Decoding the Lipid-Angiogram Link: Can Serum Lipid Profile Help Predict Your Clogged Arteries?
Year: 2024
Type: article
Study design: Observational Study
Abstract: Objective In this study, we aimed to analyze the correlation between lipid profile and angiographic profile in terms of vessel involvement, segment involvement, and angiographic severity in patients with acute coronary syndrome (ACS). Methods One hundred patients diagnosed with ACS for the first time and undergoing coronary catheterization were included. Fasting samples for lipids profile were obtained. Data were analyzed to determine if lipid parameters were related to the severity of coronary artery disease (CAD), as measured by the SYNTAX score, and the number and location of affected vessels. The SYNTAX score offers a robust and reliable method for assessing the severity of CAD. By providing a comprehensive and quantitative evaluation, it empowers clinicians to make informed decisions about patient management and optimize treatment outcomes. Results Total cholesterol (TC), non-high-density lipoprotein (non-HDL) cholesterol, and apolipoprotein (Apo) B/A ratio correlated positively with the number of vessels involved, i.e., single, double, or triple vessel disease (SVD, DVD, and TVD). Apo B/A also showed a significant relationship with left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA) involvement. RCA involvement had a significant association with TC and non-HDL levels. TC, non-HDL, and Apo B/A showed a significant relationship with mid-segment involvement. Apo A1 was found to have a significant inverse correlation, while Apo B, Apo B/A, and TC/HDL had a significant positive correlation with SYNTAX score class severity. Conclusions Our study revealed a strong association between lipid parameters and CAD severity, particularly in terms of vessel involvement and SYNTAX score. Elevated levels of TC, non-HDL cholesterol, and Apo B/A were linked to more extensive disease.
Source: Cureus
DOI: 10.7759/cureus.73454
Authors: Siddharth Gupta, Akash Priyadarshi, Mujahid Beg, MU Rabbani
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4404240979
