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Updated: Jan 30, 2026

Acute Myocardial Infarction in Rats
Published on: February 16, 2011
Risk Factors Associated With Major Cardiovascular Events 1 Year After Acute Myocardial Infarction
Yun Wang1,2,3, Jing Li4, Xin Zheng4
1Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Insights
This study identified 19 risk factors to predict 1-year cardiovascular events after acute myocardial infarction (AMI). The developed risk model helps identify high-risk patients for targeted interventions and improved outcomes.
Area of Science:
- Cardiology
- Epidemiology
- Clinical Risk Prediction
Background:
- Patients surviving acute myocardial infarction (AMI) face a substantial risk of recurrent major cardiovascular events.
- Previous research on risk factors has often concentrated on the immediate post-AMI period.
Purpose of the Study:
- To identify key risk factors for 1-year cardiovascular events following AMI.
- To develop and validate a predictive risk model for these events.
Main Methods:
- A prospective cohort study involving 4227 patients discharged alive after AMI.
- Risk factors were identified using Cox models and latent class analysis.
- The cohort was divided into training, testing, and validation samples.
Main Results:
- Nineteen risk factors were identified, including age, prior AMI, hypertension, ejection fraction, and in-hospital complications.
- The developed risk model demonstrated good predictive performance with C statistics ranging from 0.73 to 0.79 across samples.
- The model effectively stratified patients into high-, average-, and low-risk groups for 1-year events.
Conclusions:
- A validated risk model incorporating 19 factors can predict 1-year cardiovascular events post-AMI.
- This tool can assist clinicians in identifying high-risk individuals.
- The findings support intensified follow-up and aggressive risk factor management for at-risk patients.
Importance:
Patients who survive acute myocardial infarction (AMI) have a high risk of subsequent major cardiovascular events. Efforts to identify risk factors for recurrence have primarily focused on the period immediately following AMI admission.
Objectives:
To identify risk factors and develop and evaluate a risk model that predicts 1-year cardiovascular events after AMI.
Design, Setting, And Participants:
Prospective cohort study. Patients with AMI (n = 4227), aged 18 years or older, discharged alive from 53 acute-care hospitals across China from January 1, 2013, to July 17, 2014. Patients were randomly divided into samples: training (50% [2113 patients]), test (25% [1057 patients]), and validation (25% [1057 patients]). Risk factors were identified by a Cox model with Markov chain Monte Carlo simulation and further evaluated by latent class analysis. Analyses were conducted from May 1, 2017, to January 21, 2018.
Main Outcomes And Measures:
Major cardiovascular events, including recurrent AMI, stroke, heart failure, and death, within 1 year after discharge for the index AMI hospitalization.
Results:
The mean (SD) age of the cohort was 60.8 (11.8) years and 994 of 4227 patients (23.5%) were female. Common comorbidities included hypertension (2358 patients [55.8%]), coronary heart disease (1798 patients [42.5%]), and dyslipidemia (1290 patients [30.5%]). One-year event rates were 8.1% (95% CI, 6.91%-9.24%), 9.0% (95% CI, 7.22%-10.70%), and 6.4% (95% CI, 4.89%-7.85%) for the training, test, and validation samples, respectively. Nineteen risk factors comprising 15 unique variables (age, education, prior AMI, prior ventricular tachycardia or fibrillation, hypertension, angina, prearrival medical assistance, >4 hours from onset of symptoms to admission, ejection fraction, renal dysfunction, heart rate, systolic blood pressure, white blood cell count, blood glucose, and in-hospital complications) were identified. In the training, test, and validation samples, respectively, the risk model had C statistics of 0.79 (95% CI, 0.75-0.83), 0.73 (95% CI, 0.68-0.78), and 0.77 (95% CI, 0.70-0.83) and a predictive range of 1.2% to 33.9%, 1.2% to 37.9%, and 1.3% to 34.3%. The C statistic was 0.69 (95% CI, 0.65-0.74) for the latent class model in the training data. The risk model stratified 11.3%, 81.0%, and 7.7% of patients to high-, average-, and low-risk groups, with respective probabilities of 0.32, 0.06, and 0.01 for 1-year events.
Conclusions And Relevance:
Nineteen risk factors were identified, and a model was developed and evaluated to predict risk of 1-year cardiovascular events after AMI. This may aid clinicians in identifying high-risk patients who would benefit most from intensive follow-up and aggressive risk factor reduction.
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