Multivariable Prediction of Renal Insufficiency Developing After Cardiac Surgery

Abstract

Background-Renal insufficiency after coronary artery bypass graft (CABG) surgery is associated with increased short-term and long-term mortality. We hypothesized that preoperative patient characteristics could be used to predict the patient-specific risk of developing postoperative renal insufficiency. Methods and Results-Data were prospectively collected on 11 301 patients in northern New England who underwent isolated CABG surgery between 2001 and 2005. Based on National Kidney Foundation definitions, moderate renal insufficiency was defined as a GFR Ͻ60 mL/min/1.73m 2 and severe renal insufficiency as a GFR Ͻ30. Patients with at least moderate renal insufficiency at baseline were eliminated from the analysis, leaving 8363 patients who became our study cohort. A prediction model was developed to identify variables that best predicted the risk of developing severe renal insufficiency using multiple logistic regression, and the predictive ability of the model quantified using a bootstrap validated C-Index (Area Under ROC) and Hosmer-Lemeshow statistic. Three percent of the patients with normal renal function before CABG surgery developed severe renal insufficiency (229/8363). In a multivariable model the preoperative patient characteristics most strongly associated with postoperative severe renal insufficiency included: age, gender, white blood cell count Ͼ12 000, prior CABG, congestive heart failure, peripheral vascular disease, diabetes, hypertension, and preoperative intraaortic balloon pump. The predictive model was significant with 2 150.8, probability value Ͻ0.0001. The model discriminated well, ROC 0.72 (95%CI: 0.68 to 0.75). The model was well calibrated according to the Hosmer-Lemeshow test. Conclusions-We developed a robust prediction rule to assist clinicians in identifying patients with normal, or near normal, preoperative renal function who are at high risk of developing severe renal insufficiency. Physicians may be able to take steps to limit this adverse outcome and its associated increase in morbidity and mortality.

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

“…This seems logical because the postoperative renal function is the result of the preoperative renal function and the subsequent trauma of the operation [10,17]. This operative trauma may lead to further deterioration of the renal function with subsequent higher early and late mortality.…”

Preoperative Use of Angiotensin-Converting Enzyme Inhibitors/Angiotensin Receptor Blockers Is Associated with Increased Risk for Acute Kidney Injury after Cardiovascular Surgery

“…In several analyses of renal insufficiency, baseline hypertension was not in the set of predictors (20 -23), although, in one of them (23), systolic BP Ն 160 with CABG was important in predicting renal failure. In one study that focused on risk for postoperative dialysis (24), it was significant, whereas, in another research study on renal insufficiency (25), it was barely significant (P ϭ 0.049). The different objectives of these studies and the different definitions used for renal failure make it difficult to draw a definite conclusion, although it seems that hypertension does not play a major role in predicting AKI, which is the focus of our analysis.…”

Serum creatinine role in predicting outcome after cardiac surgery beyond acute kidney injury

“…Although some risk factors for AKI are common in general and cardiac surgery, the risk scores developed in a general surgery population underestimate the risk of AKI in cardiac surgery [126] . There are several risk prediction models that have been developed in the field of cardiac surgery [11,14,15,[127][128][129][130] . Chertow et al [11] developed the first risk score using a large population database in 1997.…”

“…Other available models are aimed at predicting AKI not requiring dialysis. They have not been externally validated, however, and due to different definitions of AKI it is difficult to generalize them [16,129,130] . The most important criticism to the available risk models is their lack of prediction for CSA-AKI.…”