中国比较医学杂志2026，Vol.36Issue(10)：29-42,14.DOI:10.3969/j.issn.1671-7856.2026.10.004
基于数据挖掘的糖尿病心肌病动物模型应用分析
Analysis of diabetic cardiomyopathy animal models based on data mining
摘要
Abstract
Objective To establish an animal model reflecting the pathogenesis of diabetic cardiomyopathy(DCM)by analysis of key modeling elements and detection indexes involved in the construction of animal models of DCM,to provide valuable references to improve the success rate of modeling and establish a standard for DCM animal models.Methods We searched the CNKI,Wanfang,VIP,PubMed,and Web of Science databases for the past 10 years to identify relevant articles on animal experiments of DCM.We organized and summarized the data including experimental animal species,gender,age,body weight,modeling method,publication volume and quality,types of positive control drugs and administration cycles,detection indexes,and modeling standards.We then established a database and carried out a statistical analysis of the result using Excel 2021,Origin 2022,SPSS Modeler 18.0,and Cytoscape 3.10.3.Results A total of 228 papers were included in the analysis.Most of the DCM animal models were prepared in male Sprague-Dawley rats induced by a high-sugar and high-fat diet combined with streptozotocin.Modeling success was generally assessed by blood glucose and echocardiography.Western blot and hematoxylin/eosin staining were frequently used,and in studies containing positive control drugs,the most frequently used drug was metformin,followed by rosiglitazone.Conclusions DCM animal models currently lack a systematic evaluation of Chinese medicine syndrome patterns,and the modeling method and standards have not been unified.Further studies are therefore needed to improve the modeling method and evaluation system for DCM animal modes.关键词
糖尿病心肌病/动物模型/数据挖掘/应用分析/检测指标Key words
diabetic cardiomyopathy/animal model/data mining/application analysis/detection index分类
医药卫生引用本文复制引用
谢雨新,李彬,郑婷婷,李卓毅,高原,于瑞..基于数据挖掘的糖尿病心肌病动物模型应用分析[J].中国比较医学杂志,2026,36(10):29-42,14.基金项目
国家自然科学基金(82074226) （82074226）
河南省中医药科学研究专项(2024ZY2013,2023ZXZX1165) （2024ZY2013,2023ZXZX1165）
河南省高校科技创新团队支持计划(25IRTSTHN033). （25IRTSTHN033）
