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Updated: Jul 9, 2026

A Large Animal Model for Acute Kidney Injury by Temporary Bilateral Renal Artery Occlusion
Published on: February 2, 2021
Multivariable prediction of renal insufficiency developing after cardiac surgery
Jeremiah R Brown1, Richard P Cochran, Bruce J Leavitt
1Center for the Evaluative Clinical Sciences, Dartmouth Medical School, Lebanon, NH 03756, USA. Jeremiah.R.Brown@Dartmouth.edu
Insights
Preoperative patient factors can predict severe renal insufficiency after coronary artery bypass graft (CABG) surgery. This helps identify high-risk individuals to potentially reduce adverse outcomes and mortality.
Area of Science:
- Cardiology
- Nephrology
- Surgical Outcomes Research
Background:
- Renal insufficiency post-coronary artery bypass graft (CABG) surgery is linked to higher mortality.
- Predicting this risk preoperatively is crucial for patient management.
Purpose of the Study:
- To develop and validate a predictive model for severe postoperative renal insufficiency.
- To identify key preoperative patient characteristics associated with this risk.
Main Methods:
- Prospective data from 8363 patients undergoing isolated CABG were analyzed.
- A multivariable logistic regression model was used to identify predictors.
- Model performance was assessed using C-Index (Area Under ROC) and Hosmer-Lemeshow statistics.
Main Results:
- 3% of patients with normal preoperative renal function developed severe renal insufficiency.
- Key predictors included age, gender, elevated white blood cell count, prior CABG, heart failure, peripheral vascular disease, diabetes, hypertension, and intraaortic balloon pump use.
- The prediction model demonstrated good discrimination (ROC 0.72) and calibration.
Conclusions:
- A robust prediction rule was developed to identify patients at high risk.
- This tool can aid clinicians in managing patients with normal preoperative renal function.
- Early identification may allow interventions to mitigate adverse outcomes and mortality.
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 <60 mL/min/1.73 m2 and severe renal insufficiency as a GFR <30. 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 >12,000, prior CABG, congestive heart failure, peripheral vascular disease, diabetes, hypertension, and preoperative intraaortic balloon pump. The predictive model was significant with chi2 150.8, probability value <0.0001. 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.
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