Derivation and Validation of a Simplified Predictive Index for Renal Replacement Therapy After Cardiac Surgery
Duminda N. Wijeysundera,Keyvan Karkouti,Jean-Yves Dupuis,Vivek Rao,Christopher T. Chan,John Granton,W. Scott Beattie +6 more
TLDR
RRT after cardiac surgery is predicted by readily available preoperative information and discriminated well between low- and high-risk patients in derivation and validation cohorts, and the index had improved generalizability when used to predict likelihood ratios for RRT.Abstract:
ContextA predictive index for renal replacement therapy (RRT; hemodialysis or continuous venovenous hemodiafiltration) after cardiac surgery may improve clinical decision making and research design.ObjectivesTo develop a predictive index for RRT using preoperative information.Design, Setting, and ParticipantsRetrospective cohort of 20 131 cardiac surgery patients at 2 hospitals in Ontario, Canada. The derivation cohort consisted of 10 751 patients at Toronto General Hospital (1999-2004). The validation cohorts consisted of 2566 patients at Toronto General Hospital (2004-2005) and 6814 patients at Ottawa Heart Institute (1999-2003).Main Outcome MeasurePostoperative RRT.ResultsRRT rates in the derivation, Toronto validation, and Ottawa validation cohorts were 1.3%, 1.8%, and 2.2%, respectively. Multivariable predictors of RRT were preoperative estimated glomerular filtration rate, diabetes mellitus requiring medication, left ventricular ejection fraction, previous cardiac surgery, procedure, urgency of surgery, and preoperative intra-aortic balloon pump. The predictive index was scored from 0 to 8 points. An estimated glomerular filtration rate less than or equal to 30 mL/min was assigned 2 points; other components were assigned 1 point each: estimated glomerular filtration rate 31 to 60 mL/min, diabetes mellitus, ejection fraction less than or equal to 40%, previous cardiac surgery, procedure other than coronary artery bypass grafting, intra-aortic balloon pump, and nonelective case. Among the 53% of patients with low risk scores (≤1), the risk of RRT was 0.4%; by comparison, this risk was 10% among the 6% of patients with high-risk scores (≥4). The predictive index had areas under the receiver operating characteristic curve in the derivation, Toronto validation, and Ottawa validation cohorts of 0.81, 0.78, and 0.78, respectively. When these cohorts were stratified based on index scores, likelihood ratios for RRT were more concordant than observed RRT rates.ConclusionsRRT after cardiac surgery is predicted by readily available preoperative information. A simple predictive index based on this information discriminated well between low- and high-risk patients in derivation and validation cohorts. The index had improved generalizability when used to predict likelihood ratios for RRT.read more
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KDIGO clinical practice guidelines for acute kidney injury.
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Intensive insulin therapy for the critically ill patients with stress hyperglycemia
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Urine NGAL Predicts Severity of Acute Kidney Injury After Cardiac Surgery: A Prospective Study
Michael J. Bennett,Catherine L. Dent,Qing Ma,Sudha Dastrala,Frank C. Grenier,Ryan F. Workman,Hina N. Syed,Salman Ali,Jonathan Barasch,Prasad Devarajan +9 more
TL;DR: Urine NGAL is an early predictive biomarker of AKI severity after CPB and accurate measurements of urine NGAL are obtained using the ARCHITECT platform.
Journal ArticleDOI
KDOQI US Commentary on the 2012 KDIGO Clinical Practice Guideline for Acute Kidney Injury
Paul M. Palevsky,Kathleen D. Liu,Patrick D. Brophy,Lakhmir S. Chawla,Chirag R. Parikh,Charuhas V. Thakar,Ashita Tolwani,Sushrut S. Waikar,Steven D. Weisbord +8 more
TL;DR: A group of US experts in adult and pediatric AKI and critical care nephrology to review the recommendations and comment on their relevancy in the context of current US clinical practice and concerns concluded that there is insufficient evidence to support their widespread application to clinical care in the United States.
Journal ArticleDOI
Acute Kidney Injury After Cardiac Surgery Focus on Modifiable Risk Factors
Keyvan Karkouti,Duminda N. Wijeysundera,Terrence M. Yau,Jeannie Callum,Davy Cheng,Mark Crowther,Jean Yves Dupuis,Stephen E. Fremes,Blaine Kent,Claude Laflamme,Andre Lamy,Jean Francois Legare,C. David Mazer,Stuart A. McCluskey,Fraser D. Rubens,Corey Sawchuk,W. Scott Beattie +16 more
TL;DR: Therapies aimed at mitigating preoperative anemia, perioperative red blood cell transfusions, and surgical reexploration may offer protection against this complication.
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