Wang Huaigen, Ma Aiqun, Wang Tingzhong
Department of Cardiovascular Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.
Shaanxi Key Laboratory of Molecular Cardiology (Xi'an Jiaotong University), Xi'an, Shaanxi, People's Republic of China.
Int J Gen Med. 2024 Apr 29;17:1713-1722. doi: 10.2147/IJGM.S457236. eCollection 2024.
Approximately 50% of ST-segment elevation myocardial infarction (STEMI) patients have multivessel coronary artery disease (MVD). The management strategy for these patients remains controversial. This study aimed to develop predictive models and nomogram of outcomes in STEMI patients with MVD for better identification and classification.
The least absolute shrinkage and selection operator (LASSO) method was used to select the features most significantly associated with the outcomes. A Cox regression model was built using the selected variables. One nomogram was computed from each model, and individual risk scores were obtained by applying the nomograms to the cohort. After regrouping patients based on nomogram risk scores into low- and high-risk groups, we used the Kaplan-Meier method to perform survival analysis.
The C-index of the major adverse cardiovascular event (MACE)-free survival model was 0·68 (95% CI 0·62-0·74) and 0·65 [0·62-0·68]) at internal validation, and that of the overall survival model was 0·75 (95% CI 0·66-0·84) and (0·73 [0·65-0·81]). The predictions of both models correlated with the observed outcomes. Low-risk patients had significantly lower probabilities of 1-year or 3-year MACEs (4% versus 11%, = 0.003; 7% versus 15%, =0.01, respectively) and 1-year or 3-year all-cause death (1% versus 3%, =0.048; 2% versus 7%, respectively, =0.001) than high-risk patients.
Our nomograms can be used to predict STEMI and MVD outcomes in a simple and practical way for patients who undergo primary PCI for culprit vessels and staged PCI for non-culprit vessels.
约50%的ST段抬高型心肌梗死（STEMI）患者患有多支冠状动脉疾病（MVD）。这些患者的治疗策略仍存在争议。本研究旨在建立STEMI合并MVD患者预后的预测模型和列线图，以更好地进行识别和分类。
采用最小绝对收缩和选择算子（LASSO）方法选择与预后最显著相关的特征。使用选定变量建立Cox回归模型。从每个模型计算一个列线图，并通过将列线图应用于队列获得个体风险评分。根据列线图风险评分将患者重新分组为低风险和高风险组后，我们使用Kaplan-Meier方法进行生存分析。
主要不良心血管事件（MACE）无事件生存模型在内部验证时的C指数为0·68（95%CI 0·62 - 0·74）和0·65[0·62 - 0·68]），总生存模型的C指数为0·75（95%CI 0·66 - 0·84）和（0·73[0·65 - 0·81]）。两个模型的预测均与观察到的结果相关。低风险患者1年或3年发生MACE的概率（分别为4%对11%，P = 0.003；7%对15%，P = 0.01）以及1年或3年全因死亡的概率（分别为1%对3%，P = 0.048；2%对7%，P = 0.001）均显著低于高风险患者。
我们的列线图可用于以简单实用的方式预测接受罪犯血管直接经皮冠状动脉介入治疗（PCI）和非罪犯血管分期PCI的STEMI和MVD患者的预后。
