Comparative prognostic utility of conventional and novel lipid parameters for cardiovascular disease risk prediction: Do novel lipid parameters offer an advantage?

Autor: Luis Afonso, Pawan Hari, Ankit Rathod, Vikas Veeranna, Palaniappan Manickam, Apurva Badheka, Sony Jacob, Sidakpal S. Panaich
Rok vydání: 2011
Předmět:
Zdroj: Journal of Clinical Lipidology. 5:82-90
ISSN: 1933-2874
DOI: 10.1016/j.jacl.2010.12.001
Popis: Background Comparative data on the prognostic utility of novel lipid parameters vs. conventional lipid parameters in predicting coronary events are scant. Objective We sought to compare the predictive value of various lipid measures for coronary events and to further examine the incremental value of novel lipid parameters over traditional cardiovascular risk factors in estimating cardiac risk. Methods We performed a post-hoc analysis of the National Heart Lung and Blood Institute limited access dataset of Multi-Ethnic Study of Atherosclerosis subjects (n = 6693). The lipid measures considered in the estimation of coronary risk were conventional and novel lipid parameters, the latter included total low-density lipoprotein (LDL), high-density lipoprotein (HDL) and very low-density lipoprotein (VLDL)-particle concentrations (LDL-p, HDL-p and VLDL-p), LDL-p/HDL-p ratio, and LDL-p subfractions. The outcome measured was occurrence of any coronary event (CE) that included myocardial infarction, resuscitated cardiac arrest, cardiac death, and angina. Results During an average follow up of 4.5 years, 228 patients developed coronary events. In the multivariate Cox proportional hazards model, TC/HDL-c (HR: 3.27; 95% CI: 1.95 to 5.47, P Conclusion In our large study cohort, a predictive model for future coronary events incorporating the best-available novel lipid parameter (LDL-p/HDL-p ratio) was comparable with the same model that incorporated conventional lipid ratios such as the TC/HDL-c ratio . The use of LDL-p/HDL-p ratio did not appear to offer incremental value over more traditional risk prediction models.
Databáze: OpenAIRE