Song Jingjing, Liu Yupeng, Wang Wenyao, Chen Jing, Yang Jie, Wen Jun, Gao Jun, Shao Chunli, Tang Yi-Da
State Key Laboratory of Cardiovascular Disease, Department of Cardiology, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Front Cardiovasc Med. 2022 Aug 17;9:897020. doi: 10.3389/fcvm.2022.897020. eCollection 2022.
Early detection of mortality after percutaneous coronary intervention (PCI) is crucial, whereas most risk prediction models are based on outdated cohorts before the year 2000. This study aimed to establish a nomogram predicting 30-day mortality after PCI.
In total, 10,444 patients undergoing PCI in National Center for Cardiovascular Diseases in China were enrolled to establish a nomogram to predict 30-day mortality after PCI. The nomogram was generated by incorporating parameters selected by logistic regression with the stepwise backward method.
Five features were selected to build the nomogram, including age, male sex, cardiac dysfunction, STEMI, and TIMI 0-2 after PCI. The performance of the nomogram was evaluated, and the area under the curves (AUC) was 0.881 (95% CI: 0.8-0.961). Our nomogram exhibited better performance than a previous risk model (AUC = 0.7, 95% CI: 0.586-0.813) established by Brener et al. The survival curve successfully stratified the patients above and below the median score of 4.
A novel nomogram for predicting 30-day mortality was established in unselected patients undergoing PCI, which may help risk stratification in clinical practice.
经皮冠状动脉介入治疗(PCI)后早期死亡的检测至关重要,而大多数风险预测模型基于2000年前的过时队列。本研究旨在建立一种预测PCI后30天死亡率的列线图。
总共纳入了中国国家心血管病中心接受PCI的10444例患者,以建立预测PCI后30天死亡率的列线图。通过将逐步向后法进行逻辑回归选择的参数纳入来生成列线图。
选择了五个特征来构建列线图,包括年龄、男性、心脏功能不全、ST段抬高型心肌梗死(STEMI)以及PCI后的心肌梗死溶栓治疗(TIMI)血流分级0-2级。对列线图的性能进行了评估,曲线下面积(AUC)为0.881(95%CI:0.8-0.961)。我们的列线图表现优于Brener等人先前建立的风险模型(AUC = 0.7,95%CI:0.586-0.813)。生存曲线成功地将得分中位数4以上和以下的患者进行了分层。
在未选择的接受PCI的患者中建立了一种预测30天死亡率的新型列线图,这可能有助于临床实践中的风险分层。