 2026-07-10