Analysis of Platelet Morphological Parameters as Clinical Risk Stratification in Acute Coronary Syndrome

BackgroundPlatelet activation plays a central role in the pathogenesis of acute coronary syndrome (ACS). Platelet morphological parameters, including MPV, PDW, and P-LCR, are emerging as biomarkers for predicting the severity of ACS and prognosis. AimsThis study aims to assess the relationship between these parameters and coronary severity and to evaluate their predicting adverse outcomes. MethodsA total of 134 ACS patients and 50 healthy controls were included in this prospective observational study. Platelet morphological parameters (MPV, PDW, and P-LCR) were measured at admission, and coronary artery lesion severity was determined using the Gensini score from coronary angiography. Multivariate logistic regression analysis assessed the predictive value of these platelet parameters for adverse outcomes, and ROC curve analysis was used to evaluate their diagnostic performance. ResultsMPV, PDW, and P-LCR were significantly higher in ACS patients compared to healthy controls (p < 0.001). A strong positive correlation was found between platelet parameters and the Gensini score (MPV: r = 0.778, PDW: r = 0.800, P-LCR: r = 0.761; p < 0.001). Multivariate logistic regression identified MPV (OR = 1.807, p < 0.001), PDW (OR = 1.700, p = 0.001), and P-LCR (OR = 1.287, p < 0.001) as independent predictors of advent prognosis. ROC curve analysis showed that the combined use of MPV, PDW, and P-LCR provided superior predictive accuracy (AUC = 0.927) compared to the individual parameters. ConclusionElevated platelet morphological parameters are strongly associated with coronary artery lesion severity and serve as independent predictors of adverse outcomes in ACS patients. The combined assessment of MPV, PDW, and P-LCR enhances risk stratification, offering a valuable tool for guiding therapeutics and improving prognosis in management.