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基于 Copula 的糖尿病相关性分析。

Correlation analysis of diabetes based on Copula.

机构信息

College of Science, Beijing Forestry University, Beijing, China.

State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.

出版信息

Front Endocrinol (Lausanne). 2024 Feb 14;15:1291895. doi: 10.3389/fendo.2024.1291895. eCollection 2024.

DOI:10.3389/fendo.2024.1291895
PMID:38419954
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10899488/
Abstract

INTRODUCTION

The ratio of Triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) is a crucial indicator for diabetes diagnosis.

METHODS

This study utilizes the Copula function to model and fit the non-linear correlation among fasting blood glucose (Glu), glycosylated hemoglobin (HbA1C), and TG/HDL-C in patients with diabetes. The Copula function chosen for this study includes the two-dimensional Archimedes and Elliptical distribution family, as well as the multidimensional Vine Copula function, for fitting the data. The evaluation of the fitting effect is performed using the mean absolute error (MAE) and mean square error (MSE).

RESULTS

The results indicate that the Clayton Copula exhibits the highest effectiveness in fitting the pairwise relationship between Glu and TG/HDL-C, as well as HbA1C and TG/HDL-C, displaying the smallest fitting error. Additionally, the Vine Copula function produces a satisfactory fit for the relationship among all three indicators. Compared to linear analysis methods, the Copula function more accurately depicts the correlation among these three types of indicators.

DISCUSSION

Moreover, our findings indicate a stronger correlation in the lower tail between Glu and HbA1C, as well as TG/HDL-C, suggesting that the Copula function provides greater accuracy and applicability in depicting the relationship among these indicators. As a result, it can offer a more precise auxiliary diagnosis and serve as a valuable reference in clinical judgment.

摘要

简介

甘油三酯（TG）与高密度脂蛋白胆固醇（HDL-C）的比值是诊断糖尿病的一个关键指标。

方法

本研究采用 Copula 函数对糖尿病患者空腹血糖（Glu）、糖化血红蛋白（HbA1C）与 TG/HDL-C 之间的非线性相关进行建模和拟合。本研究选择的 Copula 函数包括二维 Archimedes 和 Elliptical 分布族，以及多维 Vine Copula 函数，用于拟合数据。通过平均绝对误差（MAE）和均方误差（MSE）来评估拟合效果。

结果

结果表明，Clayton Copula 在拟合 Glu 与 TG/HDL-C 以及 HbA1C 与 TG/HDL-C 之间的二元关系方面表现出最高的有效性，拟合误差最小。此外，Vine Copula 函数对所有三个指标之间的关系产生了令人满意的拟合。与线性分析方法相比，Copula 函数更准确地描述了这三种类型的指标之间的相关性。

讨论

此外，我们的研究结果表明，Glu 和 HbA1C 以及 TG/HDL-C 之间在低尾部分具有更强的相关性，这表明 Copula 函数在描述这些指标之间的关系方面提供了更高的准确性和适用性。因此，它可以提供更精确的辅助诊断，并为临床判断提供有价值的参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/b7a5fbf73164/fendo-15-1291895-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/06f444a89c1c/fendo-15-1291895-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/4e0124121bdb/fendo-15-1291895-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/c2a8f016ba00/fendo-15-1291895-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/13e05542e333/fendo-15-1291895-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/b66474ccbb76/fendo-15-1291895-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/8d47092432a5/fendo-15-1291895-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/07c6cfb76021/fendo-15-1291895-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/b7a5fbf73164/fendo-15-1291895-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/06f444a89c1c/fendo-15-1291895-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/4e0124121bdb/fendo-15-1291895-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/c2a8f016ba00/fendo-15-1291895-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/13e05542e333/fendo-15-1291895-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/b66474ccbb76/fendo-15-1291895-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/8d47092432a5/fendo-15-1291895-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/07c6cfb76021/fendo-15-1291895-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b47/10899488/b7a5fbf73164/fendo-15-1291895-g008.jpg

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本文引用的文献

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The effect of obesity on chronic diseases in USA: a flexible copula approach.肥胖对美国慢性病的影响：一种灵活的 Copula 方法。
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Time to Kidneys Failure Modeling in the Patients at Adama Hospital Medical College: Application of Copula Model.
阿达玛医院医学院患者肾衰竭模型构建的时间：Copula 模型的应用。
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Triglycerides to high-density lipoprotein cholesterol (TG/HDL-C) ratio is an independent predictor of the severity of hyperlipidaemic acute pancreatitis.三酰甘油与高密度脂蛋白胆固醇（TG/HDL-C）比值是高脂血症性急性胰腺炎严重程度的独立预测因子。
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Altered triglyceride glucose index and fasted serum triglyceride high-density lipoprotein cholesterol ratio predict incidence of cardiovascular disease in the Mashhad cohort study.甘油三酯葡萄糖指数和空腹血清甘油三酯高密度脂蛋白胆固醇比值与心血管疾病的发生：马什哈德队列研究。
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Development of a prognostic prediction model to estimate the risk of multiple chronic diseases: constructing a copula-based model using Canadian primary care electronic medical record data.开发一种预后预测模型来估计多种慢性病的风险：使用加拿大初级保健电子病历数据构建基于 Copula 的模型。
Int J Popul Data Sci. 2021 Jan 19;6(1):1395. doi: 10.23889/ijpds.v5i1.1395.
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Association between the triglyceride to high-density lipoprotein cholesterol ratio and the risk of type 2 diabetes mellitus among Chinese elderly: the Beijing Longitudinal Study of Aging.甘油三酯与高密度脂蛋白胆固醇比值与中国老年人 2 型糖尿病风险的关系：北京老龄化纵向研究。
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