Chinese Journal of Multiple Organ Diseases in the Elderly · Oct 19, 2026
Correlation of lipoprotein-associated phospholipase A2 and myeloperoxidase with risk stratification in atherosclerotic cardiovascular disease among elderly patients with hypertension
By Qi Jingrui, Tian Panlin, Chen Wenqian et al.
Objective To investigate the correlation between lipoprotein-associated phospholipase A2 (Lp-PLA2) and myeloperoxidase (MPO) levels and arteriosclerotic cardiovascular disease (ASCVD) risk stratification in elderly hypertensive patients. Methods A single-center retrospective cross-sectional study was conducted on 264 elderly patients with hypertension who visited Cangzhou Central Hospital from January to June 2024. Based on the prediction for ASCVD risk in china(China-PAR) model (prediction for ASCVD risk in China), the patients were divided into a low-risk group (≤5.0%; n=51), a moderate-risk group (5.0%-10.0%; n=116), and a high-risk group (>10.0%; n97). The levels of Lp-PLA2 and MPO were measured and compared across groups using covariance analysis. Multivariate ordinal logistic regression analysis was performed to identify additional risk factors beyond the model. SPSS statistics 23.0 was used for statistical analysis. Data comparison between two groups was performed using t test, χ² test or analysis of variance depending on data type. Results The levels of Lp-PLA2 and MPO were significantly increased with the elevation of ASCVD risk stratification (P<0.001). Multivariate ordinal logistic regression analysis revealed significant associations between 10-year ASCVD risk (predicted by the China-PAR model) and Lp-PLA2 (OR=1.35,95%CI 1.18-1.56; P<0.001), MPO (OR=1.28,95%CI 1.10-1.51; P=0.015), fasting blood glucose (OR =1.32,95%CI 1.18-1.47; P<0.001), as well as low-density lipoprotein cholesterol (OR=1.26,95%CI 1.10-1.45; P<0.001). Conclusion Lp-PLA2 and MPO levels may serve as important inflammatory biomarkers for ASCVD risk prediction beyond the China-PAR model in elderly patients with hypertension, which may further optimize the predictive efficacy of the China-PAR model in this population and provide a scientific basis for precision prevention and treatment of cardiovascular diseases.