基于直接经皮冠状动脉介入治疗的 ST 段抬高型心肌梗死患者行 Naples 评分对长期死亡率的评估。

Evaluation of Naples Score for Long-Term Mortality in Patients With ST-Segment Elevation Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention.

机构信息

Department of Cardiology, Van Education and Research Hospital, Van, Turkey.

Department of Cardiology, Sultan Abdulhamid Han Education and Research Hospital, Istanbul, Turkey.

出版信息

Angiology. 2024 Sep;75(8):725-733. doi: 10.1177/00033197231170982. Epub 2023 Apr 14.

Abstract

The Naples score (NS), which is a composite of cardiovascular adverse event predictors including neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, albumin, and total cholesterol, has emerged as a prognostic risk score in cancer patients. We aimed to investigate the predictive value of NS for long-term mortality in ST-segment elevation myocardial infarction patients (STEMI). A total of 1889 STEMI patients were enrolled in this study. The median duration of the study was 43 months (IQR: 32-78). Patients were divided into 2 groups according to NS as group 1 and group 2. We created 3 models as a baseline model, model 1 (baseline + NS in continuous), and model 2 (baseline + NS as categorical). Group 2 patients had higher long-term mortality rates than group 1 patients. The NS was independently associated with long-term mortality and adding NS to a baseline model improved the model performance for prediction and discrimination of long-term mortality. Decision curve analysis demonstrated that model 1 had a better net benefit probability for detecting mortality compared with the baseline model. NS had the highest contributive significant effect in the prediction model. An easily accessible and calculable NS might be used for risk stratification of long-term mortality in STEMI patients undergoing primary percutaneous coronary intervention.

摘要

那不勒斯评分(NS)是一种心血管不良事件预测因子的综合指标,包括中性粒细胞与淋巴细胞比值、淋巴细胞与单核细胞比值、白蛋白和总胆固醇,已成为癌症患者的预后风险评分。我们旨在研究 NS 对 ST 段抬高型心肌梗死患者(STEMI)长期死亡率的预测价值。本研究共纳入 1889 例 STEMI 患者。研究的中位时间为 43 个月(IQR:32-78)。根据 NS 将患者分为两组:组 1 和组 2。我们创建了 3 个模型,分别为基础模型、模型 1(基础+连续 NS)和模型 2(基础+分类 NS)。组 2 患者的长期死亡率高于组 1 患者。NS 与长期死亡率独立相关,将 NS 添加到基础模型中可以提高模型对长期死亡率预测和区分的性能。决策曲线分析表明,与基础模型相比,模型 1 对检测死亡率具有更好的净获益概率。NS 在预测模型中具有最高的显著影响。一种易于获取和计算的 NS 可能用于接受直接经皮冠状动脉介入治疗的 STEMI 患者的长期死亡率风险分层。

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