scholarly journals The impact of continuous haemofiltration with high-volume fluid exchange during cardiopulmonary bypass surgery on the recovery of patients with impaired renal function: a pilot randomised trial

2013 ◽  
Vol 17 (49) ◽  
Author(s):  
B Matata ◽  
N Mediratta ◽  
M Morgan ◽  
S Shirley ◽  
N Scawn ◽  
...  
Keyword(s):  
Renal Function ◽  
Cardiopulmonary Bypass ◽  
Impaired Renal Function ◽  
Bypass Surgery ◽  
Randomised Trial ◽  
High Volume ◽  
Fluid Exchange ◽  
Cardiopulmonary Bypass Surgery ◽  
The Impact

Renal function after cardiopulmonary bypass surgery in cyanotic congenital heart disease

2000 ◽  
Vol 73 (2) ◽  
pp. 173-179 ◽  
Author(s):  
Sven Dittrich ◽  
Katrin Kurschat ◽  
Ingo Dähnert ◽  
Michael Vogel ◽  
Christian Müller ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Renal Function ◽  
Heart Disease ◽  
Cardiopulmonary Bypass ◽  
Congenital Heart ◽  
Bypass Surgery ◽  
Cyanotic Congenital Heart Disease ◽  
Cardiopulmonary Bypass Surgery

Safety and efficacy of intensive intraoperative glycaemic control in cardiopulmonary bypass surgery: a randomised trial

2014 ◽  
Vol 58 (5) ◽  
pp. 588-596 ◽  
Author(s):  
P. RUJIROJINDAKUL ◽  
T. LIABSUETRAKUL ◽  
E. MCNEIL ◽  
T. CHANCHAYANON ◽  
W. WASINWONG ◽  
...  
Keyword(s):  
Cardiopulmonary Bypass ◽  
Glycaemic Control ◽  
Bypass Surgery ◽  
Randomised Trial ◽  
Safety And Efficacy ◽  
Cardiopulmonary Bypass Surgery

Prevalence of Heparin-Associated Antibodies Without Thrombosis in Patients Undergoing Cardiopulmonary Bypass Surgery

Circulation ◽  
1997 ◽  
Vol 95 (5) ◽  
pp. 1242-1246 ◽  
Author(s):  
Thomas L. Bauer ◽  
Gowthami Arepally ◽  
Barbara A. Konkle ◽  
Bernadette Mestichelli ◽  
Sandor S. Shapiro ◽  
...  
Keyword(s):  
Cardiopulmonary Bypass ◽  
Bypass Surgery ◽  
Cardiopulmonary Bypass Surgery

scholarly journals Pulmonary infection after cardiopulmonary bypass surgery in children: a risk estimation model in China

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Chunnian Ren ◽  
Chun Wu ◽  
Zhengxia Pan ◽  
Quan Wang ◽  
Yonggang Li
Keyword(s):  
Risk Factors ◽  
Cardiopulmonary Bypass ◽  
Prediction Model ◽  
Congenital Heart ◽  
Bypass Surgery ◽  
Pulmonary Infection ◽  
Regression Analyses ◽  
Cardiopulmonary Bypass Surgery ◽  
Independent Risk Factors ◽  
Individualized Prediction

Abstract Objectives The occurrence of pulmonary infection after congenital heart disease (CHD) surgery can lead to significant increases in intensive care in cardiac intensive care unit (CICU) retention time, medical expenses, and risk of death risk. We hypothesized that patients with a high risk of pulmonary infection could be screened out as early after surgery. Hence, we developed and validated the first risk prediction model to verify our hypothesis. Methods Patients who underwent CHD surgery from October 2012 to December 2017 in the Children’s Hospital of Chongqing Medical University were included in the development group, while patients who underwent CHD surgery from December 2017 to October 2018 were included in the validation group. The independent risk factors associated with pulmonary infection following CHD surgery were screened using univariable and multivariable logistic regression analyses. The corresponding nomogram prediction model was constructed according to the regression coefficients. Model discrimination was evaluated by the area under the receiver operating characteristic curve (ROC) (AUC), and model calibration was conducted with the Hosmer-Lemeshow test. Results The univariate and multivariate logistic regression analyses identified the following six independent risk factors of pulmonary infection after cardiac surgery: age, weight, preoperative hospital stay, risk-adjusted classification for congenital heart surgery (RACHS)-1 score, cardiopulmonary bypass time and intraoperative blood transfusion. We established an individualized prediction model of pulmonary infection following cardiopulmonary bypass surgery for CHD in children. The model displayed accuracy and reliability and was evaluated by discrimination and calibration analyses. The AUCs for the development and validation groups were 0.900 and 0.908, respectively, and the P-values of the calibration tests were 0.999 and 0.452 respectively. Therefore, the predicted probability of the model was consistent with the actual probability. Conclusions Identified the independent risk factors of pulmonary infection after cardiopulmonary bypass surgery. An individualized prediction model was developed to evaluate the pulmonary infection of patients after surgery. For high-risk patients, after surgery, targeted interventions can reduce the risk of pulmonary infection.

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