Relationship Between 8-iso-prostaglandin-F and Predicted 10-Year Cardiovascular Risk in Hypertensive Patients.

BACKGROUND

8-iso-prostaglandin-F (8-iso-PGF) is a recognized marker of oxidative stress. Previous studies suggested that 8-iso-PGF plays an important role in the pathogenesis of hypertension and cardiovascular (CV) diseases. However, limited data exist on the prognostic role of 8-iso-PGF in hypertensive patients undergoing primary prevention. The aim of this study was to assess the relationship between 8-iso-PGF and 10-year CV risk, as predicted by validated equations in hypertension patients without CV diseases.

MATERIALS AND METHODS

A total of 432 individuals aged 40-75 years were enrolled. Plasma 8-iso-PGF was assessed through the ELISA method. CV risk was calculated by using the Framingham Risk Score (Fr-S) and the Atherosclerosis Cardiovascular Disease Risk Score (ASCVD-S). Low, moderate, or high CV risks were defined according to validated cutoffs.

RESULTS

Individuals with higher CV risk had significantly greater 8-iso-PGF values compared to those with low or moderate CV risk ( < 0.001). 8-iso-PGF correlated strongly with Fr-S and ASCVD-S in the entire population and in patients with normal renal function (all < 0.001) but not in patients with eGFR < 60 mL/min/1.73 m. These associations remained significant after adjustment for traditional factors included in the CV risk equations in the overall population and in patients with normal renal function. The 8-iso-PGF cutoffs that best distinguished patients with high CV risk were 310 pg/mL for Fr-S and 264 pg/mL for ASCVD-S in the overall population, with significant differences between the groups divided by eGFR (all < 0.001).

CONCLUSIONS

These findings highlight the potential utility of 8-iso-PGF as a biomarker for refining cardiovascular risk stratification in hypertensive patients, particularly those with preserved renal function. Future studies should explore its prognostic value in longitudinal cohorts and assess its integration into clinical risk models to enhance early prevention strategies for cardiovascular disease.