Abstract
This study aimed to explore the predictive value of the systemic inflammatory response index (SIRI) and the pan-immune-inflammatory value (PIV) in assessing the risk of myocardial infarction (MI) among UA cases. The risk factors were identified by univariate and binary logistic regression analyses, and the relationship between variables was analyzed using Pearson correlation analysis. The receiver operating characteristic (ROC) curve analysis was used to assess the predictive value of the indicators for MI in UA cases. No significant difference was found in gender, age, hypertension, body mass index (BMI), diabetes, alcohol consumption, smoking status, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), or hemoglobin (Hb) between the two groups (P > 0.05). Nevertheless, statistical differences were found in monocyte (MON), N-terminal pro-B-type natriuretic peptide (NT-proBNP), platelet count (PLT), lymphocyte count (LYM), neutrophil count (NEU), SIRI, and PIV (P < 0.05). Pearson correlation analysis indicated positive correlations between SIRI and PIV (r = 0.807), SIRI and NT-proBNP (r = 0.116), and PIV and NT-proBNP (r = 0.176) (all P < 0.05). Binary logistic regression analysis identified NT-proBNP, SIRI, and PIV as significant predictors of MI in UA cases (P < 0.05). ROC curve analysis demonstrated that SIRI achieved an area under the curve (AUC) of 0.851 (standard error (SE) = 0.027, 95% confidence interval (CI): 0.798-0.904), and the Youden index was 0.58 (specificity, 74.58%; sensitivity, 83.83%). PIV yielded an AUC of 0.902 (SE = 0.020, 95% CI: 0.863-0.940), and the Youden index was 0.68 (specificity, 80.97%; sensitivity, 86.76%). The united SIRI + PIV model yielded an AUC of 0.920 (SE = 0.016, 95% CI: 0.889-0.951), and the Youden index was 0.71 (specificity, 79.93%; sensitivity, 91.18%). Applying the optimal cutoff thresholds, the incidence of MI was lower in cases with SIRI ≤ 1.23 compared to SIRI > 1.23, and it was also found in cases with PIV ≤ 215.88 compared to PIV > 215.88 (P < 0.05). SIRI and PIV were found highly effective in predicting MI risk in UA cases, and their combination could further enhance the predictive performance.