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与小高密度脂蛋白相比,大高密度脂蛋白联合炎症因子是冠状动脉疾病更优的预测指标。

Large HDL combined with inflammatory factors as superior predictors for coronary artery disease than small HDL.

作者信息

Wu Xiaoying, He Zhijian, Sun Runlu, Xie Xiangkun, Chen Qingqun, Wang Junjie, Bao Jinlan, Huang Jingjing, Jiang Yuan, Zhang Yuling, Wang Jingfeng

机构信息

Cardiovascular Medicine Department, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.

Cardiovascular Medicine Department, The First Affiliated Hospital/School of Clinical Medicine, Guangdong Pharmaceutical University, Guangzhou, China.

出版信息

Ann Transl Med. 2021 Apr;9(8):672. doi: 10.21037/atm-21-948.

Abstract

BACKGROUND

This study investigated whether combinations of high-density lipoprotein (HDL) subfractions and inflammatory markers would add value to coronary artery disease (CAD) prediction.

METHODS

Non-CAD subjects (n=245) were stratified into low/moderate/high-Framingham risk (L/M/H-FR) groups and 180 CAD patients were enrolled. Levels of HDL-C, HDL, HDL, monocyte chemoattractant protein-1 (MCP-1), and high-sensitivity C-reactive protein (hsCRP) were measured. Multivariable logistic models for CAD were estimated with a single parameter or all parameters together after adjustment for conventional risk factors (CRFs), and Z statistics, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to compare discrimination among different models.

RESULTS

The results show that HDL-C, HDL and HDL gradually decreased, while MCP-1 and hsCRP gradually increased from L/M/H-FR to the CAD group. When applying a single factor in the CRFs-adjusted models, HDL-C (OR 0.011, 95% CI, 0.002-0.071, P<0.05) and HDL (OR 0.000072, 95% CI, 0.000001-0.004, P<0.05), but not HDL, were significantly related to CAD risk. Only HDL (OR 0.000072, 95% CI, 0.000001-0.004, P<0.001) remained significant when applying all HDL parameters. In the model including all HDL and inflammatory parameters, HDL (OR 0.001, 95% CI, 0.000027-0.051), MCP-1 (OR 1.066, 95% CI, 1.039-1.094), and hsCRP (OR 1.130, 95% CI, 1.041-1.227) showed significant differences (all P<0.05). This combined model showed improved discrimination over the models with a single factor (P<0.05) or all HDL parameters (Z=3.299, NRI =0.179, IDI =0.081, P<0.001).

CONCLUSIONS

Large HDL is superior to small HDL in the inverse association with CAD. The combination of HDL, MCP-1, and hsCRP with CRFs provides an optimal prediction for CAD.

摘要

背景

本研究调查了高密度脂蛋白(HDL)亚组分与炎症标志物的组合是否会增加冠状动脉疾病(CAD)预测的价值。

方法

将非CAD受试者(n = 245)分为低/中/高弗明翰风险(L/M/H-FR)组,并纳入180例CAD患者。测量HDL-C、HDL、HDL、单核细胞趋化蛋白-1(MCP-1)和高敏C反应蛋白(hsCRP)的水平。在调整传统风险因素(CRF)后,用单个参数或所有参数一起估计CAD的多变量逻辑模型,并使用Z统计量、净重新分类改善(NRI)和综合判别改善(IDI)来比较不同模型之间的判别能力。

结果

结果显示,从L/M/H-FR组到CAD组,HDL-C、HDL和HDL逐渐降低,而MCP-1和hsCRP逐渐升高。在经CRF调整的模型中应用单个因素时,HDL-C(比值比[OR]0.011,95%置信区间[CI],0.002 - 0.071,P < 0.05)和HDL(OR 0.000072,95% CI,0.000001 - 0.004,P < 0.05)与CAD风险显著相关,但HDL不相关。应用所有HDL参数时,只有HDL(OR 0.000072,95% CI,0.000001 - 0.004,P < 0.001)仍具有显著性。在包括所有HDL和炎症参数的模型中,HDL(OR 0.001,95% CI,0.000027 - 0.051)、MCP-1(OR 1.066,95% CI,1.039 - 1.094)和hsCRP(OR 1.130,95% CI,1.041 - 1.227)显示出显著差异(均P < 0.05)。与单因素模型(P < 0.05)或所有HDL参数模型相比,该联合模型的判别能力有所提高(Z = 3.299,NRI = 0.179,IDI = 0.081,P < 0.001)。

结论

大颗粒HDL在与CAD的负相关中优于小颗粒HDL。HDL、MCP-1和hsCRP与CRF的组合可为CAD提供最佳预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2d3/8106016/b19063fd0930/atm-09-08-672-f1.jpg

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