A risk score model for predicting cardiac rupture after acute myocardial infarction

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 ea...

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Main Authors: Yuan Fu, Kui-Bao Li, Xin-Chun Yang, Xin Chen
Format: Article
Language:English
Published: Wolters Kluwer 2019-05-01
Series:Chinese Medical Journal
Online Access:http://journals.lww.com/10.1097/CM9.0000000000000175
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spelling doaj-c2edcb8109c04a8697cab855d5721c902020-12-02T07:47:04ZengWolters KluwerChinese Medical Journal0366-69992542-56412019-05-0113291037104410.1097/CM9.0000000000000175201905050-00005A risk score model for predicting cardiac rupture after acute myocardial infarctionYuan Fu0Kui-Bao Li1Xin-Chun Yang2Xin Chen3Department of Cardiology, Chaoyang Hospital, Capital Medical University, Beijing 100020, China.Department of Cardiology, Chaoyang Hospital, Capital Medical University, Beijing 100020, China.Department of Cardiology, Chaoyang Hospital, Capital Medical University, Beijing 100020, China.Department of Cardiology, Chaoyang Hospital, Capital Medical University, Beijing 100020, China.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/m2, 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.http://journals.lww.com/10.1097/CM9.0000000000000175
collection DOAJ
language English
format Article
sources DOAJ
author Yuan Fu
Kui-Bao Li
Xin-Chun Yang
Xin Chen
spellingShingle Yuan Fu
Kui-Bao Li
Xin-Chun Yang
Xin Chen
A risk score model for predicting cardiac rupture after acute myocardial infarction
Chinese Medical Journal
author_facet Yuan Fu
Kui-Bao Li
Xin-Chun Yang
Xin Chen
author_sort Yuan Fu
title A risk score model for predicting cardiac rupture after acute myocardial infarction
title_short A risk score model for predicting cardiac rupture after acute myocardial infarction
title_full A risk score model for predicting cardiac rupture after acute myocardial infarction
title_fullStr A risk score model for predicting cardiac rupture after acute myocardial infarction
title_full_unstemmed A risk score model for predicting cardiac rupture after acute myocardial infarction
title_sort risk score model for predicting cardiac rupture after acute myocardial infarction
publisher Wolters Kluwer
series Chinese Medical Journal
issn 0366-6999
2542-5641
publishDate 2019-05-01
description 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/m2, 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.
url http://journals.lww.com/10.1097/CM9.0000000000000175
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