Date of Graduation
Master of Science in Physician Assistant Studies
Background: Cardiovascular events are the leading cause of death in the United States. Providers use various risk factors as a guide to monitor and treat patient’s cardiovascular risk. Low-density lipoprotein cholesterol (LDL-C) has been used as a way to measure cholesterol, a known major risk factor of cardiovascular disease. This systematic review examines the importance of using LDL particle number in predicting future cardiovascular events compared to total LDL cholesterol, LDL-C.
Methods: An exhaustive search of available medical literature was conducted using Medline-OVID, Web of Science, CINAHL and EBMR Multifile databases. The following keywords were utilized as search terms: LDL particle number, LDL cholesterol, cardiovascular disease and nuclear magnetic resonance. Study quality was assessed using the GRADE system.
Results: This search resulted in 51articles. After unrelated articles were excluded, two cohort studies and one case-control study met criteria and were included in the review. The studies looked at LDL particle number and LDL-C with primary outcomes being cardiovascular events and coronary artery disease. Overall, when looking at LDL particle number compared to total LDL cholesterol, LDL particle number was more predictive of a future cardiovascular event. The quality of both the cohort studies were low and the case-control study was very low.
Conclusion: This systematic review demonstrated that LDL particle number is more predictive of future cardiovascular events when compared to LDL-C. The standard lipid panel continues to be a critical quantitative test to evaluate cholesterol, a major cardiovascular risk factor, but the implementation of looking at particle number as well should be performed and is an important aspect to further reduce risk of cardiovascular events and patient important outcomes.
Keywords: LDL particle number, LDL cholesterol, Cardiovascular disease, Nuclear Magnetic Resonance
Holmes, Heidi, "The Importance of LDL Particle Number in Predicting Risk of Cardiovascular Events" (2013). School of Physician Assistant Studies. 434.