A risk score model for predicting cardiac rupture after acute myocardial infarction.
10.1097/CM9.0000000000000175
- Author:
Yuan FU
1
;
Kui-Bao LI
;
Xin-Chun YANG
Author Information
1. Department of Cardiology, Chaoyang Hospital, Capital Medical University, Beijing 100020, China.
- Publication Type:Case Reports
- MeSH:
Aged;
Aged, 80 and over;
Case-Control Studies;
Female;
Heart Rupture;
epidemiology;
etiology;
Humans;
Logistic Models;
Male;
Myocardial Infarction;
complications;
epidemiology;
Percutaneous Coronary Intervention;
Retrospective Studies;
Risk Factors;
Ventricular Function, Left;
physiology;
Ventricular Septal Rupture;
epidemiology;
etiology
- From:
Chinese Medical Journal
2019;132(9):1037-1044
- CountryChina
- Language:English
-
Abstract:
BACKGROUND:Cardiac rupture (CR) is a major lethal complication of acute myocardial infarction (AMI). However, no valid risk score model was found to predict CR after AMI in previous researches. This study aimed to establish a simple model to assess risk of CR after AMI, which could be easily used in a clinical environment.
METHODS:This was a retrospective case-control study that included 53 consecutive patients with CR after AMI during a period from January 1, 2010 to December 31, 2017. The controls included 524 patients who were selected randomly from 7932 AMI patients without CR at a 1:10 ratio. Risk factors for CR were identified using univariate analysis and multivariate logistic regression. Risk score model was developed based on multiple regression coefficients. Performance of risk model was evaluated using receiver-operating characteristic (ROC) curves and internal validity was explored using bootstrap analysis.
RESULTS:Among all 7985 AMI patients, 53 (0.67%) had CR (free wall rupture, n = 39; ventricular septal rupture, n = 14). Hospital mortalities were 92.5% and 4.01% in patients with and without CR (P < 0.001). Independent variables associated with CR included: older age, female gender, higher heart rate at admission, body mass index (BMI) <25 kg/m, lower left ventricular ejection fraction (LVEF) and no primary percutaneous coronary intervention (pPCI) treatment. In ROC analysis, our CR risk assess model demonstrated a very good discriminate power (area under the curve [AUC] = 0.895, 95% confidence interval: 0.845-0.944, optimism-corrected AUC = 0.821, P < 0.001).
CONCLUSION:This study developed a novel risk score model to help predict CR after AMI, which had high accuracy and was very simple to use.
