258290 Risk Categorization Differences for Cardiovascular Disease Dependent upon Measurement Technology

Sunday, October 28, 2012

Rodney G. Bowden, PhD , School of Education, Baylor University, Waco, TX
Ronald L. Wilson, MD , Central Texas Nephrology Associates, Waco, TX
A. Alexander Beaujean, PhD, PhD , Department of Educational Psychology, Baylor University, Waco, TX
Background: Few studies have been conducted making comparisons between traditional measures of cholesterol and cholesterol subfractions and only one study has compared LDL particle number, LDL particle size, and LDL among End-Stage-Renal Disease (ESRD) patients. The purpose of this study was to examine the relationships between cholesterol measures and differences in risk stratification when using ATP-III guidelines. Methods: ESRD patients (N=1092) from clinics associated with the Central Texas Nephrology Associates were recruited to participate in this study. Blood samples were provided after a 12-hour fast. Results: LDL particle size categorized more patients at-risk when compared to LDL, non-HDL, and triglycerides. Pearson correlation coefficients revealed a strong significant correlation between LDL cholesterol and LDL particle number (r2=.908, p=.0001) and a significant correlation between LDL particle number and LDL particle size (r2= -.290, p =.0001). A significant but weak correlation existed between LDL cholesterol and LDL particle size (r2= .107, p=.0001). A significant correlation existed between LDL particle number and triglycerides (r2=.335, p=.0001) and a significant inverse relationship between LDL particle size and triglycerides (r2= -.500, p=.0001). Conclusions: LDL particle size categorized 732 (67.0%) more patients at-risk compared to LDL, 497 (45.5%) more compared to non-HDL, and 747 (68.4%) more compared to triglycerides. Our study seems to suggest that using LDL particle size may help to identify those who would not be considered at-risk using LDL, non-HDL or triglycerides alone and can be used as a further screening measure that may be more predictive of cardiovascular disease outcomes.

Learning Areas:
Chronic disease management and prevention
Epidemiology

Learning Objectives:
1. Participants will be able to describe the different cholesterol measurement technologies 2. Participants will be able to compare risk categorization based on ATP-III guidelines.

Keywords: Cholesterol, Chronic Diseases

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am the PI for this study
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.