ArticleBrazilian journal of cardiovascular surgery2020
Predictors of Hospital Readmission within 30 Days after Coronary Artery Bypass Grafting: Data Analysis of 2,272 Brazilian Patients.
Article in Brazilian journal of cardiovascular surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Hospital discharge readiness based on Meleis's transition theory and its associated factors among patients after coronary artery bypass grafting: a cross-sectional study.Frontiers in medicine · 2026Article
- Machine learning methods for perioperative anesthetic management in cardiac surgery patients: a scoping review.Journal of thoracic disease · 2021Article
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4 authors.
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Abstract
introductionIn 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.
methodsA 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.
resultsData 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.
conclusionThe predictors identified may support a closer postoperative follow-up and individualized planning for a safe discharge.
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