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A novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery
BACKGROUND: Postoperative atrial fibrillation (POAF) is a severe complication after cardiac surgery and is associated with an increased risk of ischemic stroke and mortality. The main aim of this study was to identify the independent predictors associated with POAF after isolated valve operation and...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556269/ https://www.ncbi.nlm.nih.gov/pubmed/36247462 http://dx.doi.org/10.3389/fcvm.2022.949259 |
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author | Yang, Heng Yuan, Chen Yang, Juesheng Xiang, Haiyan Lan, Wanqi Tang, Yanhua |
author_facet | Yang, Heng Yuan, Chen Yang, Juesheng Xiang, Haiyan Lan, Wanqi Tang, Yanhua |
author_sort | Yang, Heng |
collection | PubMed |
description | BACKGROUND: Postoperative atrial fibrillation (POAF) is a severe complication after cardiac surgery and is associated with an increased risk of ischemic stroke and mortality. The main aim of this study was to identify the independent predictors associated with POAF after isolated valve operation and to develop a risk prediction model. METHODS: This retrospective observational study involved patients without previous AF who underwent isolated valve surgery from November 2018 to October 2021. Patients were stratified into two groups according to the development of new-onset POAF. Baseline characteristics and perioperative data were collected from the two groups of patients. Univariate and multivariate logistic regression analyses were applied to identify independent risk factors for the occurrence of POAF, and the results of the multivariate analysis were used to create a predictive nomogram. RESULTS: A total of 422 patients were included in the study, of which 163 (38.6%) developed POAF. The Multivariate logistic regression analysis indicated that cardiac function (odds ratio [OR] = 2.881, 95% confidence interval [CI] = 1.595–5.206; P < 0.001), Left atrial diameter index (OR = 1.071, 95%CI = 1.028–1.117; P = 0.001), Operative time (OR = 1.532, 95%CI = 1.095–2.141; P = 0.013), Neutrophil count (OR = 1.042, 95%CI = 1.006–1.08; P = 0.021) and the magnitude of fever (OR = 3.414, 95%CI = 2.454–4.751; P < 0.001) were independent predictors of POAF. The above Variables were incorporated, and a nomogram was successfully constructed with a C-index of 0.810. The area under the receiver operating characteristic curve was 0.817. CONCLUSION: Cardiac function, left atrial diameter index, operative time, neutrophil count, and fever were independent predictors of POAF in patients with isolated valve surgery. Establishing a nomogram model based on the above predictors helps predict the risk of POAF and may have potential clinical utility in preventive interventions. |
format | Online Article Text |
id | pubmed-9556269 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95562692022-10-14 A novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery Yang, Heng Yuan, Chen Yang, Juesheng Xiang, Haiyan Lan, Wanqi Tang, Yanhua Front Cardiovasc Med Cardiovascular Medicine BACKGROUND: Postoperative atrial fibrillation (POAF) is a severe complication after cardiac surgery and is associated with an increased risk of ischemic stroke and mortality. The main aim of this study was to identify the independent predictors associated with POAF after isolated valve operation and to develop a risk prediction model. METHODS: This retrospective observational study involved patients without previous AF who underwent isolated valve surgery from November 2018 to October 2021. Patients were stratified into two groups according to the development of new-onset POAF. Baseline characteristics and perioperative data were collected from the two groups of patients. Univariate and multivariate logistic regression analyses were applied to identify independent risk factors for the occurrence of POAF, and the results of the multivariate analysis were used to create a predictive nomogram. RESULTS: A total of 422 patients were included in the study, of which 163 (38.6%) developed POAF. The Multivariate logistic regression analysis indicated that cardiac function (odds ratio [OR] = 2.881, 95% confidence interval [CI] = 1.595–5.206; P < 0.001), Left atrial diameter index (OR = 1.071, 95%CI = 1.028–1.117; P = 0.001), Operative time (OR = 1.532, 95%CI = 1.095–2.141; P = 0.013), Neutrophil count (OR = 1.042, 95%CI = 1.006–1.08; P = 0.021) and the magnitude of fever (OR = 3.414, 95%CI = 2.454–4.751; P < 0.001) were independent predictors of POAF. The above Variables were incorporated, and a nomogram was successfully constructed with a C-index of 0.810. The area under the receiver operating characteristic curve was 0.817. CONCLUSION: Cardiac function, left atrial diameter index, operative time, neutrophil count, and fever were independent predictors of POAF in patients with isolated valve surgery. Establishing a nomogram model based on the above predictors helps predict the risk of POAF and may have potential clinical utility in preventive interventions. Frontiers Media S.A. 2022-09-29 /pmc/articles/PMC9556269/ /pubmed/36247462 http://dx.doi.org/10.3389/fcvm.2022.949259 Text en Copyright © 2022 Yang, Yuan, Yang, Xiang, Lan and Tang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cardiovascular Medicine Yang, Heng Yuan, Chen Yang, Juesheng Xiang, Haiyan Lan, Wanqi Tang, Yanhua A novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery |
title | A novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery |
title_full | A novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery |
title_fullStr | A novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery |
title_full_unstemmed | A novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery |
title_short | A novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery |
title_sort | novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556269/ https://www.ncbi.nlm.nih.gov/pubmed/36247462 http://dx.doi.org/10.3389/fcvm.2022.949259 |
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