Abstract
Background: The population with myocardial infarction (MI) undergoing primary percutaneous coronary intervention (PPCI) is growing, but validated models to guide their clinical management are lacking. This study aimed to develop and validate prognostic models to predict major adverse cardiovascular events (MACEs) in patients with MI undergoing PPCI.Methods and Results: Models were developed in 4,151 patients with MI who underwent PPCI in Fuwai Hospital between January 2010 and June 2017, with a median follow-up of 698 days during which 544 MACEs occurred. The predictors included in the models were age, a history of diabetes mellitus, atrial fibrillation, chronic kidney disease, coronary artery bypass grafting, the Killip classification, ejection fraction at admission, the high-sensitivity C-reactive protein (hs-CRP) level, the estimated glomerular filtration rate, the d-dimer level, multivessel lesions, and the culprit vessel. The models had good calibration and discrimination in the derivation and internal validation with C-indexes of 0.74 and 0.60, respectively, for predicting MACEs. The new prediction model and Thrombolysis in Myocardial Infarction (TIMI) risk score model were compared using the receiver operating characteristic curve. The areas under the curve of the new prediction model and TIMI risk score model were 0.806 and 0.782, respectively (difference between areas = 0.024 < 0.05; z statistic, 1.718).Conclusion: The new prediction model could be used in clinical practice to support risk stratification as recommended in clinical guidelines.
Highlights
Cardiovascular disease (CVD) has become the leading cause of mortality worldwide [1] and a major global economic burden [2]
They can be considered as two undifferentiated populations and can be used for model establishment and validation
In the multivariate Cox regression analysis, a history of diabetes mellitus (HR, 1.347; 95% confidence interval (CI), 1.054–1.723; P = 0.0175), atrial fibrillation (HR, 1.511; 95% CI, 1.040–2.195; P = 0.0305), CABG (HR, 1.937; 95% CI, 1.363–2.752; P = 0.0002), ejection fraction (EF) grade at admission ≤45 (HR, 1.530; 95% CI, 1.089, 2.150; P = 0.0143), and multivessel lesions (HR, 1.713; 95% CI, 1.214, 2.419; P = 0.0022) were relevant factors for major adverse cardiovascular events (MACEs) during follow-up
Summary
Cardiovascular disease (CVD) has become the leading cause of mortality worldwide [1] and a major global economic burden [2]. Primary percutaneous coronary intervention (PPCI) has increased the survival rate and decreased the mortality rate, all-cause death rate, and incidence of recurrent myocardial infarction (MI) in patients with acute coronary syndrome (ACS) [3]. Clinical guidelines have provided direction for disease management; only a few tools can be used to assess the incidence of major adverse cardiovascular events (MACEs) among patients with MI undergoing PPCI and to guide patients’ clinician communication and long-term risk management [6]. The population with myocardial infarction (MI) undergoing primary percutaneous coronary intervention (PPCI) is growing, but validated models to guide their clinical management are lacking. This study aimed to develop and validate prognostic models to predict major adverse cardiovascular events (MACEs) in patients with MI undergoing PPCI
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