Evaluation of Efficacy of Inflammatory Novel Biomarkers for Risk Prediction of Cardiovascular Disease among Clinically Asymptomatic Individuals – A Systematic Review

Background: Cardiovascular disease (CVD) is the leading cause of death worldwide; hence, improved risk screening and prediction techniques are essential. This thorough analysis explores novel inflammatory biomarkers that might change the approach by which CVD is predicted in those who lack symptoms. Using a thorough analysis of the current state of prediction tactics and an intensive examination of their CVD events, this present research aims to provide the door to a more accurate and preventive approach to CVD prevention. Methodology: We extensively searched literature from 2012 to 2023, using databases such as Medline, Web of Science, PubMed, the Cochrane Library, and sources such as Google Scholar, Science Direct, and clinical trials. In this review, various study types were screened, including trials, commentaries, and editorials. To evaluate bias, we employed a two-part tool addressing five domains: selection bias, presentation bias, attrition bias, selective reporting, and different biases. In addition, a quality assessment tool was used for diagnostic accuracy studies. Results: In this current review, randomized controlled trials (RCTs) were included from 2012 to 2023. After the screening, approximately 10 RCTs (n = 43,879 patients) were incorporated into the present investigation. The average follow-up duration of these included studies was found to be around 6.49 years. The overall scenario of these trials reported that the maximum number of participants were male. Furthermore, our findings suggest that several serum biomarkers, especially hs-CRP and NT-proBNP, Gal-3, GDF-15, ST-2, etc., have the potential to improve primary CVD risk prevention among asymptomatic individuals. Conclusion: This systematic review highlights the critical importance of the utilization of biomarkers across diverse pathophysiological pathways as essential tools for the stratification of CVD risk in order to improve clinical outcomes. Keywords: Biomarkers, cardiovascular disease, fetal disease, heart failure, mortality, myocardial infraction