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Predictors of Hospital Readmission within 30 Days after Coronary Artery Bypass Grafting: Data Analysis of 2,272 Brazilian Patients
INTRODUCTION: In order to reduce readmission rates after coronary artery bypass grafting (CABG), its predictors should be known in different contexts. The objective of this study was to identify predictive factors of hospital readmission within 30 days after CABG in a Brazilian center. METHODS: A se...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Sociedade Brasileira de Cirurgia Cardiovascular
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7731841/ https://www.ncbi.nlm.nih.gov/pubmed/33306313 http://dx.doi.org/10.21470/1678-9741-2020-0266 |
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author | Chiorino, Camilla do Rosário Nicolino Santos, Vinicius Batista Lopes, Juliana de Lima Lopes, Camila Takao |
author_facet | Chiorino, Camilla do Rosário Nicolino Santos, Vinicius Batista Lopes, Juliana de Lima Lopes, Camila Takao |
author_sort | Chiorino, Camilla do Rosário Nicolino |
collection | PubMed |
description | INTRODUCTION: In order to reduce readmission rates after coronary artery bypass grafting (CABG), its predictors should be known in different contexts. The objective of this study was to identify predictive factors of hospital readmission within 30 days after CABG in a Brazilian center. METHODS: A secondary analysis of an electronic database of patients submitted to isolated CABG was performed. The relationship between readmission within 30 days and demographic, anthropometric, clinical, and surgery-related characteristics was investigated by univariate analyses. Predictors were identified by multiple logistic regression. RESULTS: Data from 2,272 patients were included, with an incidence of readmission of 8.6%. The predictors of readmission were brown skin color (Beta=1.613; 95% confidence interval [CI] 1.047-2.458; P=0.030), African-American ethnicity (Beta=0.136; 95% CI 0.019-0.988; P=0.049), chronic kidney disease (Beta=2.214; 95% CI 1.269-3.865; P=0.005), postoperative use of blood products (Beta=1.515; 95% CI 1.101-2.086; P=0.011), chronic obstructive pulmonary disease (Beta=2.095; 95% CI 1.284-3.419; P=0.003), and use of acetylsalicylic acid (Beta=1.418; 95% CI 1.000-2.011; P=0.05). Preoperative antibiotic prophylaxis (Beta=0.742; 95% CI 0.5471.007; P=0.055) was marginally significant. CONCLUSION: The predictors identified may support a closer postoperative follow-up and individualized planning for a safe discharge. |
format | Online Article Text |
id | pubmed-7731841 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Sociedade Brasileira de Cirurgia Cardiovascular |
record_format | MEDLINE/PubMed |
spelling | pubmed-77318412020-12-16 Predictors of Hospital Readmission within 30 Days after Coronary Artery Bypass Grafting: Data Analysis of 2,272 Brazilian Patients Chiorino, Camilla do Rosário Nicolino Santos, Vinicius Batista Lopes, Juliana de Lima Lopes, Camila Takao Braz J Cardiovasc Surg Original Article INTRODUCTION: In order to reduce readmission rates after coronary artery bypass grafting (CABG), its predictors should be known in different contexts. The objective of this study was to identify predictive factors of hospital readmission within 30 days after CABG in a Brazilian center. METHODS: A secondary analysis of an electronic database of patients submitted to isolated CABG was performed. The relationship between readmission within 30 days and demographic, anthropometric, clinical, and surgery-related characteristics was investigated by univariate analyses. Predictors were identified by multiple logistic regression. RESULTS: Data from 2,272 patients were included, with an incidence of readmission of 8.6%. The predictors of readmission were brown skin color (Beta=1.613; 95% confidence interval [CI] 1.047-2.458; P=0.030), African-American ethnicity (Beta=0.136; 95% CI 0.019-0.988; P=0.049), chronic kidney disease (Beta=2.214; 95% CI 1.269-3.865; P=0.005), postoperative use of blood products (Beta=1.515; 95% CI 1.101-2.086; P=0.011), chronic obstructive pulmonary disease (Beta=2.095; 95% CI 1.284-3.419; P=0.003), and use of acetylsalicylic acid (Beta=1.418; 95% CI 1.000-2.011; P=0.05). Preoperative antibiotic prophylaxis (Beta=0.742; 95% CI 0.5471.007; P=0.055) was marginally significant. CONCLUSION: The predictors identified may support a closer postoperative follow-up and individualized planning for a safe discharge. Sociedade Brasileira de Cirurgia Cardiovascular 2020 /pmc/articles/PMC7731841/ /pubmed/33306313 http://dx.doi.org/10.21470/1678-9741-2020-0266 Text en http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Chiorino, Camilla do Rosário Nicolino Santos, Vinicius Batista Lopes, Juliana de Lima Lopes, Camila Takao Predictors of Hospital Readmission within 30 Days after Coronary Artery Bypass Grafting: Data Analysis of 2,272 Brazilian Patients |
title | Predictors of Hospital Readmission within 30 Days after Coronary Artery Bypass Grafting: Data Analysis of 2,272 Brazilian Patients |
title_full | Predictors of Hospital Readmission within 30 Days after Coronary Artery Bypass Grafting: Data Analysis of 2,272 Brazilian Patients |
title_fullStr | Predictors of Hospital Readmission within 30 Days after Coronary Artery Bypass Grafting: Data Analysis of 2,272 Brazilian Patients |
title_full_unstemmed | Predictors of Hospital Readmission within 30 Days after Coronary Artery Bypass Grafting: Data Analysis of 2,272 Brazilian Patients |
title_short | Predictors of Hospital Readmission within 30 Days after Coronary Artery Bypass Grafting: Data Analysis of 2,272 Brazilian Patients |
title_sort | predictors of hospital readmission within 30 days after coronary artery bypass grafting: data analysis of 2,272 brazilian patients |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7731841/ https://www.ncbi.nlm.nih.gov/pubmed/33306313 http://dx.doi.org/10.21470/1678-9741-2020-0266 |
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