Study to Evaluate Correlation between Serum Uric Acid Levels and Severity of Coronary Artery Disease in Patients Undergoing Coronary Angiography at Tertiary Health Care Centre
Background: Coronary heart disease constitutes an immense public health problem. Myocardial Infarction is one of kind components of cardio vascular disease burden all around the world. Aim: Many epidemiologic studies have shown raised uric acid levels to predict increased risk of cardiovascular events. Studies have addressed the value of this biomarker across the whole range of patients with ACS (Acute Coronary Syndrome) especially in Indian scenarios. Thus, the aim of this study was to investigate whether there is an association between serum uric acid level with CAD (Coronary Artery Disease) risk factors and its severity in ACS patients. Also to know the prognostic value of serum uric acid levels in those patients undergoing coronary angiography for underlying coronary artery diseases. Material and Methods: This prospective observational study included 200 random patients admitted with Acute Coronary Syndrome in the ICU and medicine department of the institution. The presence and severity of CAD was determined by the following clinical vessel score; Absent: No coronary lesions, 1 vessel, 2 vessels and 3 vessels - disease based on the number of coronary arteries involved. The correlation of serum uric acid levels with CAD risk factors and the severity of CAD in the ACS patients was analysed statistically. Results: There was a significant association between uric acid and the coronary angiographic findings (P<0.001). The patients in the hyperuricemia group had more number of coronary vessels involved than the other group. Conclusion: The serum uric acid level is correlated with the presence and severity of CAD by coronary angiographic findings (P<0.001) in the Acute Coronary Syndrome patients. Uric acid being an inexpensive and easily available biochemical marker, it will be of much use in settings with restricted resources. Serum uric acid levels can be used to predict the severity of CAD.
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