Identification of Predictable Biomarkers in Conjunction to Framingham Risk Score to Predict the Risk for Cardiovascular disease (CVD) in Non Cardiac Subjects BC23-BC27
Dr. Rama Krishna Reddy Y.V.,
Research Scholar, Department of Biochemistry, Frontier Lifeline Hospital, Mogappair, Chennai-600101, India.
Introduction: Although the cardiovascular disease (CVD) burden is rising in different countries, the morbidity and mortality rate is not reduced to much extent because of lack of application of the biomarkers for diagnosing CVD. Hence, we aimed to establish the predictable biomarkers in conjunction to framingham risk score in order to predict the risk for CVD in non cardiac patients.
Materials and Methods: Three hundred subjects were screened for the study who came for the master health checkup. Out of them 50 patients were excluded as they were under medication. 23 patients were excluded due to various systemic diseases like fever and infection etc. The remaining of 227 patients with age range of 30-80 y was randomly selected for investigation. These subjects were divided into four different groups: Group I â€“ controls with age range: 30-60 y (n=50) these subjects were free from all the systemic ailments and risk factors. Study groups comprised of Group II - (n=44) with age range: 30-40 y, Group III - (n=50) with age range: 41-50 y and Group IV - (n=83) with age range: 51-80 y. Patients with different risk factors without medication participated as study groups. Routine biochemical parameters were analysed using fully automated analyser and atherosclerotic biomarkers was analysed using ELISA kit. In addition to this, framingham risk scores was calculated in all the groups, for 30 y risk prognosis for CVD.
Results: The atherosclerotic biomarkers such as E-selectin, Leptin, osteoprotegerin (OPG) and Ox-LDL were elevated among the study groups as compared to control group. Pearson correlation showed a significant association between the individual risk score (30 y framingham risk for CVD) of individuals, and the above biomarkers. The Receiver operating curve (ROC) analysis also showed a greater area under curve with higher sensitivity and specificity.
Conclusion: We conclude the application E-Selectin, leptin, OPG and Ox-LDL as biomarkers along with the framingham risk scores in prediction risk for CVD in the individuals with subclinical atherosclerosis. It is more reliable and predictable as compared to the individual biomarkers alone.