Zheng Ying-Ying, Wu Ting-Ting, Gao Ying, Guo Qian-Qian, Ma Yan-Yan, Zhang Jian-Chao, Xun Yi-Li, Wang Ding-Yu, Pan Ying, Cheng Meng-Die, Song Feng-Hua, Liu Zhi-Yu, Wang Kai, Jiang Li-Zhu, Fan Lei, Yue Xiao-Ting, Bai Yan, Zhang Zeng-Lei, Dai Xin-Ya, Zheng Ru-Jie, Chen You, Ma Xiang, Ma Yi-Tong, Zhang Jin-Ying, Xie Xiang
Department of Cardiology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Key Laboratory of Cardiac Injury and Repair of Henan Province, Zhengzhou, China.
Thromb Haemost. 2021 Mar;121(3):297-308. doi: 10.1055/s-0040-1718411. Epub 2020 Oct 31.
In the present study, we aimed to establish a novel score to predict long-term mortality of non-ST-segment elevation acute coronary syndrome (NSTE-ACS) patients who underwent percutaneous coronary intervention (PCI).
A total of 2,174 NSTE-ACS patients from the CORFCHD-ZZ study were enrolled as the derivation cohort. The validation cohort including 1,808 NSTE-ACS patients were from the CORFCHD-PCI study. Receiver operating characteristic analysis and area under the curve (AUC) evaluation were used to select the candidate variables. The model performance was validated internally and externally. The primary outcome was cardiac mortality (CM). We also explored the model performance for all-cause mortality (ACM).
Initially, 28 risk factors were selected and ranked according to their AUC values. Finally, we selected age, N-terminal pro-B-type natriuretic peptide, and creatinine to develop a novel prediction model named "ABC" model. The ABC model had a high discriminatory ability for both CM (C-index: 0.774, 0.001) and ACM (C-index: 0.758, 0.001) in the derivation cohort. In the validation cohort, the C-index of CM was 0.802 ( 0.001) and that of ACM was 0.797 ( 0.001), which suggested good discrimination. In addition, this model had adequate calibration in both the derivation and validation cohorts. Furthermore, the ABC score outperformed the GRACE score to predict mortality in NSTE-ACS patients who underwent PCI.
In the present study, we developed and validated a novel model to predict mortality in patients with NSTE-ACS who underwent PCI. This model can be used as a credible tool for risk assessment and management of NSTE-ACS after PCI.
在本研究中，我们旨在建立一种新的评分系统，以预测接受经皮冠状动脉介入治疗（PCI）的非ST段抬高型急性冠状动脉综合征（NSTE-ACS）患者的长期死亡率。
来自CORFCHD-ZZ研究的2174例NSTE-ACS患者被纳入推导队列。包括1808例NSTE-ACS患者的验证队列来自CORFCHD-PCI研究。采用受试者工作特征分析和曲线下面积（AUC）评估来选择候选变量。对模型性能进行内部和外部验证。主要结局为心脏性死亡（CM）。我们还探讨了该模型对全因死亡（ACM）的预测性能。
最初，根据AUC值选择并排列了28个危险因素。最后，我们选择年龄、N末端B型脑钠肽原和肌酐来建立一个名为“ABC”模型的新预测模型。ABC模型在推导队列中对CM（C指数：0.774，P<0.001）和ACM（C指数：0.758，P<0.001）均具有较高的鉴别能力。在验证队列中，CM的C指数为0.802（P<0.001），ACM的C指数为0.797（P<0.001），提示鉴别能力良好。此外，该模型在推导队列和验证队列中均具有良好的校准。此外，ABC评分在预测接受PCI的NSTE-ACS患者死亡率方面优于GRACE评分。
在本研究中，我们开发并验证了一种新的模型，用于预测接受PCI的NSTE-ACS患者的死亡率。该模型可作为PCI术后NSTE-ACS风险评估和管理的可靠工具。
