The Combination Effect of the Red Blood Cell Distribution Width and Prognostic Nutrition Index on the Prognosis in Patients Undergoing PCI

红细胞分布宽度和预后营养指数联合评估经皮冠状动脉介入治疗患者预后的影响

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Abstract

BACKGROUND: Inflammation and malnutrition are related to adverse clinical outcomes in patients with coronary artery disease (CAD). However, it is unclear whether there is a relationship between the PNI (prognostic nutritional index) and RDW (red blood cell distribution width) regarding the impact on the prognosis in patients with CAD undergoing percutaneous coronary intervention (PCI). METHODS: A total of 5605 consecutive CAD patients undergoing PCI were selected retrospectively. The patients were stratified into four groups according to the PNI [high PNI (H-PNI) and low PNI (L-PNI)] and RDW [high RDW (H-RDW) and low RDW (L-RDW)]. The cutoff values of RDW and PNI were calculated using receiver-operating characteristic curve analysis. The primary endpoint was 1-year all-cause mortality (ACM). The secondary endpoint was major adverse cardiac cerebrovascular events (MACCEs), the composite of cardiac death (CD), the recurrence of MI, target lesion revascularization (TLR), and stroke. A Cox proportional hazards model was used to evaluate the association between the PNI, RDW, and clinical endpoints. RESULTS: During 1-year follow-up, 235 (4.19%) patients died. In multivariate regression analysis, the L-PNI/H-RDW group was found to have the highest risk of 1-year ACM [hazard ratio (HR) = 8.85, 95% confidence interval (CI): 5.96-13.15, p = 0.020] with the H-PNI/L-RDW group as a reference, followed by the L-PNI/L-RDW (HR = 3.96, 95% CI: 2.60-6.00, p < 0.001) and H-RDW/H-PNI groups (HR = 3.00, 95% CI: 1.99-4.50, p < 0.001). Nomograms were developed to predict the probability of 1-year ACM and MACCEs. CONCLUSIONS: CAD patients with L-PNI and H-RDW experienced the worst prognosis. The combination of PNI and RDW was a strong predictor of 1-year ACM. The coexistence of PNI and RDW appears to have a synergistic effect, providing further information for the risk stratification of CAD patients.

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