Clinical Nomogram to Predict Major Adverse Cardiac Events in Acute Myocardial Infarction Patients within 1 Year of
Defeng Pan1, Shengjue Xiao1, Yue Hu2
1Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221004, China.
Insights
This study identified key risk factors for major adverse cardiovascular events (MACEs) in acute myocardial infarction (AMI) patients post-percutaneous coronary intervention (PCI). A predictive nomogram was developed to assess MACE risk within one year, aiding clinical decision-making.
Area of Science:
- Cardiology
- Clinical Research
- Predictive Modeling
Background:
- Major adverse cardiovascular events (MACEs) pose a significant risk to patients following acute myocardial infarction (AMI) and percutaneous coronary intervention (PCI).
- Identifying clinical characteristics and risk factors associated with MACEs is crucial for improving patient outcomes and guiding preventative strategies.
Purpose of the Study:
- To summarize the clinical characteristics and risk factors for MACEs in patients who experienced AMI within one year of PCI.
- To develop and validate a nomogram for predicting MACEs in this patient population.
Main Methods:
- A retrospective study included 421 AMI patients treated with PCI who experienced MACEs within one year, matched with 561 control patients without MACEs.
- Univariate and multivariate analyses were performed to identify risk factors. A nomogram was constructed and validated using C statistic, calibration curves, and decision curve analysis.
Main Results:
- Key predictors for MACEs included age, diabetes mellitus, low-density lipoprotein cholesterol, uric acid, lipoprotein (a), left ventricular ejection fraction, Syntax score, and hypersensitive troponin T.
- The developed nomogram demonstrated good discriminative performance (C statistic = 0.814) and calibration, with satisfactory utility.
Conclusions:
- A practical and effective nomogram was developed for predicting MACEs in AMI patients within one year of PCI.
- The model requires external validation to ensure generalizability and widespread clinical application.
Abstract:
The purpose of this study was to summarize the clinical characteristics and risk factors of major adverse cardiovascular events (MACEs) in patients who had had acute myocardial infarction (AMI) within 1 year of percutaneous coronary intervention (PCI). A total of 421 AMI patients who were treated with PCI and experienced MACEs within 1 year of their admission were included in this retrospective study. In addition, patients were matched for age, sex, and presentation with 561 patients after AMI who had not had MACEs. The clinical characteristics and risk factors for MACEs within 1 year in AMI patients were investigated, to develop a nomogram for MACEs based on univariate and multivariate analyses. The C statistic was used to assess the discriminative performance of the nomogram. In addition, calibration curve and decision curve analyses were conducted to validate the calibration performance and utility, respectively, of the nomogram. After univariate and multivariate analyses, a nomogram was constructed based on age (odds ratio (OR): 1.030; 95% confidence interval (CI): 1.014-1.047), diabetes mellitus (OR: 1.667; 95% CI: 1.151-2.415), low-density lipoprotein cholesterol (OR: 1.332; 95% CI: 1.134-1.565), uric acid (OR: 1.003; 95% CI: 1.001-1.005), lipoprotein (a) (OR: 1.003; 95% CI: 1.002-1.003), left ventricular ejection fraction (OR: 0.929; 95% CI: 0.905-0.954), Syntax score (OR: 1.075; 95% CI: 1.053-1.097), and hypersensitive troponin T (OR: 1.002; 95% CI: 1.002-1.003). The C statistic was 0.814. The calibration curve showed good concordance of the nomogram, while decision curve analysis demonstrated satisfactory positive net benefits. We developed a convenient, practical, and effective prediction model for predicting MACEs in AMI patients within 1 year of PCI. To ensure generalizability, this model requires external validation.
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