BACKGROUND: After cardiac surgery, acute renal failure (ARF) requiring dialysis develops in 1% to 5% of patients and is strongly associated with perioperative morbidity and mortality. Prior studies have attempted to identify predictors of ARF but have had insufficient power to perform multivariable analyses or to develop risk stratification algorithms. METHODS AND RESULTS: We conducted a prospective cohort study of 43 642 patients who underwent coronary artery bypass or valvular heart surgery in 43 Department of Veterans Affairs medical centers between April 1987 and March 1994. Logistic regression analysis was used to identify independent predictors of ARF requiring dialysis. A risk stratification algorithm derived from recursive partitioning was constructed and was validated on an independent sample of 3795 patients operated on between April and December 1994. The overall risk of ARF requiring dialysis was 1.1%. Thirty-day mortality in patients with ARF was 63.7%, compared with 4.3% in patients without ARF. Ten clinical variables related to baseline cardiovascular disease and renal function were independently associated with the risk of ARF. A risk stratification algorithm partitioned patients into low-risk (0.4%), medium-risk (0.9% to 2.8%), and high-risk (> or = 5.0%) groups on the basis of several of these factors and their interactions. CONCLUSIONS: The risk of ARF after cardiac surgery can be accurately quantified on the basis of readily available preoperative data. These findings may be used by physicians and surgeons to provide patients with improved risk estimates and to target high-risk subgroups for interventions aimed at reducing the risk and ameliorating the consequences of this serious complication.
BACKGROUND: After cardiac surgery, acute renal failure (ARF) requiring dialysis develops in 1% to 5% of patients and is strongly associated with perioperative morbidity and mortality. Prior studies have attempted to identify predictors of ARF but have had insufficient power to perform multivariable analyses or to develop risk stratification algorithms. METHODS AND RESULTS: We conducted a prospective cohort study of 43 642 patients who underwent coronary artery bypass or valvular heart surgery in 43 Department of Veterans Affairs medical centers between April 1987 and March 1994. Logistic regression analysis was used to identify independent predictors of ARF requiring dialysis. A risk stratification algorithm derived from recursive partitioning was constructed and was validated on an independent sample of 3795 patients operated on between April and December 1994. The overall risk of ARF requiring dialysis was 1.1%. Thirty-day mortality in patients with ARF was 63.7%, compared with 4.3% in patients without ARF. Ten clinical variables related to baseline cardiovascular disease and renal function were independently associated with the risk of ARF. A risk stratification algorithm partitioned patients into low-risk (0.4%), medium-risk (0.9% to 2.8%), and high-risk (> or = 5.0%) groups on the basis of several of these factors and their interactions. CONCLUSIONS: The risk of ARF after cardiac surgery can be accurately quantified on the basis of readily available preoperative data. These findings may be used by physicians and surgeons to provide patients with improved risk estimates and to target high-risk subgroups for interventions aimed at reducing the risk and ameliorating the consequences of this serious complication.
Authors: S Al-Ruzzeh; G Asimakopoulos; G Ambler; R Omar; R Hasan; B Fabri; A El-Gamel; A DeSouza; V Zamvar; S Griffin; D Keenan; U Trivedi; M Pullan; A Cale; M Cowen; K Taylor; M Amrani Journal: Heart Date: 2003-04 Impact factor: 5.994
Authors: Gaurav S Mehta; Damien J LaPar; Castigliano M Bhamidipati; John A Kern; Irving L Kron; Gilbert R Upchurch; Gorav Ailawadi Journal: Surgery Date: 2012-04-11 Impact factor: 3.982
Authors: Kevin W Lobdell; Devin M Parker; Donald S Likosky; Michael Rezaee; Moritz Wyler von Ballmoos; Shama S Alam; Sherry Owens; Heather Thiessen-Philbrook; Todd MacKenzie; Jeremiah R Brown Journal: J Thorac Cardiovasc Surg Date: 2018-04-11 Impact factor: 5.209