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血脂水平及血脂异常不同临床分类与糖尿病肾病的相关性及预测价值研究

OBJECTIVE: To explore the relationship between blood lipid indicators and different clinical classifications of dyslipidemia and diabetic kidney disease (DKD) and to compare the value of different clinical classifications of dyslipidemia for predicting DKD. METHODS: Continuously enrollment of subjec...

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Formato: Online Artículo Texto
Lenguaje:English
Publicado: 四川大学学报(医学版)编辑部 2023
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10579073/
https://www.ncbi.nlm.nih.gov/pubmed/37866961
http://dx.doi.org/10.12182/20230960103
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description OBJECTIVE: To explore the relationship between blood lipid indicators and different clinical classifications of dyslipidemia and diabetic kidney disease (DKD) and to compare the value of different clinical classifications of dyslipidemia for predicting DKD. METHODS: Continuously enrollment of subjects was conducted at the First Affiliated Hospital of Chongqing Medical University and the Yongchuan Hospital of Chongqing Medical University between October 2020 and October 2021. A total of 356 type 2 diabetes mellitus (T2DM) patients admitted to the two hospitals were enrolled. They were divided into DKD group (n=126) and simple T2DM group (n=230) according to whether their T2DM was combined with DKD. In addition, 250 healthy individuals undergoing physical examination during the same period were enrolled for the control group. The blood pressure, blood lipid, blood glucose, and the kidney function indicators of the three groups were measured. The effects of different classifications of dyslipidemia on DKD were analyzed with unconditional logistic regression models, the receiver operating characteristic (ROC) curve was constructed, the area under the curve (AUC) of ROC was calculated, and the value of different classifications of dyslipidemia for predicting DKD was analyzed. RESULTS: The diastolic blood pressure (DBP), systolic blood pressure (SBP), total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-C), serum creatinine (Scr), uric acid (UA), and glycosylated hemoglobin A1c (HbA1c) of the DKD group and the simple T2DM group were significantly higher than those of the control group, while the high-density lipoprotein cholesterol (HDL-C) levels of the DKD group and the simple T2DM group were lower than that of the control group (all P<0.05). The disease course of T2DM, DBP, SBP, TC, TG, Scr, UA and HbA1c of the DKD group were significantly higher than those of the T2DM group (all P<0.05). After adjusting for the effects of T2DM disease course, DBP, SBP, Scr, UA and HbA1c, the results showed that TC (OR=1.426, 95%CI: 1.088-1.868) and TG (OR=1.404, 95%CI: 1.075-1.833) were independent risk factors for DKD, and that hypercholesterolemia (OR=1.817, 95%CI: 1.040-3.177) and mixed hyperlipidemia (OR=2.148, 95%CI: 1.110-4.159) were independent risk factors for DKD (all P<0.05). The AUC (95%CI) of hypercholesterolemia was 0.789 (0.729-0.871). The AUC (95%CI) of mixed hyperlipidemia was 0.671 (0.579-0.760). Hypercholesterolemia showed better predictive value for the diagnosis and prediction of DKD. CONCLUSION: Among the blood lipid indicators, TC and TG are independent risk factors of DKD. In the clinical classifications of dyslipidemia, hypercholesterolemia and mixed hyperlipidemia are independent risk factors of DKD. Hypercholesterolemia can be used as a predictor to screen for DKD among T2DM patients and is well suited for extensive application in outpatient screening.
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spelling pubmed-105790732023-10-18 血脂水平及血脂异常不同临床分类与糖尿病肾病的相关性及预测价值研究 Sichuan Da Xue Xue Bao Yi Xue Ban 临床研究 OBJECTIVE: To explore the relationship between blood lipid indicators and different clinical classifications of dyslipidemia and diabetic kidney disease (DKD) and to compare the value of different clinical classifications of dyslipidemia for predicting DKD. METHODS: Continuously enrollment of subjects was conducted at the First Affiliated Hospital of Chongqing Medical University and the Yongchuan Hospital of Chongqing Medical University between October 2020 and October 2021. A total of 356 type 2 diabetes mellitus (T2DM) patients admitted to the two hospitals were enrolled. They were divided into DKD group (n=126) and simple T2DM group (n=230) according to whether their T2DM was combined with DKD. In addition, 250 healthy individuals undergoing physical examination during the same period were enrolled for the control group. The blood pressure, blood lipid, blood glucose, and the kidney function indicators of the three groups were measured. The effects of different classifications of dyslipidemia on DKD were analyzed with unconditional logistic regression models, the receiver operating characteristic (ROC) curve was constructed, the area under the curve (AUC) of ROC was calculated, and the value of different classifications of dyslipidemia for predicting DKD was analyzed. RESULTS: The diastolic blood pressure (DBP), systolic blood pressure (SBP), total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-C), serum creatinine (Scr), uric acid (UA), and glycosylated hemoglobin A1c (HbA1c) of the DKD group and the simple T2DM group were significantly higher than those of the control group, while the high-density lipoprotein cholesterol (HDL-C) levels of the DKD group and the simple T2DM group were lower than that of the control group (all P<0.05). The disease course of T2DM, DBP, SBP, TC, TG, Scr, UA and HbA1c of the DKD group were significantly higher than those of the T2DM group (all P<0.05). After adjusting for the effects of T2DM disease course, DBP, SBP, Scr, UA and HbA1c, the results showed that TC (OR=1.426, 95%CI: 1.088-1.868) and TG (OR=1.404, 95%CI: 1.075-1.833) were independent risk factors for DKD, and that hypercholesterolemia (OR=1.817, 95%CI: 1.040-3.177) and mixed hyperlipidemia (OR=2.148, 95%CI: 1.110-4.159) were independent risk factors for DKD (all P<0.05). The AUC (95%CI) of hypercholesterolemia was 0.789 (0.729-0.871). The AUC (95%CI) of mixed hyperlipidemia was 0.671 (0.579-0.760). Hypercholesterolemia showed better predictive value for the diagnosis and prediction of DKD. CONCLUSION: Among the blood lipid indicators, TC and TG are independent risk factors of DKD. In the clinical classifications of dyslipidemia, hypercholesterolemia and mixed hyperlipidemia are independent risk factors of DKD. Hypercholesterolemia can be used as a predictor to screen for DKD among T2DM patients and is well suited for extensive application in outpatient screening. 四川大学学报(医学版)编辑部 2023-09-20 /pmc/articles/PMC10579073/ /pubmed/37866961 http://dx.doi.org/10.12182/20230960103 Text en © 2023《四川大学学报(医学版)》编辑部 版权所有 https://creativecommons.org/licenses/by-nc/4.0/开放获取 本文遵循知识共享署名—非商业性使用4.0国际许可协议(CC BY-NC 4.0),允许第三方对本刊发表的论文自由共享(即在任何媒介以任何形式复制、发行原文)、演绎(即修改、转换或以原文为基础进行创作),必须给出适当的署名,提供指向本文许可协议的链接,同时标明是否对原文作了修改;不得将本文用于商业目的。CC BY-NC 4.0许可协议访问 https://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International license (CC BY-NC 4.0). In other words, the full-text content of the journal is made freely available for third-party users to copy and redistribute in any medium or format, and to remix, transform, and build upon the content of the journal. You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may not use the content of the journal for commercial purposes. For more information about the license, visit https://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
spellingShingle 临床研究
血脂水平及血脂异常不同临床分类与糖尿病肾病的相关性及预测价值研究
title 血脂水平及血脂异常不同临床分类与糖尿病肾病的相关性及预测价值研究
title_full 血脂水平及血脂异常不同临床分类与糖尿病肾病的相关性及预测价值研究
title_fullStr 血脂水平及血脂异常不同临床分类与糖尿病肾病的相关性及预测价值研究
title_full_unstemmed 血脂水平及血脂异常不同临床分类与糖尿病肾病的相关性及预测价值研究
title_short 血脂水平及血脂异常不同临床分类与糖尿病肾病的相关性及预测价值研究
title_sort 血脂水平及血脂异常不同临床分类与糖尿病肾病的相关性及预测价值研究
topic 临床研究
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10579073/
https://www.ncbi.nlm.nih.gov/pubmed/37866961
http://dx.doi.org/10.12182/20230960103
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