Literature DB >> 19324131

Impact of renal dysfunction on long-term survival after isolated coronary artery bypass surgery.

Ye Lin1, Zhe Zheng, Yan Li, Xin Yuan, Jianfeng Hou, Shiju Zhang, Hongguang Fan, Yang Wang, Wei Li, Shengshou Hu.   

Abstract

BACKGROUND: Preoperative renal dysfunction has been an important predictor for adverse cardiovascular events after coronary artery bypass grafting (CABG). In the past, serum creatinine was widely used to assess renal function. Until recently, estimated glomerular filtration rate (eGFR) was recommended in evaluating renal function. The Cockcroft-Gault formula and the Modification of Diet in Renal Disease (MDRD) equation are two widely used formulas in clinical practice. Which method best predicts long-term outcome after CABG is still unknown. This study compared the predictive effectiveness of the Cockcroft-Gault formula, the MDRD equation, and serum creatinine level for in-hospital and long-term mortality.
METHODS: We retrospectively reviewed data collected from 5559 patients who underwent isolated CABG at Fuwai Hospital from January 1999 to December 2005. The main outcomes were in-hospital and long-term mortality. Receiver operating characteristic (ROC) curves and Cox analysis were used for the comparison.
RESULTS: Mean follow-up was 56.5 +/- 24.6 months. ROC curve analysis showed that the Cockcroft-Gault formula had the greatest accuracy for predicting in-hospital mortality (area under the curve, 0.755; p < 0.001). Multivariate analysis confirmed that the eGFR based on the Cockcroft-Gault formula was an independent predictor of in-hospital (odds ratio, 4.51, p < 0.001) and long-term (hazard ratio, 1.54; p = 0.003) mortality. Both formulas were better than the serum creatinine level.
CONCLUSIONS: Both formulas could provide a better measure of risk assessment than serum creatinine for in-hospital and long-term mortality. The Cockcroft-Gault formula was better than the MDRD equation for predicting in-hospital mortality.

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Year:  2009        PMID: 19324131     DOI: 10.1016/j.athoracsur.2009.01.065

Source DB:  PubMed          Journal:  Ann Thorac Surg        ISSN: 0003-4975            Impact factor:   4.330


  6 in total

1.  Which method of estimating renal function is the best predictor of mortality after coronary artery bypass grafting?

Authors:  A H M van Straten; M A Soliman Hamad; B M J A Koene; E J Martens; M E S H Tan; E Berreklouw; A A J van Zundert
Journal:  Neth Heart J       Date:  2011-11       Impact factor: 2.380

2.  Implications of Hemodialysis in Patients Undergoing Coronary Artery Bypass Grafting.

Authors:  Jimmy T Efird; Wesley T O'Neal; Catherine A Gouge; Linda C Kindell; Whitney L Kennedy; Paul Bolin; Jason B O'Neal; Curtis A Anderson; Evelio Rodriguez; T Bruce Ferguson; W Randolph Chitwood; Alan P Kypson
Journal:  Int J Cardiovasc Res       Date:  2013-03-13

3.  Cardiovascular events and all-cause mortality in a cohort of 57,946 patients with type 2 diabetes: associations with renal function and cardiovascular risk factors.

Authors:  Lucia Cea Soriano; Saga Johansson; Bergur Stefansson; Luis A García Rodríguez
Journal:  Cardiovasc Diabetol       Date:  2015-04-18       Impact factor: 9.951

Review 4.  Factors affecting mortality after coronary bypass surgery: a scoping review.

Authors:  Sean Christopher Hardiman; Yuri Fabiola Villan Villan; Jillian Michelle Conway; Katie Jane Sheehan; Boris Sobolev
Journal:  J Cardiothorac Surg       Date:  2022-03-21       Impact factor: 1.637

5.  Prognostic Values of Three Equations in Estimating Glomerular Filtration Rates of Patients Undergoing Off-Pump Coronary Artery Bypass Grafting.

Authors:  Zhi Li; Wen Ge; Chunyan Han; Mengwei Lv; Yanzhong He; Juntao Su; Ban Liu; Yangyang Zhang
Journal:  Ther Clin Risk Manag       Date:  2020-05-21       Impact factor: 2.423

6.  Joint relationship between renal function and proteinuria on mortality of patients with type 2 diabetes: the Taichung Diabetes Study.

Authors:  Cheng-Chieh Lin; Ching-Chu Chen; Pei-Tseng Kung; Chia-Ing Li; Sing-Yu Yang; Chiu-Shong Liu; Wen-Yuan Lin; Cheng-Chun Lee; Tsai-Chung Li; Sharon L R Kardia
Journal:  Cardiovasc Diabetol       Date:  2012-10-19       Impact factor: 9.951

  6 in total

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