Evaluation of Uric Acid to Albumin Ratio as a Marker of Coronary Artery Disease Severity in Acute Coronary Syndrome: A Cross-Sectional Study

Coronary artery disease (CAD) is a widespread cause of morbidity and mortality. Serum uric acid, a mediator of endothelial dysfunction and inflammation in vascular disease, can increase the risk of atherosclerosis, contributing to CAD. As serum albumin inhibits platelet activation and aggregation, low levels of it can contribute to platelet-induced coronary artery stenosis. Limited studies have been conducted worldwide in evaluating the role of uric acid to albumin ratio (UAR) in predicting severity or poor outcomes in acute coronary syndrome (ACS) patients. This study was undertaken to assess the role of UAR as a predictor of CAD severity, which can facilitate the identification of high-risk patients. A hospital-based analytical cross-sectional study was conducted in an urban tertiary healthcare center for a period of two months between June and August of 2022. A total of 100 ACS patients were included in the study. The study population included patients above the age of 18 years diagnosed with ACS who underwent a coronary angiography. Coronary angiograms were used to diagnose the presence of CAD, and its severity was assessed using Synergy between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) scores (SS). The correlation of UAR with CAD severity using SS was studied and compared between three varieties of ACS: ST-elevation myocardial infarction (STEMI), non-ST-elevation myocardial infarction (NSTEMI), and unstable angina (UA). Chi-squared tests were used to determine statistical significance for qualitative data. Independent t-tests were used to identify the mean difference between two quantitative variables. Receiver operating characteristic (ROC) curves were constructed for UAR and high SS. A comparison between UAR and neutrophil to lymphocyte ratio (NLR) as a predictor of disease severity was done. ROC and optimal cutoff points were chosen to calculate sensitivity, specificity, and positive and negative predictive values. Microsoft Excel (Microsoft, Redmond, WA, USA) and SPSS V22.0 (IBM Corp., Armonk, NY, USA) were used to analyze the data. A total of 100 ACS patients were included in the study and divided into two groups on the basis of SS, with 74% showing low severity and 26% showing intermediate-high severity. There was a statistically significant difference found between older age and SS (p=0.017). Our study showed 74% (n=74) of the patients were male and 26% (n=26) were female. It also revealed that 75.7% (n=56) of t