Suppr超能文献

用于预测冠心病风险的多种脂质评分系统:在非裔美国人中的应用。

Multiple lipid scoring system for prediction of coronary heart disease risk: application to African Americans.

作者信息

Everett Charles J, Mainous Arch G, Koopman Richelle J, Diaz Vanessa A

机构信息

Department of Family Medicine, Medical University of South Carolina, 295 Calhoun St., PO Box 250192, Charleston, SC 29425, USA.

出版信息

J Natl Med Assoc. 2006 Nov;98(11):1740-5.

Abstract

BACKGROUND

Clinicians often obtain a panel of lipids but then only use low-density-lipoprotein (LDL) cholesterol to make clinical decisions. We previously described the multiple lipid measure, a strategy that integrates information about seven lipid measures. Our current inquiry uses the multiple lipid measure to create a scoring system and validates that system in a second cohort.

METHODS AND RESULTS

A scoring system that uses total cholesterol, high-density lipoprotein (HDL) cholesterol, LDL cholesterol and triglycerides was developed and tested. African-American participants of the Atherosclerosis Risk in Communities (ARIC) Study were used to validate the multiple lipid measure score. For nonsmokers, scores > or = 2 had a hazard ratio of 4.25 (95% CI 1.92-9.40) compared to reference scores of < or = -3 in adjusted survival analysis predicting incident coronary heart disease risk in the ARIC. The best conventional single lipid measure for nonsmokers was LDL cholesterol. Compared to LDL cholesterol <100 mg/dl, those with LDL cholesterol > or = 160 mg/dl had a hazard ratio of 2.31 (95% CI 1.13-4.75). For current smokers, the best conventional lipid measure was the total cholesterol/HDL cholesterol ratio, which was similar in predictive ability to the multiple lipid measure score. However, the multiple lipid measure score predicted an additional 10% of the cohort at risk compared to the total cholesterol/HDL cholesterol ratio.

CONCLUSIONS

The use of the multiple lipid scoring system improves the assessment of incident coronary heart disease risk and may have utility for clinicians in integrating lipid values.

摘要

背景

临床医生常常获取一组血脂指标,但随后仅使用低密度脂蛋白(LDL)胆固醇来做出临床决策。我们之前描述了多重血脂测量法,这是一种整合七种血脂指标信息的策略。我们当前的研究使用多重血脂测量法创建了一个评分系统,并在第二个队列中对该系统进行了验证。

方法与结果

开发并测试了一种使用总胆固醇、高密度脂蛋白(HDL)胆固醇、LDL胆固醇和甘油三酯的评分系统。社区动脉粥样硬化风险(ARIC)研究中的非裔美国参与者被用于验证多重血脂测量评分。在ARIC中预测冠心病发病风险的调整生存分析中,对于不吸烟者,评分≥2的风险比为4.25(95%可信区间1.92 - 9.40),而参考评分为≤ - 3。对于不吸烟者,最佳的传统单一血脂指标是LDL胆固醇。与LDL胆固醇<100 mg/dl相比,LDL胆固醇≥160 mg/dl者的风险比为2.31(95%可信区间1.13 - 4.75)。对于当前吸烟者,最佳的传统血脂指标是总胆固醇/HDL胆固醇比值,其预测能力与多重血脂测量评分相似。然而,与总胆固醇/HDL胆固醇比值相比,多重血脂测量评分能额外预测10%的有风险队列。

结论

使用多重血脂评分系统可改善对冠心病发病风险的评估,可能对临床医生整合血脂值有帮助。

相似文献

4
Risk scores of common genetic variants for lipid levels influence atherosclerosis and incident coronary heart disease.
Arterioscler Thromb Vasc Biol. 2013 Sep;33(9):2233-9. doi: 10.1161/ATVBAHA.113.301236. Epub 2013 Jun 13.
5
Efficacy of cholesterol levels and ratios in predicting future coronary heart disease in a Chinese population.
Am J Cardiol. 2001 Oct 1;88(7):737-43. doi: 10.1016/s0002-9149(01)01843-4.
7
Non-high-density lipoprotein cholesterol and apolipoprotein B in the prediction of coronary heart disease in men.
Circulation. 2005 Nov 29;112(22):3375-83. doi: 10.1161/CIRCULATIONAHA.104.532499.
10
Lipids, apolipoproteins, and their ratios in relation to cardiovascular events with statin treatment.
Circulation. 2008 Jun 10;117(23):3002-9. doi: 10.1161/CIRCULATIONAHA.107.713438. Epub 2008 Jun 2.

本文引用的文献

1
2
Predicting coronary heart disease risk using multiple lipid measures.
Am J Cardiol. 2005 Apr 15;95(8):986-8. doi: 10.1016/j.amjcard.2004.12.043.
4
5
Apolipoproteins versus lipids as indices of coronary risk and as targets for statin treatment.
Lancet. 2003 Mar 1;361(9359):777-80. doi: 10.1016/s0140-6736(03)12663-3.
6
Nonfasting apolipoprotein B and triglyceride levels as a useful predictor of coronary heart disease risk in middle-aged UK men.
Arterioscler Thromb Vasc Biol. 2002 Nov 1;22(11):1918-23. doi: 10.1161/01.atv.0000035521.22199.c7.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验