Why the study?
Non-traditional cardiovascular risk factors increasingly modify cardiovascular risk beyond traditional metrics, but further research is needed to precisely estimate the magnitude of their impact as risk and prognosis modifiers for inclusion in future risk charts.
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Design
Review
Non-traditional cardiovascular risk factors provide important prognostic information beyond traditional metrics and should be integrated into personalized patient assessment to reduce cardiovascular disease burden.
Non-traditional cardiovascular risk factors (RFs) are increasingly emerging as important modifiers of cardiovascular risk (CVR), offering insights beyond traditional metrics like hypertension, diabetes, and dyslipidemia. These include novel biomarkers, chronic conditions (e.g., chronic kidney disease and chronic obstructive pulmonary disease), environmental exposures, chronic inflammation, infections, psychosocial factors, and sex-specific conditions, all of which influence the prediction, management, and outcomes of cardiovascular disease (CVD). These additional RFs may impact on CVD prediction and add valid information during tailored patient assessment and management. Therefore, a careful assessment of both traditional and non-traditional cardiovascular RFs, with a personalized treatment, could dramatically reduce the total CVD burden. Nevertheless, further research is needed to precisely estimate the magnitude of their impact as risk and prognosis modifiers in order to be included in future risk charts. This review provides a critical analysis of non-traditional RFs, their pathophysiological mechanisms, and their implications for personalized care. Integrating these factors into CVR assessment can reclassify patient risk categories, optimize therapeutic strategies, and improve prognosis. However, further research is needed to refine their inclusion in risk charts and evaluate their impact on public health outcomes. A tailored, multidisciplinary approach is essential to reduce the burden of CVD and associated mortality.
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Perone et al. (2025) studied this question.
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