Abstract
BackgroundImproving the accuracy of 10-year cardiovascular risk prediction beyond established algorithms like SCORE2 is a clinical priority. The plasma ratio of polyunsaturated to monounsaturated fatty acids (PUFA/MUFA) is an objective marker of dietary fat quality, which is linked to cardiovascular health. This study aimed to evaluate whether adding the PUFA/MUFA ratio to the SCORE2 model improves the prediction of major adverse cardiovascular events (MACE).MethodsThis prospective cohort study included 183,237 UK Biobank participants aged 50-69 years, free of cardiovascular disease or diabetes at baseline. The plasma PUFA/MUFA ratio was quantified using high-throughput nuclear magnetic resonance (NMR) spectroscopy. The cohort was randomly split into training (70%) and validation (30%) sets. The predictive performance of the original SCORE2 model was compared to an extended model including the PUFA/MUFA ratio, using Harrell's C-index, Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI).ResultsIn the independent validation set (N = 54,971), a higher PUFA/MUFA ratio was associated with a lower risk of MACE. Adding the PUFA/MUFA ratio to the SCORE2 model resulted in a statistically significant increase in the C-index from 0.740 (95% CI: 0.736-0.743) to 0.744 (95% CI: 0.740-0.748) (P < 0.001). The extended model also showed significant risk reclassification, with An NRI of 7.5% (95% CI: 3.5-11.4%) And An IDI of 0.025 (95% CI: 0.016-0.034). Both models were well-calibrated.ConclusionsIncorporating the plasma PUFA/MUFA ratio into the SCORE2 algorithm provides a modest but statistically significant improvement in 10-year MACE risk prediction. As an objective biomarker of dietary fat quality, the PUFA/MUFA ratio shows promise as a supplementary tool for risk assessment, though its direct clinical impact requires further validation and consideration of cost-effectiveness.</p>