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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2019
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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. |
format | Online Article Text |
id | pubmed-6595886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
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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