Evaluation of the effect of percutaneous coronary intervention and quality of life in patients with myocardial infarction using automatic quantitative parameters of three-dimensional ultrasound and the construction of its nomogram model
10.3969/j.issn.1008-794X.2025.05.011
- VernacularTitle:三维超声自动定量参数评估心肌梗死经皮冠状动脉介入治疗效果及生存质量列线图模型构建
- Author:
Qingli CHONG
1
;
Aiqin CHENG
Author Information
1. 214200 江苏宜兴 江苏大学附属宜兴医院超声医学科
- Keywords:
automatic quantitative parameter of three-dimensional ultrasound;
myocardial infarction;
percutaneous coronary intervention;
influencing factor;
prediction model
- From:
Journal of Interventional Radiology
2025;34(5):500-506
- CountryChina
- Language:Chinese
-
Abstract:
Objective To discuss the application of automatic quantitative parameters of three-dimensional ultrasound(3-D ultrasound)in evaluating left ventricular function and quality of life in patients with myocardial infarction after receiving percutaneous coronary intervention(PCI),and to construct a nomogram prediction model based on the influencing factors.Methods A total of 300 patients with myocardial infarction,who were admitted to Yixing Hospital of Jiangsu University from January 2022 to January 2024,were enrolled in this study.The patients were randomly divided into experimental group(n=200)and validation group(n=100).According to the quality of life at three months after PCI,the patients in the experimental group were subdivided into poor-quality of life subgroup(n=52)and good-quality of life subgroup(n=148).The clinical data of the two subgroups were collected,and the clinical indicators having differences between the two groups were included in the logistic regression model to analyze the factors affecting the poor quality of life of myocardial infarction patients after PCI.According to the influencing factors,a nomogram prediction model was constructed.The receiver operating characteristic(ROC)curve was used to analyze the efficacy of the nomogram prediction model in predicting poor quality of life in patients with myocardial infarction after PCI.The external validation group was used to verify the predictive efficacy of the nomogram prediction model for poor quality of life in patients with myocardial infarction after PCI.Results No statistically significant differences in the clinical data existed between the experimental group and the validation group(P＞0.05).Comparison of the clinical data between the two subgroups showed that statistically significant differences in the age,BMI,diabetes history,left ventricular ejection fraction(LVEF),left ventricular end-systolic volume(LVESV),left ventricular end-diastolic volume(LVEDV),left ventricular global peak longitudinal strain(GLS),left ventricular global peak radial strain(GRS),and left ventricular global peak area strain(GAS)existed between the two subgroups(all P＜0.05).LVEF,LVESV,LVEDV and GLS were the influencing factors for poor quality of life in patients with myocardial infarction after PCI.ROC analysis showed that the AUC of LVEF,LVESV,LVEDV,GLS and nomogram prediction model were 0.763,0.790,0.786,0.729 and 0.921 respectively,indicating LVEF,LVESV,LVEDV and GLS had certain predictive value for poor quality of life in patients with myocardial infarction after PCI,and the nomogram prediction model had higher predictive value.When taking the cut-off value,the sensitivities of LVEF,LVESV,LVEDV,GLS,and nomogram prediction model were 0.728,0.730,0.838,0.660 and 0.951 respectively,and the specificity were 0.730,0.796,0.631,0.730 and 0.865 respectively.Internal validation of the nomogram prediction model using the Bootstrap method(B=1 000)showed that the prediction curve basically coincided with the ideal line,and the nomogram model had good predictive ability.The decision curve of this model showed that its net return rate was＞0 in the threshold probability range of 0.03-1.00.When the validation group was used to verify the nomogram prediction model,the AUC was 0.903,when the cut-off value was taken,the sensitivity was 0.838 and the specificity was 0.856.In the external validation group,the nomogram prediction model had a high predictive value for poor quality of life in patients with myocardial infarction after PCI.Conclusion LVEF,LVESV,LVEDV and GLS are the adverse factors affecting the quality of life in patients with myocardial infarction after PCI.The nomogram prediction model that is constructed based on LVEF,LVESV,LVEDV and GLS has a higher predictive ability for poor quality of life in patients with myocardial infarction after PCI,which is helpful for guiding clinical intervention and treatment.
