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

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 i...

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Autores principales: Fu, Yuan, Li, Kui-Bao, Yang, Xin-Chun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6595886/
https://www.ncbi.nlm.nih.gov/pubmed/30829714
http://dx.doi.org/10.1097/CM9.0000000000000175
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author Fu, Yuan
Li, Kui-Bao
Yang, Xin-Chun
author_facet Fu, Yuan
Li, Kui-Bao
Yang, Xin-Chun
author_sort Fu, Yuan
collection PubMed
description 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(2), 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.
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spelling pubmed-65958862019-07-02 A risk score model for predicting cardiac rupture after acute myocardial infarction Fu, Yuan Li, Kui-Bao Yang, Xin-Chun Chin Med J (Engl) Original Articles 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(2), 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. Wolters Kluwer Health 2019-05-05 2019-05-05 /pmc/articles/PMC6595886/ /pubmed/30829714 http://dx.doi.org/10.1097/CM9.0000000000000175 Text en Copyright © 2019 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0
spellingShingle Original Articles
Fu, Yuan
Li, Kui-Bao
Yang, Xin-Chun
A risk score model for predicting cardiac rupture after acute myocardial infarction
title 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_short 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
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6595886/
https://www.ncbi.nlm.nih.gov/pubmed/30829714
http://dx.doi.org/10.1097/CM9.0000000000000175
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