基于机器学习的2型糖尿病与骨代谢的关联性研究

Association study on bone metabolism in type 2 diabetes by using machine learning

2型糖尿病常伴有严重的并发症,包括骨代谢性疾病、肝病、肾病等,受病程、性别、年龄和个体差异的影响,没有统一的治疗模式。因此,深入分析临床数据、寻找2型糖尿病并发症数据的相关性,对2型糖尿病及其并发症的治疗具有重要的指导意义。本文以安徽省2型糖尿病患者的临床数据为基础,建立多元线性回归模型。我们的研究结果表明,影响2型糖尿病骨并发症的主要因素包括体型指数、肌酸酐、尿酸、甘油三酯和血压。有趣的是,2型糖尿病患者的腰椎骨密度增加,这表明2型糖尿病患者存在腰椎骨质增生的风险。

Type 2 diabetes mellitus is often accompanied by serious complications,including bone metabolic diseases,liver diseases,and kidney diseases,which are affected by the course of disease,sex,age and individual differences and cannot be a unified treatment paradigm.Therefore,for the in-depth analysis of clinical data,looking for the correlation of type 2 diabetes complication data has important guiding significance for the treatment of type 2 diabetes and its complications.In this paper,multiple linear regression models were established based on the clinical data of type 2 diabetes patients in Anhui Province.Our results suggest that the main factors affecting bone complications of type 2 diabetes include body shape indexes,creatinine,uric acid,triglycerides and blood pressure.Interestingly,the bone mineral density of lumbar vertebrae in patients with type 2 diabetes was increased,suggesting that there was a risk of lumbar hyperosteogeny.