Oxidative Stress and Lipid Biomarkers as Predictors of Hypertension Severity: A Cross-Sectional Study

Abstract

ABSTRACT

Background: Hypertension is a major risk factor for cardiovascular morbidity and mortality, yet predicting disease severity remains a clinical challenge. Oxidative stress and lipid biomarkers are increasingly recognized as important contributors to vascular dysfunction. This study aimed to assess the predictive role of malondialdehyde (MDA), oxidized LDL (ox-LDL), and lipid profile parameters in determining hypertension severity.

Methods: We conducted a cross-sectional study among hypertensive patients aged 30–65 years. Clinical data and fasting blood samples were obtained. Serum lipid profile was analyzed using enzymatic assays; MDA  and ox-LDL concentrations were measured by ELISA. Multiple linear regression was applied to identify independent predictors of systolic blood pressure (SBP), and receiver operating characteristic (ROC) curve analysis was used to evaluate diagnostic accuracy for severe hypertension.

Results: Regression analysis revealed that MDA and ox-LDL were significant independent predictors of SBP, while HDL-C showed an inverse association, indicating a protective role. Traditional lipid parameters, including total cholesterol, triglycerides, and LDL-C, did not demonstrate significant predictive value. ROC analysis indicated that MDA had the strongest predictive ability for severe hypertension, whereas ox-LDL and LDL-C showed limited discriminative performance.

Conclusion: MDA and ox-LDL are significantly associated with hypertension severity, with MDA demonstrating moderate predictive performance. HDL-C exhibited a protective effect, while routine lipid parameters were less informative. These findings highlight the potential of incorporating oxidative stress biomarkers into hypertension risk assessment to improve early detection and personalized management.