Sufyan Ibrahim1, Anurupa Udupi1, Cleeta Rebeiro2, Varashree Bolar Suryakanth2, Asha Kamath3, Revathi Panduranga Shenoy2. 1. Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India. 2. Department of Biochemistry, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India. 3. Department of Data Science, Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Abstract
Background: Globally, cardiovascular diseases (CVDs) are the leading cause of death and disability. Elevated low-density lipoprotein-cholesterol (LDL-C) and more specifically, elevation of its small, dense phenotype (sdLDL-C) has been regarded as the key modifiable risk factors associated with atherogenesis. This study aimed to determine the association of LDL-C and sdLDL-C with the development of CVDs in the next six months to establish their predictive efficacy. Methods: A batch of 162 anonymized serum samples sent for analysis of lipid profile parameters, were classified into tests and controls based on the calculated LDL-C values obtained by Fried Ewald formula. Direct LDL-C was also estimated automatically using assay kits. Using the formula provided by Srisawasdi et al., sdLDL-C was then computed for all samples. Six months later, samples were deanonymized, and the lipid profiles were compared with cardiovascular outcomes of these patients, to determine which parameter had the greatest correlation. Results: Four control group patients and three test group patients developed the outcome (any cardiovascular event) during the 6-month follow-up period. Binary logistic regression analysis showed that none of the lipid profile parameters: calculated LDL-C (OR= 0.99; 95% CI= 0.97-1.01; p= 0.826), direct LDL-C (OR= 0.99; 95% CI= 0.97-1.01; p= 0.818) or sdLDL-C (OR= 0.99; 95% CI= 0.93-1.04; p= 0.734), were significantly associated with the occurrence of outcome. The median % sdLDL-C both with respect to direct and calculated LDL-C was slightly higher in patients with the outcome. Conclusion: The levels of LDL-C or its individual phenotypes may not be used singly as indicator of cardiovascular morbidity in the next six months.
Background: Globally, cardiovascular diseases (CVDs) are the leading cause of death and disability. Elevated low-density lipoprotein-cholesterol (LDL-C) and more specifically, elevation of its small, dense phenotype (sdLDL-C) has been regarded as the key modifiable risk factors associated with atherogenesis. This study aimed to determine the association of LDL-C and sdLDL-C with the development of CVDs in the next six months to establish their predictive efficacy. Methods: A batch of 162 anonymized serum samples sent for analysis of lipid profile parameters, were classified into tests and controls based on the calculated LDL-C values obtained by Fried Ewald formula. Direct LDL-C was also estimated automatically using assay kits. Using the formula provided by Srisawasdi et al., sdLDL-C was then computed for all samples. Six months later, samples were deanonymized, and the lipid profiles were compared with cardiovascular outcomes of these patients, to determine which parameter had the greatest correlation. Results: Four control group patients and three test group patients developed the outcome (any cardiovascular event) during the 6-month follow-up period. Binary logistic regression analysis showed that none of the lipid profile parameters: calculated LDL-C (OR= 0.99; 95% CI= 0.97-1.01; p= 0.826), direct LDL-C (OR= 0.99; 95% CI= 0.97-1.01; p= 0.818) or sdLDL-C (OR= 0.99; 95% CI= 0.93-1.04; p= 0.734), were significantly associated with the occurrence of outcome. The median % sdLDL-C both with respect to direct and calculated LDL-C was slightly higher in patients with the outcome. Conclusion: The levels of LDL-C or its individual phenotypes may not be used singly as indicator of cardiovascular morbidity in the next six months.
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