Risk Factors Associated With Major Cardiovascular Events 1 Year After Acute Myocardial Infarction

Abstract

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.

Figure 1.. Distribution of Patient Risk Scores and Probability of 1-Year Major Cardiovascular Events by Risk Score

The histograms show the distribution of risk scores for training (A), test (B), and validation (C) samples, and the curves show the probability of major cardiovascular events at 1 year. The black curve represents a fitted density curve on the risk score histogram. A risk score, ranging from 0 to 100, was constructed at the patient level based on the regression coefficients estimated from the final risk model with the training sample. A higher risk score indicates a higher probability of major cardiovascular events 1 year after discharge.

Figure 2.. Risk Stratification by Risk Scores

For the training, test, and validation samples, respectively, the highest risk group includes 11.3%, 12.1%, and 11.7% of the patients; the average risk group includes 81.0%, 81.8%, and 81.1% of the patients; and the lowest risk group includes 7.7%, 6.1%, and 7.2% of the patients.

Figure 3.. Observed Probability of Being Free From 1-Year Major Cardiovascular Events by Risk Groups