Acessibilidade / Reportar erro

Age, Renal Failure and Transfusion are Risk Predictors of Prolonged Hospital Stay after Coronary Artery Bypass Grafting Surgery

Abstract

Background:

Identifying risk factors in cardiovascular surgery assists in predictability, resulting in optimization of outcomes and cost reduction.

Objective:

This study aimed to identify preoperative and intraoperative risk predictors for prolonged hospitalization after coronary artery bypass grafting (CABG) surgery in the state of São Paulo, Brazil.

Methods:

A cross-sectional analysis using data from the REPLICCAR II database, a prospective, consecutive, multicenter registry that included CABG surgeries performed between August 2017 and July 2019. The primary outcome was a prolonged hospital stay (PHS), defined as a postoperative period exceeding 14 days. Univariate and multivariate logistic regression analyses were performed to identify the predictors with significance set at p <0.05.

Results:

The median age was 63 (57-70) years and 26.55% of patients were female. Among the 3703 patients analyzed, 228 (6.16%) had a PHS after CABG, with a median hospital stay of 17 (16-20) days. Predictors of PHS after CABG included age >60 years (OR 2.05; 95% CI 1.43-2.87; p<0.001); renal failure (OR 1.73; 95% CI 1.29-2.32; p <0.001) and intraoperative red blood cell transfusion (OR 1.32; 95% CI 1.07-2.06; p=0.01).

Conclusion:

Age >60 years, renal failure, and intraoperative red blood cell transfusion were independent predictors of PHS after CABG. The identification of these variables can help in multiprofessional strategic planning aimed to enhance results and resource utilization in the state of São Paulo.

Keywords:
Length of Stay; Myocardial Revascularization; Process Optimization

Resumo

Fundamento:

A identificação de fatores de riscos na cirurgia cardiovascular auxilia na previsibilidade resultando na otimização de desfechos e redução de custos.

Objetivo:

Identificação dos preditores de risco pré e intraoperatórios para internação prolongada após cirurgia de revascularização do miocárdio (CRM) no Estado de São Paulo.

Métodos:

Análise transversal no banco de dados REPLICCAR II, registro prospectivo, consecutivo, multicêntrico que incluiu cirurgias de revascularização miocárdica realizadas entre agosto de 2017 e julho de 2019. O desfecho principal foi o tempo de internação prolongado, definida como período de pós-operatório superior a 14 (quatorze) dias. Para a identificação dos preditores foram realizadas análises de regressão logística uni- e multivariada. Os valores de p menores de 0,05 foram considerados significativos.

Resultados:

A mediana de idade foi de 63 (57-70) anos e 26,55% eram do sexo feminino. Dos 3703 pacientes analisados, 228 (6,16%) apresentaram longa permanência hospitalar (LPH) após a CRM e a mediana da internação foi de 17 (16-20) dias. Foram preditores da LPH após a CRM: idade >60 anos (OR 2,05; IC95% 1,43 - 2,87; p<0,001); insuficiência renal (OR 1,73; IC95% 1,29 - 2,32; p<0,001) e transfusão de hemácias no intraoperatório (OR 1,32; IC 1,07 - 2,06; p=0,01).

Conclusão:

Nesta análise, a idade > 60 anos, insuficiência renal e a transfusão de hemácias no intraoperatório foram preditores independentes de LPH após a CRM. A identificação destas variáveis pode ajudar no planejamento estratégico multiprofissional visando melhoria de resultados e otimização de recursos no estado de São Paulo.

Palavras-chave:
Tempo de Internação; Revascularização Miocárdica; Otimização de Processos

Introduction

The length of postoperative hospital stay is a robust measure of healthcare quality,11 LaPar DJ, Crosby IK, Rich JB, Fonner E Jr, Kron IL, Ailawadi G, et al. A Contemporary Cost Analysis of Postoperative Morbidity after Coronary Artery Bypass Grafting with and Without Concomitant Aortic Valve Replacement to Improve Patient Quality and Cost-effective Care. Ann Thorac Surg. 2013;96(5):1621-7. doi: 10.1016/j.athoracsur.2013.05.050.
https://doi.org/10.1016/j.athoracsur.201...

2 Torabipour A, Arab M, Zeraati H, Rashidian A, Sari AA, Sarzaiem MR. Multivariate Analysis of Factors Influencing Length of Hospital Stay after Coronary Artery Bypass Surgery in Tehran, Iran. Acta Med Iran. 2016;54(2):124-33.
-33 Kato N, Kondo M, Okubo I, Hasegawa T. Length of Hospital Stay in Japan 1971-2008: Hospital Ownership and Cost-containment Policies. Health Policy. 2014;115(2-3):180-8. doi: 10.1016/j.healthpol.2014.01.002.
https://doi.org/10.1016/j.healthpol.2014...
guiding resource management in both public and private health management sectors.33 Kato N, Kondo M, Okubo I, Hasegawa T. Length of Hospital Stay in Japan 1971-2008: Hospital Ownership and Cost-containment Policies. Health Policy. 2014;115(2-3):180-8. doi: 10.1016/j.healthpol.2014.01.002.
https://doi.org/10.1016/j.healthpol.2014...
,44 Brasil. Ministério da Saúde. Portaria GM/MS nº 1.100, de 12 de maio de 2022. Define o 1º Ciclo do Programa de Qualificação da Assistência Cardiovascular, QualiSUS Cardio, no âmbito do Sistema Único de Saúde – SUS. Brasília: Ministério da Saúde; 2022. Brazil, for instance, has adopted a public payment model since 2022 that incorporates quality and performance metrics, considering the length of postoperative hospital stay as one of the variables used.44 Brasil. Ministério da Saúde. Portaria GM/MS nº 1.100, de 12 de maio de 2022. Define o 1º Ciclo do Programa de Qualificação da Assistência Cardiovascular, QualiSUS Cardio, no âmbito do Sistema Único de Saúde – SUS. Brasília: Ministério da Saúde; 2022. With consolidated evidence on the reduction of cardiovascular outcomes in the long term,55 Neumann FJ, Sousa-Uva M, Ahlsson A, Alfonso F, Banning AP, Benedetto U, et al. 2018 ESC/EACTS Guidelines on Myocardial Revascularization. Eur Heart J. 2019;40(2):87-165. doi: 10.1093/eurheartj/ehy394.
https://doi.org/10.1093/eurheartj/ehy394...
coronary artery bypass grafting (CABG) surgery can contribute to prolonged hospital stay (PHS), bringing risks to patients, impacting quality of life, increasing healthcare costs,11 LaPar DJ, Crosby IK, Rich JB, Fonner E Jr, Kron IL, Ailawadi G, et al. A Contemporary Cost Analysis of Postoperative Morbidity after Coronary Artery Bypass Grafting with and Without Concomitant Aortic Valve Replacement to Improve Patient Quality and Cost-effective Care. Ann Thorac Surg. 2013;96(5):1621-7. doi: 10.1016/j.athoracsur.2013.05.050.
https://doi.org/10.1016/j.athoracsur.201...
and adversely affecting hospital service quality indicators.66 Kaboli PJ, Go JT, Hockenberry J, Glasgow JM, Johnson SR, Rosenthal GE, et al. Associations Between Reduced Hospital Length of Stay and 30-day Readmission Rate and Mortality: 14-year Experience in 129 Veterans Affairs Hospitals. Ann Intern Med. 2012;157(12):837-45. doi: 10.7326/0003-4819-157-12-201212180-00003.
https://doi.org/10.7326/0003-4819-157-12...

In a multicenter cohort study conducted in the United States,77 Osnabrugge RL, Speir AM, Head SJ, Jones PG, Ailawadi G, Fonner CE, et al. Prediction of Costs and Length of Stay in Coronary Artery Bypass Grafting. Ann Thorac Surg. 2014;98(4):1286-93. doi: 10.1016/j.athoracsur.2014.05.073..
https://doi.org/10.1016/j.athoracsur.201...
the correlation between hospital length of stay and costs to the healthcare system was analyzed, based on data from 42,839 patients who underwent CABG. The findings revealed that an average hospitalization of 5.4 days incurred a cost of US$33,275.00, whereas an average stay of 13.8 days amounted to US$69,122.00 for healthcare payers. In Brazil, according to data from DATASUS,88 Brasil. Ministério da Saúde. Banco de dados do Sistema Único de Saúde-DATASUS [Internet]. Brasília: Ministério da Saúde; 2023 [cited 2023 Jan 08]. Available from: http://www.datasus.gov.br.
http://www.datasus.gov.br...
between January and November 2022, a total of 17,931 isolated CABG surgeries were carried out by the Brazilian Unified Health System, costing R$180,123,355.01. Moreover, during this period,88 Brasil. Ministério da Saúde. Banco de dados do Sistema Único de Saúde-DATASUS [Internet]. Brasília: Ministério da Saúde; 2023 [cited 2023 Jan 08]. Available from: http://www.datasus.gov.br.
http://www.datasus.gov.br...
the average hospital stay for a CABG using cardiopulmonary bypass with two or more grafts was 12.1 days. Various research endeavors aiming to reduce hospital stays, associated costs, and complications following CABG are underway, focusing on the implementation of rapid recovery protocols.99 Li M, Zhang J, Gan TJ, Qin G, Wang L, Zhu M, et al. Enhanced Recovery after Surgery Pathway for Patients Undergoing Cardiac Surgery: A Randomized Clinical Trial. Eur J Cardiothorac Surg. 2018;54(3):491-7. doi: 10.1093/ejcts/ezy100.
https://doi.org/10.1093/ejcts/ezy100...

The existing literature on factors leading to PHS following CABG varies in methodologies, with some studies utilizing limited sample sizes and different patient allocation criteria,22 Torabipour A, Arab M, Zeraati H, Rashidian A, Sari AA, Sarzaiem MR. Multivariate Analysis of Factors Influencing Length of Hospital Stay after Coronary Artery Bypass Surgery in Tehran, Iran. Acta Med Iran. 2016;54(2):124-33.,1010 Lee J, Govindan S, Celi LA, Khabbaz KR, Subramaniam B. Customized Prediction of Short Length of Stay Following Elective Cardiac Surgery in Elderly Patients Using a Genetic Algorithm. World J Cardiovasc Surg. 2013;3(5):163-70. doi: 10.4236/wjcs.2013.35034.
https://doi.org/10.4236/wjcs.2013.35034...

11 Shahian DM, O’Brien SM, Filardo G, Ferraris VA, Haan CK, Rich JB, et al. The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 1--coronary Artery Bypass Grafting Surgery. Ann Thorac Surg. 2009;88(1Suppl):2-22. doi: 10.1016/j.athoracsur.2009.05.053.
https://doi.org/10.1016/j.athoracsur.200...

12 Triana AJ, Vyas R, Shah AS, Tiwari V. Predicting Length of Stay of Coronary Artery Bypass Grafting Patients Using Machine Learning. J Surg Res. 2021;264:68-75. doi: 10.1016/j.jss.2021.02.003.
https://doi.org/10.1016/j.jss.2021.02.00...
-1313 Oliveira EK, Turquetto AL, Tauil PL, Junqueira LF Jr, Porto LG. Risk Factors for Prolonged Hospital Stay after Isolated Coronary Artery Bypass Grafting. Rev Bras Cir Cardiovasc. 2013;28(3):353-63. doi: 10.5935/1678-9741.20130055.
https://doi.org/10.5935/1678-9741.201300...
and results with different impact factors for PHS after CABG. Socioeconomic characteristics, alongside clinical and hospital-related characteristics, have been shown to influence postoperative hospitalization duration,22 Torabipour A, Arab M, Zeraati H, Rashidian A, Sari AA, Sarzaiem MR. Multivariate Analysis of Factors Influencing Length of Hospital Stay after Coronary Artery Bypass Surgery in Tehran, Iran. Acta Med Iran. 2016;54(2):124-33.,1111 Shahian DM, O’Brien SM, Filardo G, Ferraris VA, Haan CK, Rich JB, et al. The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 1--coronary Artery Bypass Grafting Surgery. Ann Thorac Surg. 2009;88(1Suppl):2-22. doi: 10.1016/j.athoracsur.2009.05.053.
https://doi.org/10.1016/j.athoracsur.200...
requiring specific studies for different populations. However, studies focusing on the Brazilian population remain insufficient in providing predictive insights, either by a limited sample1313 Oliveira EK, Turquetto AL, Tauil PL, Junqueira LF Jr, Porto LG. Risk Factors for Prolonged Hospital Stay after Isolated Coronary Artery Bypass Grafting. Rev Bras Cir Cardiovasc. 2013;28(3):353-63. doi: 10.5935/1678-9741.20130055.
https://doi.org/10.5935/1678-9741.201300...
or methodologies focused on a narrow set of variables.1414 Volkmann MA, Behr PE, Burmeister JE, Consoni PR, Kalil RA, Prates PR, et al. Hidden Renal Dysfunction Causes Increased In-hospital Mortality Risk after Coronary Artery Bypass Graft Surgery. Rev Bras Cir Cardiovasc. 2011;26(3):319-25. doi: 10.5935/1678-9741.20110005.
https://doi.org/10.5935/1678-9741.201100...
Hence, there is a need for more robust data related to this theme.

In this context, it becomes imperative to identify and understand the factors that lead to prolonged hospitalization after CABG, aiming to increase predictability, improve outcomes, and reduce costs to healthcare system.33 Kato N, Kondo M, Okubo I, Hasegawa T. Length of Hospital Stay in Japan 1971-2008: Hospital Ownership and Cost-containment Policies. Health Policy. 2014;115(2-3):180-8. doi: 10.1016/j.healthpol.2014.01.002.
https://doi.org/10.1016/j.healthpol.2014...
This study aimed to identify risk predictors of PHS after CABG surgery.

Methods

This study comprises a cross-sectional analysis of the REPLICCAR II database,1515 Orlandi BMM, Mejia OAV, Borgomoni GB, Goncharov M, Rocha KN, Bassolli L, et al. REPLICCAR II Study: Data Quality Audit in the Paulista Cardiovascular Surgery Registry. PLoS One. 2020;15(7):e0223343. doi: 10.1371/journal.pone.0223343.
https://doi.org/10.1371/journal.pone.022...
a prospective, observational, and multicenter registry encompassing CABG surgeries performed at five hospitals in the state of São Paulo between August 2017 and July 2019.

The REPLICCAR II database1515 Orlandi BMM, Mejia OAV, Borgomoni GB, Goncharov M, Rocha KN, Bassolli L, et al. REPLICCAR II Study: Data Quality Audit in the Paulista Cardiovascular Surgery Registry. PLoS One. 2020;15(7):e0223343. doi: 10.1371/journal.pone.0223343.
https://doi.org/10.1371/journal.pone.022...
comprises patients aged ≥ 18 years who underwent elective and urgent CABG surgery. Data collection utilized the REDCap platform (http://www.project-redcap.org), especially for the project, and was collected online by qualified and trained professionals. The database contains the same variables and definitions as version 2.9 of the Society of Thoracic Surgeons (STS) data collection system.1111 Shahian DM, O’Brien SM, Filardo G, Ferraris VA, Haan CK, Rich JB, et al. The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 1--coronary Artery Bypass Grafting Surgery. Ann Thorac Surg. 2009;88(1Suppl):2-22. doi: 10.1016/j.athoracsur.2009.05.053.
https://doi.org/10.1016/j.athoracsur.200...

Data quality

The REPLICCAR II1515 Orlandi BMM, Mejia OAV, Borgomoni GB, Goncharov M, Rocha KN, Bassolli L, et al. REPLICCAR II Study: Data Quality Audit in the Paulista Cardiovascular Surgery Registry. PLoS One. 2020;15(7):e0223343. doi: 10.1371/journal.pone.0223343.
https://doi.org/10.1371/journal.pone.022...
database includes a total of 4049 patients, however, 346 were excluded from this analysis due to the missing data regarding hospital stay.

Variable definitions

Long hospital stay after CABG was defined as hospitalization exceeding 14 days post-surgery, following the definition used by the STS database.1111 Shahian DM, O’Brien SM, Filardo G, Ferraris VA, Haan CK, Rich JB, et al. The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 1--coronary Artery Bypass Grafting Surgery. Ann Thorac Surg. 2009;88(1Suppl):2-22. doi: 10.1016/j.athoracsur.2009.05.053.
https://doi.org/10.1016/j.athoracsur.200...
Intraoperative transfusion was characterized by the infusion of packed red blood cells during the surgical procedure. Creatinine clearance was calculated using the Crockoft-Gault equation.1616 Cockcroft DW, Gault MH. Prediction of Creatinine Clearance from Serum Creatinine. Nephron. 1976;16(1):31-41. doi: 10.1159/000180580.
https://doi.org/10.1159/000180580...
Emergency surgeries were excluded from this analysis to mitigate potential bias in identifying manageable predictors, as factors related to patient severity could confound the results.

Statistical analysis

All analyses in this study were conducted using R software version 4.0.2.

In the descriptive analysis, continuous variables presented asymmetry and, therefore, were described through median and interquartile ranges. Categorical variables were expressed as frequencies and percentages.

Categorical independent variables were analyzed by comparing proportions using either the chi-square or Fisher's exact tests, as appropriate. Normality and sample homogeneity tests were performed using the Shapiro-Wilk and Levene tests, respectively. Continuous variables were analyzed using the Mann-Whitney test due to data distribution.

Prediction variables, both preoperative and intraoperative, were analyzed using univariate logistic regression. Variables with a p-value <0.05 were consecutively submitted to a multivariate logistic regression model to assess their independent impact on postoperative length of stay.

Odds ratios and their corresponding 95% confidence intervals were expressed. A significance level of p <0.05 was utilized.

Ethics and informed consent

This analysis utilized data from the REPLICCAR II1515 Orlandi BMM, Mejia OAV, Borgomoni GB, Goncharov M, Rocha KN, Bassolli L, et al. REPLICCAR II Study: Data Quality Audit in the Paulista Cardiovascular Surgery Registry. PLoS One. 2020;15(7):e0223343. doi: 10.1371/journal.pone.0223343.
https://doi.org/10.1371/journal.pone.022...
registry, which received approval from the Ethics Committee under opinion number 5.603.742, CAAE registration number: 66919417.6.1001.0068 and SDC 4506/17/006 approved on 04/10/2017. Informed consent for data collection was waived due to the research design employed in the initial project.

Results

A total of 3703 patients who underwent CABG were evaluated. Among them, 228 (6.16%) had prolonged postoperative hospitalization, with a median duration of 17 (16-20) days.

Table 1 shows the characteristics of the two evaluated groups. The group experiencing PHS after CABG demonstrated a higher median age. Additionally, there was a higher prevalence of females in this group, and a higher proportion of patients with a body mass index ≥30, as well as emergency admissions.

Table 1
Characteristics of patients with prolonged hospital stay after CABG, REPLICCAR II, São Paulo, 2022

The PHS group exhibited a higher incidence of previous cerebrovascular disease compared to the group with a postoperative hospital stay of up to 14 days. Among patients with PHS, a significantly higher proportion had a cardiac ejection fraction <30%, while this incidence was lower in the group with postoperative hospitalization of up to 14 days. Regarding patients with renal failure, the prevalence of creatinine clearance <60 ml/min/1.73 m2 was significantly higher in the PHS group. In addition, among patients in the PHS group, there was a higher incidence of those classified with angina class IV according to the Canadian Cardiovascular Society (CCS)1818 Smith ER. The Angina Grading System of the Canadian Cardiovascular Society. Can J Cardiol. 2002;18(4):439, 442. and a more significant presence of patients in functional classes III and IV according to New York Heart Association (NYHA),1919 Fisher JD. New York Heart Association Classification. Arch Intern Med. 1972;129(5):836. compared to the group with postoperative hospitalization of up to 14 days.

In the group experiencing PHS following CABG, there was a higher incidence of patients with preoperative anemia compared to those with postoperative hospitalization of up to 14 days. Patients requiring intraoperative red blood cell transfusion were more prevalent in the PHS group. The risk of PHS estimated by STS was higher in patients with prolonged hospitalization compared to the group with postoperative hospitalization of up to 14 days. Similarly, the mortality risk estimated by STS was higher in patients who had PHS after CABG. Previous myocardial infarction, systemic arterial hypertension, diabetes mellitus, atrial fibrillation, and the use of cardiopulmonary bypass did not show statistically significant differences between these two groups. Following univariate logistic regression (Table 2), ten variables were associated with PHS after CABG and were subsequently included in multivariate logistic regression analysis.

Table 2
Univariate logistic regression with predictors of prolonged hospital stay after CABG. REPLICCAR II, São Paulo, 2022

Among the variables included in the multivariate logistic regression (Table 3), three variables demonstrated an association with prolonged postoperative hospitalization: age, renal failure, and intraoperative red blood cell transfusion (central figure).

Table 3
Univariate logistic regression with predictors of prolonged hospital stay after CABG. REPLICCAR II, São Paulo, 2022

Urgent CABG, as well as gender, history of cerebrovascular disease, preoperative anemia, ejection fraction < 30%, presence of angina CCS class IV, as well as NYHA functional class III and IV, did not show statistical significance in the length of postoperative stay.

Discussion

In the sample of this study, 6.15% (n=228) of patients experienced prolonged hospitalization, a finding compatible with previous studies,22 Torabipour A, Arab M, Zeraati H, Rashidian A, Sari AA, Sarzaiem MR. Multivariate Analysis of Factors Influencing Length of Hospital Stay after Coronary Artery Bypass Surgery in Tehran, Iran. Acta Med Iran. 2016;54(2):124-33.,1010 Lee J, Govindan S, Celi LA, Khabbaz KR, Subramaniam B. Customized Prediction of Short Length of Stay Following Elective Cardiac Surgery in Elderly Patients Using a Genetic Algorithm. World J Cardiovasc Surg. 2013;3(5):163-70. doi: 10.4236/wjcs.2013.35034.
https://doi.org/10.4236/wjcs.2013.35034...
albeit slightly higher than averages found in studies investigating rapid recovery after cardiac surgery.99 Li M, Zhang J, Gan TJ, Qin G, Wang L, Zhu M, et al. Enhanced Recovery after Surgery Pathway for Patients Undergoing Cardiac Surgery: A Randomized Clinical Trial. Eur J Cardiothorac Surg. 2018;54(3):491-7. doi: 10.1093/ejcts/ezy100.
https://doi.org/10.1093/ejcts/ezy100...
The predictors of PHS after CABG found in this analysis (age >60 years, renal failure, and intraoperative red blood cell transfusion) differ from the literature related to the Brazilian population, with a similar objective,1313 Oliveira EK, Turquetto AL, Tauil PL, Junqueira LF Jr, Porto LG. Risk Factors for Prolonged Hospital Stay after Isolated Coronary Artery Bypass Grafting. Rev Bras Cir Cardiovasc. 2013;28(3):353-63. doi: 10.5935/1678-9741.20130055.
https://doi.org/10.5935/1678-9741.201300...
but are in line with data from the world literature elaborated with diverse statistical analyzes.1212 Triana AJ, Vyas R, Shah AS, Tiwari V. Predicting Length of Stay of Coronary Artery Bypass Grafting Patients Using Machine Learning. J Surg Res. 2021;264:68-75. doi: 10.1016/j.jss.2021.02.003.
https://doi.org/10.1016/j.jss.2021.02.00...
A North American study with 2121 patients who underwent CABG1212 Triana AJ, Vyas R, Shah AS, Tiwari V. Predicting Length of Stay of Coronary Artery Bypass Grafting Patients Using Machine Learning. J Surg Res. 2021;264:68-75. doi: 10.1016/j.jss.2021.02.003.
https://doi.org/10.1016/j.jss.2021.02.00...
in a single center, which analyzed 116 variables with two different artificial intelligence techniques for data analysis, identified four main impact factors for PHS after CABG: intubation time, preoperative creatinine value, age, and number of intraoperative transfusions.

The observed impact of age >60 years on the increase in length of hospital stay, as evidenced in this study, is in line with data from previous studies.22 Torabipour A, Arab M, Zeraati H, Rashidian A, Sari AA, Sarzaiem MR. Multivariate Analysis of Factors Influencing Length of Hospital Stay after Coronary Artery Bypass Surgery in Tehran, Iran. Acta Med Iran. 2016;54(2):124-33.,1010 Lee J, Govindan S, Celi LA, Khabbaz KR, Subramaniam B. Customized Prediction of Short Length of Stay Following Elective Cardiac Surgery in Elderly Patients Using a Genetic Algorithm. World J Cardiovasc Surg. 2013;3(5):163-70. doi: 10.4236/wjcs.2013.35034.
https://doi.org/10.4236/wjcs.2013.35034...
In a study with 649 patients undergoing CABG,22 Torabipour A, Arab M, Zeraati H, Rashidian A, Sari AA, Sarzaiem MR. Multivariate Analysis of Factors Influencing Length of Hospital Stay after Coronary Artery Bypass Surgery in Tehran, Iran. Acta Med Iran. 2016;54(2):124-33. both univariate parametric tests and a multiple linear regression model were used to identify predictors of PHS after CABG, with age as an independent variable. Another study with 1426 patients1010 Lee J, Govindan S, Celi LA, Khabbaz KR, Subramaniam B. Customized Prediction of Short Length of Stay Following Elective Cardiac Surgery in Elderly Patients Using a Genetic Algorithm. World J Cardiovasc Surg. 2013;3(5):163-70. doi: 10.4236/wjcs.2013.35034.
https://doi.org/10.4236/wjcs.2013.35034...
from the STS1111 Shahian DM, O’Brien SM, Filardo G, Ferraris VA, Haan CK, Rich JB, et al. The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 1--coronary Artery Bypass Grafting Surgery. Ann Thorac Surg. 2009;88(1Suppl):2-22. doi: 10.1016/j.athoracsur.2009.05.053.
https://doi.org/10.1016/j.athoracsur.200...
database used an artificial intelligence-based model, known as a genetic algorithm, which identified 23 pre- and intraoperative factors related to increased hospital stay after CABG, with age being one of the three main factors found. Both the STS1111 Shahian DM, O’Brien SM, Filardo G, Ferraris VA, Haan CK, Rich JB, et al. The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 1--coronary Artery Bypass Grafting Surgery. Ann Thorac Surg. 2009;88(1Suppl):2-22. doi: 10.1016/j.athoracsur.2009.05.053.
https://doi.org/10.1016/j.athoracsur.200...
and EuroSCORE II2020 Nashef SA, Roques F, Sharples LD, Nilsson J, Smith C, Goldstone AR, et al. EuroSCORE II. Eur J Cardiothorac Surg. 2012;41(4):734-44. doi: 10.1093/ejcts/ezs043.
https://doi.org/10.1093/ejcts/ezs043...
surgical risk prediction models emphasize age as an isolated risk factor for increased morbidity and mortality after cardiac surgery. Age-related physiological variations and increased comorbidities in elderly populations are suggested factors for increased postoperative complications and PHS after CABG.2121 Mortasawi A, Arnrich B, Walter J, Frerichs I, Rosendahl U, Ennker J. Impact of Age on the Results of Coronary Artery Bypass Grafting. Asian Cardiovasc Thorac Ann. 2004;12(4):324-9. doi: 10.1177/021849230401200410.
https://doi.org/10.1177/0218492304012004...

Preoperative renal dysfunction is recognized as a significant factor contributing to adverse short- and long-term outcomes after CABG.2222 Lv M, Hu B, Ge W, Li Z, Wang Q, Han C, et al. Impact of Preoperative Occult Renal Dysfunction on Early and Late Outcomes after Off-Pump Coronary Artery Bypass. Heart Lung Circ. 2021;30(2):288-95. doi: 10.1016/j.hlc.2020.05.105.
https://doi.org/10.1016/j.hlc.2020.05.10...
,2323 Cooper WA, O‘Brien SM, Thourani VH, Guyton RA, Bridges CR, Szczech LA, et al. Impact of Renal Dysfunction on Outcomes of Coronary Artery Bypass Surgery: Results from the Society of Thoracic Surgeons National Adult Cardiac Database. Circulation. 2006;113(8):1063-70. doi: 10.1161/CIRCULATIONAHA.105.580084.
https://doi.org/10.1161/CIRCULATIONAHA.1...
Despite the widespread use of creatinine as a biomarker of renal function, normal serum levels ≤1.3 mg/dL2323 Cooper WA, O‘Brien SM, Thourani VH, Guyton RA, Bridges CR, Szczech LA, et al. Impact of Renal Dysfunction on Outcomes of Coronary Artery Bypass Surgery: Results from the Society of Thoracic Surgeons National Adult Cardiac Database. Circulation. 2006;113(8):1063-70. doi: 10.1161/CIRCULATIONAHA.105.580084.
https://doi.org/10.1161/CIRCULATIONAHA.1...
may mask underlying renal dysfunction, characterized by creatinine clearance <60 ml/min/1.73 m2, known as hidden renal dysfunction.2222 Lv M, Hu B, Ge W, Li Z, Wang Q, Han C, et al. Impact of Preoperative Occult Renal Dysfunction on Early and Late Outcomes after Off-Pump Coronary Artery Bypass. Heart Lung Circ. 2021;30(2):288-95. doi: 10.1016/j.hlc.2020.05.105.
https://doi.org/10.1016/j.hlc.2020.05.10...
,2424 Miceli A, Bruno VD, Capoun R, Romeo F, Angelini GD, Caputo M. Occult Renal Dysfunction: A Mortality and Morbidity Risk Factor in Coronary Artery Bypass Grafting Surgery. J Thorac Cardiovasc Surg. 2011;141(3):771-6. doi: 10.1016/j.jtcvs.2010.08.016.
https://doi.org/10.1016/j.jtcvs.2010.08....
This hidden dysfunction serves as an independent risk factor for mortality,2323 Cooper WA, O‘Brien SM, Thourani VH, Guyton RA, Bridges CR, Szczech LA, et al. Impact of Renal Dysfunction on Outcomes of Coronary Artery Bypass Surgery: Results from the Society of Thoracic Surgeons National Adult Cardiac Database. Circulation. 2006;113(8):1063-70. doi: 10.1161/CIRCULATIONAHA.105.580084.
https://doi.org/10.1161/CIRCULATIONAHA.1...
,2424 Miceli A, Bruno VD, Capoun R, Romeo F, Angelini GD, Caputo M. Occult Renal Dysfunction: A Mortality and Morbidity Risk Factor in Coronary Artery Bypass Grafting Surgery. J Thorac Cardiovasc Surg. 2011;141(3):771-6. doi: 10.1016/j.jtcvs.2010.08.016.
https://doi.org/10.1016/j.jtcvs.2010.08....
postoperative renal dysfunction,2323 Cooper WA, O‘Brien SM, Thourani VH, Guyton RA, Bridges CR, Szczech LA, et al. Impact of Renal Dysfunction on Outcomes of Coronary Artery Bypass Surgery: Results from the Society of Thoracic Surgeons National Adult Cardiac Database. Circulation. 2006;113(8):1063-70. doi: 10.1161/CIRCULATIONAHA.105.580084.
https://doi.org/10.1161/CIRCULATIONAHA.1...
,2424 Miceli A, Bruno VD, Capoun R, Romeo F, Angelini GD, Caputo M. Occult Renal Dysfunction: A Mortality and Morbidity Risk Factor in Coronary Artery Bypass Grafting Surgery. J Thorac Cardiovasc Surg. 2011;141(3):771-6. doi: 10.1016/j.jtcvs.2010.08.016.
https://doi.org/10.1016/j.jtcvs.2010.08....
need for hemodialysis,2323 Cooper WA, O‘Brien SM, Thourani VH, Guyton RA, Bridges CR, Szczech LA, et al. Impact of Renal Dysfunction on Outcomes of Coronary Artery Bypass Surgery: Results from the Society of Thoracic Surgeons National Adult Cardiac Database. Circulation. 2006;113(8):1063-70. doi: 10.1161/CIRCULATIONAHA.105.580084.
https://doi.org/10.1161/CIRCULATIONAHA.1...
,2424 Miceli A, Bruno VD, Capoun R, Romeo F, Angelini GD, Caputo M. Occult Renal Dysfunction: A Mortality and Morbidity Risk Factor in Coronary Artery Bypass Grafting Surgery. J Thorac Cardiovasc Surg. 2011;141(3):771-6. doi: 10.1016/j.jtcvs.2010.08.016.
https://doi.org/10.1016/j.jtcvs.2010.08....
cerebrovascular accident,2323 Cooper WA, O‘Brien SM, Thourani VH, Guyton RA, Bridges CR, Szczech LA, et al. Impact of Renal Dysfunction on Outcomes of Coronary Artery Bypass Surgery: Results from the Society of Thoracic Surgeons National Adult Cardiac Database. Circulation. 2006;113(8):1063-70. doi: 10.1161/CIRCULATIONAHA.105.580084.
https://doi.org/10.1161/CIRCULATIONAHA.1...
and hospitalization >7 days2323 Cooper WA, O‘Brien SM, Thourani VH, Guyton RA, Bridges CR, Szczech LA, et al. Impact of Renal Dysfunction on Outcomes of Coronary Artery Bypass Surgery: Results from the Society of Thoracic Surgeons National Adult Cardiac Database. Circulation. 2006;113(8):1063-70. doi: 10.1161/CIRCULATIONAHA.105.580084.
https://doi.org/10.1161/CIRCULATIONAHA.1...
,2424 Miceli A, Bruno VD, Capoun R, Romeo F, Angelini GD, Caputo M. Occult Renal Dysfunction: A Mortality and Morbidity Risk Factor in Coronary Artery Bypass Grafting Surgery. J Thorac Cardiovasc Surg. 2011;141(3):771-6. doi: 10.1016/j.jtcvs.2010.08.016.
https://doi.org/10.1016/j.jtcvs.2010.08....
after CABG. These conditions may contribute to PHS after surgery.2222 Lv M, Hu B, Ge W, Li Z, Wang Q, Han C, et al. Impact of Preoperative Occult Renal Dysfunction on Early and Late Outcomes after Off-Pump Coronary Artery Bypass. Heart Lung Circ. 2021;30(2):288-95. doi: 10.1016/j.hlc.2020.05.105.
https://doi.org/10.1016/j.hlc.2020.05.10...

23 Cooper WA, O‘Brien SM, Thourani VH, Guyton RA, Bridges CR, Szczech LA, et al. Impact of Renal Dysfunction on Outcomes of Coronary Artery Bypass Surgery: Results from the Society of Thoracic Surgeons National Adult Cardiac Database. Circulation. 2006;113(8):1063-70. doi: 10.1161/CIRCULATIONAHA.105.580084.
https://doi.org/10.1161/CIRCULATIONAHA.1...
-2424 Miceli A, Bruno VD, Capoun R, Romeo F, Angelini GD, Caputo M. Occult Renal Dysfunction: A Mortality and Morbidity Risk Factor in Coronary Artery Bypass Grafting Surgery. J Thorac Cardiovasc Surg. 2011;141(3):771-6. doi: 10.1016/j.jtcvs.2010.08.016.
https://doi.org/10.1016/j.jtcvs.2010.08....

The association between red blood cell transfusion and adverse events in the postoperative period of CABG is consistently described in the literature.2525 Corwin HL, Gettinger A, Pearl RG, Fink MP, Levy MM, Abraham E, et al. The CRIT Study: Anemia and Blood Transfusion in the Critically Ill--current Clinical Practice in the United States. Crit Care Med. 2004;32(1):39-52. doi: 10.1097/01.CCM.0000104112.34142.79.
https://doi.org/10.1097/01.CCM.000010411...

26 Vincent JL, Baron JF, Reinhart K, Gattinoni L, Thijs L, Webb A, et al. Anemia and Blood Transfusion in Critically Ill Patients. JAMA. 2002;288(12):1499-507. doi: 10.1001/jama.288.12.1499.
https://doi.org/10.1001/jama.288.12.1499...

27 Koch CG, Li L, Duncan AI, Mihaljevic T, Cosgrove DM, Loop FD, et al. Morbidity and Mortality Risk Associated with Red Blood Cell and Blood-component Transfusion in Isolated Coronary Artery Bypass Grafting. Crit Care Med. 2006;34(6):1608-16. doi: 10.1097/01.CCM.0000217920.48559.D8.
https://doi.org/10.1097/01.CCM.000021792...
-2828 Dorneles CC, Bodanese LC, Guaragna JC, Macagnan FE, Coelho JC, Borges AP, et al. The Impact of Blood Transfusion on Morbidity and Mortality after Cardiac Surgery. Rev Bras Cir Cardiovasc. 2011;26(2):222-9. doi: 10.1590/s0102-76382011000200012.
https://doi.org/10.1590/s0102-7638201100...
The link between PHS and blood transfusion, as observed in this study, is supported by the existing literature.2626 Vincent JL, Baron JF, Reinhart K, Gattinoni L, Thijs L, Webb A, et al. Anemia and Blood Transfusion in Critically Ill Patients. JAMA. 2002;288(12):1499-507. doi: 10.1001/jama.288.12.1499.
https://doi.org/10.1001/jama.288.12.1499...

27 Koch CG, Li L, Duncan AI, Mihaljevic T, Cosgrove DM, Loop FD, et al. Morbidity and Mortality Risk Associated with Red Blood Cell and Blood-component Transfusion in Isolated Coronary Artery Bypass Grafting. Crit Care Med. 2006;34(6):1608-16. doi: 10.1097/01.CCM.0000217920.48559.D8.
https://doi.org/10.1097/01.CCM.000021792...

28 Dorneles CC, Bodanese LC, Guaragna JC, Macagnan FE, Coelho JC, Borges AP, et al. The Impact of Blood Transfusion on Morbidity and Mortality after Cardiac Surgery. Rev Bras Cir Cardiovasc. 2011;26(2):222-9. doi: 10.1590/s0102-76382011000200012.
https://doi.org/10.1590/s0102-7638201100...
-2929 Murphy GJ, Reeves BC, Rogers CA, Rizvi SI, Culliford L, Angelini GD. Increased Mortality, Postoperative Morbidity, and Cost after Red Blood Cell Transfusion in Patients Having Cardiac Surgery. Circulation. 2007;116(22):2544-52. doi: 10.1161/CIRCULATIONAHA.107.698977.
https://doi.org/10.1161/CIRCULATIONAHA.1...
Several factors contribute to this association, such as infections, arrhythmias, acute renal failure, and cerebrovascular accident.2727 Koch CG, Li L, Duncan AI, Mihaljevic T, Cosgrove DM, Loop FD, et al. Morbidity and Mortality Risk Associated with Red Blood Cell and Blood-component Transfusion in Isolated Coronary Artery Bypass Grafting. Crit Care Med. 2006;34(6):1608-16. doi: 10.1097/01.CCM.0000217920.48559.D8.
https://doi.org/10.1097/01.CCM.000021792...

28 Dorneles CC, Bodanese LC, Guaragna JC, Macagnan FE, Coelho JC, Borges AP, et al. The Impact of Blood Transfusion on Morbidity and Mortality after Cardiac Surgery. Rev Bras Cir Cardiovasc. 2011;26(2):222-9. doi: 10.1590/s0102-76382011000200012.
https://doi.org/10.1590/s0102-7638201100...
-2929 Murphy GJ, Reeves BC, Rogers CA, Rizvi SI, Culliford L, Angelini GD. Increased Mortality, Postoperative Morbidity, and Cost after Red Blood Cell Transfusion in Patients Having Cardiac Surgery. Circulation. 2007;116(22):2544-52. doi: 10.1161/CIRCULATIONAHA.107.698977.
https://doi.org/10.1161/CIRCULATIONAHA.1...
In a prospective, multicenter cohort study conducted in the United States, transfusion of packed red blood cells was identified as an independent risk factor for PHS in the intensive care unit and overall length of hospital stay.2525 Corwin HL, Gettinger A, Pearl RG, Fink MP, Levy MM, Abraham E, et al. The CRIT Study: Anemia and Blood Transfusion in the Critically Ill--current Clinical Practice in the United States. Crit Care Med. 2004;32(1):39-52. doi: 10.1097/01.CCM.0000104112.34142.79.
https://doi.org/10.1097/01.CCM.000010411...
This finding aligns with a prospective observational study that found the same associations regardless of the pre-transfusion hemoglobin value.2626 Vincent JL, Baron JF, Reinhart K, Gattinoni L, Thijs L, Webb A, et al. Anemia and Blood Transfusion in Critically Ill Patients. JAMA. 2002;288(12):1499-507. doi: 10.1001/jama.288.12.1499.
https://doi.org/10.1001/jama.288.12.1499...

Based on the data from this study and previous studies, it is understood that interventions targeting the impact variables have the potential to reduce the risk of prolonged postoperative hospitalization, such as preventive and therapeutic measures specific for patients >60 years; diagnosis of preoperative renal dysfunction and perioperative nephroprotection measures; techniques to reduce intraoperative red blood cell transfusion.

Limitations

In this study, logistic regression was used to identify predictors of PHS following CABG. While logistic regression is efficient for such analyses, artificial intelligence techniques are increasingly employed, particularly for handling large databases with similar objectives, offering potentially reduced error probabilities.

The lack of data regarding postoperative length of stay led to the exclusion of certain patients from this analysis, thus limiting the sample size. Nonetheless, the analysis performed had a greater number of events, surpassing the requirements for such analyses. In addition, this study represents the largest sample among previous studies conducted in the Brazilian population, aligning well with the global literature.

In this analysis, the construction of a risk score capable of predicting the risk of PHS after CABG was not performed. However, these data can serve as a parameter for the development of such a model in future studies.

Conclusion

Patients aged over 60 years, along with renal failure and intraoperative red blood cell transfusion, were independent predictors of PHS after CABG. These variables should be validated in other populations to confirm their accuracy and can be considered in multiprofessional strategic planning aimed at optimizing healthcare system results and resource utilization.

  • Sources of funding
    This study was funded by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP).
  • Study association
    This study is not associated with any thesis or dissertation work.
  • Ethics approval and consent to participate
    This study was approved by the Ethics Committee of the Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo under the protocol number 66919417.6.1001.0068, parecer 5.603.742. All the procedures in this study were in accordance with the 1975 Helsinki Declaration, updated in 2013.

Referências

  • 1
    LaPar DJ, Crosby IK, Rich JB, Fonner E Jr, Kron IL, Ailawadi G, et al. A Contemporary Cost Analysis of Postoperative Morbidity after Coronary Artery Bypass Grafting with and Without Concomitant Aortic Valve Replacement to Improve Patient Quality and Cost-effective Care. Ann Thorac Surg. 2013;96(5):1621-7. doi: 10.1016/j.athoracsur.2013.05.050.
    » https://doi.org/10.1016/j.athoracsur.2013.05.050
  • 2
    Torabipour A, Arab M, Zeraati H, Rashidian A, Sari AA, Sarzaiem MR. Multivariate Analysis of Factors Influencing Length of Hospital Stay after Coronary Artery Bypass Surgery in Tehran, Iran. Acta Med Iran. 2016;54(2):124-33.
  • 3
    Kato N, Kondo M, Okubo I, Hasegawa T. Length of Hospital Stay in Japan 1971-2008: Hospital Ownership and Cost-containment Policies. Health Policy. 2014;115(2-3):180-8. doi: 10.1016/j.healthpol.2014.01.002.
    » https://doi.org/10.1016/j.healthpol.2014.01.002
  • 4
    Brasil. Ministério da Saúde. Portaria GM/MS nº 1.100, de 12 de maio de 2022. Define o 1º Ciclo do Programa de Qualificação da Assistência Cardiovascular, QualiSUS Cardio, no âmbito do Sistema Único de Saúde – SUS. Brasília: Ministério da Saúde; 2022.
  • 5
    Neumann FJ, Sousa-Uva M, Ahlsson A, Alfonso F, Banning AP, Benedetto U, et al. 2018 ESC/EACTS Guidelines on Myocardial Revascularization. Eur Heart J. 2019;40(2):87-165. doi: 10.1093/eurheartj/ehy394.
    » https://doi.org/10.1093/eurheartj/ehy394
  • 6
    Kaboli PJ, Go JT, Hockenberry J, Glasgow JM, Johnson SR, Rosenthal GE, et al. Associations Between Reduced Hospital Length of Stay and 30-day Readmission Rate and Mortality: 14-year Experience in 129 Veterans Affairs Hospitals. Ann Intern Med. 2012;157(12):837-45. doi: 10.7326/0003-4819-157-12-201212180-00003.
    » https://doi.org/10.7326/0003-4819-157-12-201212180-00003
  • 7
    Osnabrugge RL, Speir AM, Head SJ, Jones PG, Ailawadi G, Fonner CE, et al. Prediction of Costs and Length of Stay in Coronary Artery Bypass Grafting. Ann Thorac Surg. 2014;98(4):1286-93. doi: 10.1016/j.athoracsur.2014.05.073..
    » https://doi.org/10.1016/j.athoracsur.2014.05.073
  • 8
    Brasil. Ministério da Saúde. Banco de dados do Sistema Único de Saúde-DATASUS [Internet]. Brasília: Ministério da Saúde; 2023 [cited 2023 Jan 08]. Available from: http://www.datasus.gov.br
    » http://www.datasus.gov.br
  • 9
    Li M, Zhang J, Gan TJ, Qin G, Wang L, Zhu M, et al. Enhanced Recovery after Surgery Pathway for Patients Undergoing Cardiac Surgery: A Randomized Clinical Trial. Eur J Cardiothorac Surg. 2018;54(3):491-7. doi: 10.1093/ejcts/ezy100.
    » https://doi.org/10.1093/ejcts/ezy100
  • 10
    Lee J, Govindan S, Celi LA, Khabbaz KR, Subramaniam B. Customized Prediction of Short Length of Stay Following Elective Cardiac Surgery in Elderly Patients Using a Genetic Algorithm. World J Cardiovasc Surg. 2013;3(5):163-70. doi: 10.4236/wjcs.2013.35034.
    » https://doi.org/10.4236/wjcs.2013.35034
  • 11
    Shahian DM, O’Brien SM, Filardo G, Ferraris VA, Haan CK, Rich JB, et al. The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 1--coronary Artery Bypass Grafting Surgery. Ann Thorac Surg. 2009;88(1Suppl):2-22. doi: 10.1016/j.athoracsur.2009.05.053.
    » https://doi.org/10.1016/j.athoracsur.2009.05.053
  • 12
    Triana AJ, Vyas R, Shah AS, Tiwari V. Predicting Length of Stay of Coronary Artery Bypass Grafting Patients Using Machine Learning. J Surg Res. 2021;264:68-75. doi: 10.1016/j.jss.2021.02.003.
    » https://doi.org/10.1016/j.jss.2021.02.003
  • 13
    Oliveira EK, Turquetto AL, Tauil PL, Junqueira LF Jr, Porto LG. Risk Factors for Prolonged Hospital Stay after Isolated Coronary Artery Bypass Grafting. Rev Bras Cir Cardiovasc. 2013;28(3):353-63. doi: 10.5935/1678-9741.20130055.
    » https://doi.org/10.5935/1678-9741.20130055
  • 14
    Volkmann MA, Behr PE, Burmeister JE, Consoni PR, Kalil RA, Prates PR, et al. Hidden Renal Dysfunction Causes Increased In-hospital Mortality Risk after Coronary Artery Bypass Graft Surgery. Rev Bras Cir Cardiovasc. 2011;26(3):319-25. doi: 10.5935/1678-9741.20110005.
    » https://doi.org/10.5935/1678-9741.20110005
  • 15
    Orlandi BMM, Mejia OAV, Borgomoni GB, Goncharov M, Rocha KN, Bassolli L, et al. REPLICCAR II Study: Data Quality Audit in the Paulista Cardiovascular Surgery Registry. PLoS One. 2020;15(7):e0223343. doi: 10.1371/journal.pone.0223343.
    » https://doi.org/10.1371/journal.pone.0223343
  • 16
    Cockcroft DW, Gault MH. Prediction of Creatinine Clearance from Serum Creatinine. Nephron. 1976;16(1):31-41. doi: 10.1159/000180580.
    » https://doi.org/10.1159/000180580
  • 17
    Adeli K, Raizman JE, Chen Y, Higgins V, Nieuwesteeg M, Abdelhaleem M, et al. Complex Biological Profile of Hematologic Markers Across Pediatric, Adult, and Geriatric Ages: Establishment of Robust Pediatric and Adult Reference Intervals on the Basis of the Canadian Health Measures Survey. Clin Chem. 2015;61(8):1075-86. doi: 10.1373/clinchem.2015.240531.
    » https://doi.org/10.1373/clinchem.2015.240531
  • 18
    Smith ER. The Angina Grading System of the Canadian Cardiovascular Society. Can J Cardiol. 2002;18(4):439, 442.
  • 19
    Fisher JD. New York Heart Association Classification. Arch Intern Med. 1972;129(5):836.
  • 20
    Nashef SA, Roques F, Sharples LD, Nilsson J, Smith C, Goldstone AR, et al. EuroSCORE II. Eur J Cardiothorac Surg. 2012;41(4):734-44. doi: 10.1093/ejcts/ezs043.
    » https://doi.org/10.1093/ejcts/ezs043
  • 21
    Mortasawi A, Arnrich B, Walter J, Frerichs I, Rosendahl U, Ennker J. Impact of Age on the Results of Coronary Artery Bypass Grafting. Asian Cardiovasc Thorac Ann. 2004;12(4):324-9. doi: 10.1177/021849230401200410.
    » https://doi.org/10.1177/021849230401200410
  • 22
    Lv M, Hu B, Ge W, Li Z, Wang Q, Han C, et al. Impact of Preoperative Occult Renal Dysfunction on Early and Late Outcomes after Off-Pump Coronary Artery Bypass. Heart Lung Circ. 2021;30(2):288-95. doi: 10.1016/j.hlc.2020.05.105.
    » https://doi.org/10.1016/j.hlc.2020.05.105
  • 23
    Cooper WA, O‘Brien SM, Thourani VH, Guyton RA, Bridges CR, Szczech LA, et al. Impact of Renal Dysfunction on Outcomes of Coronary Artery Bypass Surgery: Results from the Society of Thoracic Surgeons National Adult Cardiac Database. Circulation. 2006;113(8):1063-70. doi: 10.1161/CIRCULATIONAHA.105.580084.
    » https://doi.org/10.1161/CIRCULATIONAHA.105.580084
  • 24
    Miceli A, Bruno VD, Capoun R, Romeo F, Angelini GD, Caputo M. Occult Renal Dysfunction: A Mortality and Morbidity Risk Factor in Coronary Artery Bypass Grafting Surgery. J Thorac Cardiovasc Surg. 2011;141(3):771-6. doi: 10.1016/j.jtcvs.2010.08.016.
    » https://doi.org/10.1016/j.jtcvs.2010.08.016
  • 25
    Corwin HL, Gettinger A, Pearl RG, Fink MP, Levy MM, Abraham E, et al. The CRIT Study: Anemia and Blood Transfusion in the Critically Ill--current Clinical Practice in the United States. Crit Care Med. 2004;32(1):39-52. doi: 10.1097/01.CCM.0000104112.34142.79.
    » https://doi.org/10.1097/01.CCM.0000104112.34142.79
  • 26
    Vincent JL, Baron JF, Reinhart K, Gattinoni L, Thijs L, Webb A, et al. Anemia and Blood Transfusion in Critically Ill Patients. JAMA. 2002;288(12):1499-507. doi: 10.1001/jama.288.12.1499.
    » https://doi.org/10.1001/jama.288.12.1499
  • 27
    Koch CG, Li L, Duncan AI, Mihaljevic T, Cosgrove DM, Loop FD, et al. Morbidity and Mortality Risk Associated with Red Blood Cell and Blood-component Transfusion in Isolated Coronary Artery Bypass Grafting. Crit Care Med. 2006;34(6):1608-16. doi: 10.1097/01.CCM.0000217920.48559.D8.
    » https://doi.org/10.1097/01.CCM.0000217920.48559.D8
  • 28
    Dorneles CC, Bodanese LC, Guaragna JC, Macagnan FE, Coelho JC, Borges AP, et al. The Impact of Blood Transfusion on Morbidity and Mortality after Cardiac Surgery. Rev Bras Cir Cardiovasc. 2011;26(2):222-9. doi: 10.1590/s0102-76382011000200012.
    » https://doi.org/10.1590/s0102-76382011000200012
  • 29
    Murphy GJ, Reeves BC, Rogers CA, Rizvi SI, Culliford L, Angelini GD. Increased Mortality, Postoperative Morbidity, and Cost after Red Blood Cell Transfusion in Patients Having Cardiac Surgery. Circulation. 2007;116(22):2544-52. doi: 10.1161/CIRCULATIONAHA.107.698977.
    » https://doi.org/10.1161/CIRCULATIONAHA.107.698977

Edited by

Editor responsible for the review: Alexandre Colafranceschi

Publication Dates

  • Publication in this collection
    24 June 2024
  • Date of issue
    2024

History

  • Received
    06 Nov 2023
  • Reviewed
    09 Feb 2024
  • Accepted
    13 Mar 2024
Sociedade Brasileira de Cardiologia - SBC Avenida Marechal Câmara, 160, sala: 330, Centro, CEP: 20020-907, (21) 3478-2700 - Rio de Janeiro - RJ - Brazil, Fax: +55 21 3478-2770 - São Paulo - SP - Brazil
E-mail: revista@cardiol.br