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Updated: Jul 9, 2026
09:02
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
Circulation
|September 14, 2007
Summary
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.
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