Analysis of predictive factors and model construction for in-hospital major adverse cardiovascular events following percutaneous coronary intervention in patients with acute myocardial infarction
10.3969/j.issn.1008-9691.2024.05.005
- VernacularTitle:急性心肌梗死经皮冠脉介入术后发生院内主要不良心血管事件的预测因素分析及模型构建
- Author:
Yanji GUO
1
;
Chenglin LIU
;
Manman WANG
;
Meng SHI
;
Yong LI
;
Ruomeng LI
;
Min FU
;
Ziya XIAO
Author Information
1. 济宁医学院附属医院急诊科,山东济宁 272100
- Publication Type:Journal Article
- Keywords:
Acute myocardial infarction;
In-hospital major adverse cardiovascular events;
Nomogram;
Predictive value
- From:
Chinese Journal of Integrated Traditional and Western Medicine in Intensive and Critical Care
2024;31(5):549-554
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the potential factors influencing the occurrence of major adverse cardiovascular events (MACE) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI) and develop an efficient and accurate predictive model. Methods Clinical data of AMI patients treated in the emergency department of Jining Medical University Affiliated Hospital between January and December 2020 were retrospectively collected. Patients were divided into two groups based on the occurrence of in-hospital MACE,the MACE group and the non-MACE group. Clinical indicators of the two groups were compared,and statistically significant variables were selected for inclusion in a multivariate logistic regression analysis. Based on this analysis,a nomogram model was constructed to predict the risk of in-hospital MACE in AMI patients after PCI. The model's predictive accuracy was evaluated using the receiver operating characteristic (ROC) curve,and the goodness of fit was assessed using the Hosmer-Lemeshow test. Results A total of 583 patients were included after screening based on inclusion and exclusion criteria,of whom 85 (14.58％) experienced in-hospital MACE. Univariate analysis showed that compared to the non-MACE group,the MACE group had higher values for age,Killip classification,myoglobin (MYO),brain natriuretic peptide (BNP),white blood cell count (WBC),prothrombin time (PT),T-wave changes on electrocardiogram (ECG),abnormal wall motion on echocardiography,ischemia duration greater than 6 hours,the number of MACE before PCI,and left anterior descending artery stenosis. In contrast,the number of patients with a history of oral antiplatelet medication use,coronary artery disease (CAD),family history of CAD,admission systolic blood pressure,and left ventricular ejection fraction (LVEF) were lower in the MACE group. Multivariate analysis indicated that Killip classification,BNP,ischemia duration greater than 6 hours,and MACE before PCI were independent risk factors for in-hospital MACE in AMI patients after PCI,while pre-onset use of antiplatelet medications and LVEF were independent protective factors. The nomogram model constructed based on independent risk factors demonstrated good predictive ability,with an area under the ROC curve (AUC) of 0.817,a sensitivity of 81.48％,and a specificity of 67.66％. The Hosmer-Lemeshow test confirmed the model's good fit (x2=1.937,P=0.983). Conclusion The nomogram model developed in this study effectively assesses the risk of in-hospital MACE in AMI patients after PCI,providing a valuable tool for predicting patient outcomes post-PCI.
