Medical School, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Diabetes Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
BMC Endocr Disord. 2024 Oct 21;24(1):221. doi: 10.1186/s12902-024-01758-3.
Type 2 diabetes mellitus (T2DM) was one of the most prevalent comorbidities among patients with coronavirus disease 2019 (COVID-19). Interactions between different metabolic parameters contribute to the susceptibility to the virus; thereby, this study aimed to rank the importance of clinical and laboratory variables as risk factors for COVID-19 or as protective factors against it by applying machine learning methods.
This study is a retrospective cohort conducted at a single center, focusing on a population with T2DM. The patients attended the Yazd Diabetes Research Center in Yazd, Iran, from February 20, 2020, to October 21, 2020. Clinical and laboratory data were collected within three months before the onset of the COVID-19 pandemic in Iran. 59 patients were infected with COVID-19, while 59 were not. The dataset was split into 70% training and 30% test sets. Principal Component Analysis (PCA) was applied to the data. The most important components were selected using a 'sequential feature selector' and scored by a Linear Discriminant Analysis model. PCA loadings were then multiplied by the PCs' scores to determine the importance of the original variables in contracting COVID-19.
HDL-C, followed by eGFR, showed a strong negative correlation with the risk of contracting the virus. Higher levels of HDL-C and eGFR offer protection against COVID-19 in the T2DM population. But, the ratio of BUN to creatinine did not show any correlation. Conversely, the AIP, TyG index and TG showed the most positive correlation with susceptibility to COVID-19 in such a way that higher levels of these factors increase the risk of contracting the virus. The positive correlation of diastolic BP, TyG-BMI index, MAP, BMI, weight, TC, FPG, HbA1C, Cr, systolic BP, BUN, and LDL-C with the risk of COVID-19 decreased, respectively.
The atherogenic index of plasma, triglyceride glucose index, and triglyceride levels are the most significant risk factors for COVID-19 contracting in individuals with T2DM. Meanwhile, high-density lipoprotein cholesterol is the most protective factor.
2 型糖尿病(T2DM)是 2019 年冠状病毒病(COVID-19)患者最常见的合并症之一。不同代谢参数之间的相互作用导致了对病毒的易感性;因此,本研究旨在通过应用机器学习方法,对临床和实验室变量作为 COVID-19 的危险因素或保护因素的重要性进行排名。
本研究是在单一中心进行的回顾性队列研究,重点关注 T2DM 人群。患者于 2020 年 2 月 20 日至 2020 年 10 月 21 日在伊朗亚兹德糖尿病研究中心就诊。临床和实验室数据在伊朗 COVID-19 大流行发生前三个月内收集。59 例患者感染了 COVID-19,而 59 例未感染。数据集分为 70%的训练集和 30%的测试集。应用主成分分析(PCA)对数据进行分析。使用“顺序特征选择器”选择最重要的组件,并由线性判别分析模型对其进行评分。然后,将 PCA 载荷乘以 PCs 的得分,以确定原始变量在感染 COVID-19 中的重要性。
HDL-C,其次是 eGFR,与感染病毒的风险呈强烈负相关。HDL-C 和 eGFR 水平较高可保护 T2DM 人群免受 COVID-19 感染。但是,BUN 与肌酐的比值没有显示出任何相关性。相反,AIP、TyG 指数和 TG 与 COVID-19 的易感性呈最正相关,这些因素的水平升高会增加感染病毒的风险。舒张压、TyG-BMI 指数、MAP、BMI、体重、TC、FPG、HbA1C、Cr、收缩压、BUN 和 LDL-C 与 COVID-19 风险呈正相关,分别呈下降趋势。
血浆致动脉粥样硬化指数、甘油三酯葡萄糖指数和甘油三酯水平是 T2DM 个体感染 COVID-19 的最重要危险因素。同时,高密度脂蛋白胆固醇是最具保护作用的因素。