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Published on: March 27, 2018
Validation of Renal Risk Score Models for Coronary Artery Bypass Surgery in Diabetic Patients
Mehmet Kalender1, Taylan Adademir2, Deniz Çevirme2
1Cardiovascular Surgery Department, Derince Training and Research Hospital, Kocaeli, Turkey.
Insights
The KDIGO criterion is superior for predicting acute kidney injury (AKI) in diabetic patients undergoing coronary artery bypass grafting (CABG). This scoring system aids early diagnosis and management in high-risk populations.
Area of Science:
- Nephrology
- Cardiology
- Surgical Outcomes
Background:
- Coronary artery bypass grafting (CABG) carries risks, especially with comorbidities like diabetes mellitus.
- Acute kidney injury (AKI) is a significant concern post-CABG, necessitating accurate diagnostic and grading tools.
- Existing AKI definitions include Kidney Disease: Improving Global Outcomes (KDIGO), Risk, Injury, Failure, Loss of kidney function and End-stage kidney disease (RIFLE), and Acute Kidney Injury Network (AKIN).
Purpose of the Study:
- To compare the predictive performance of KDIGO, RIFLE, and AKIN scoring systems for AKI in diabetic patients undergoing CABG.
- To investigate the utility of these AKI definitions in assessing renal impairment after CABG in a specific high-risk cohort.
Main Methods:
- A retrospective study of 617 diabetic patients who underwent on-pump CABG between January 2010 and December 2013.
- Application and comparison of KDIGO, RIFLE, and AKIN criteria for AKI assessment.
- Analysis of discriminative capacity using the area under the receiver operating characteristic curve (AUC).
Main Results:
- All three scoring systems demonstrated good discriminative capacity for predicting outcomes in the overall patient sample.
- The RIFLE score showed a higher area under the ROC curve (AUC) of 0.803 (95% CI: 0.724-0.882) in the general patient cohort.
- The goodness of fit was acceptable across all evaluated AKI classification scales.
Conclusions:
- KDIGO, RIFLE, and AKIN scoring systems are valuable for the early diagnosis of AKI in diabetic patients undergoing on-pump CABG.
- The KDIGO criterion exhibited superior prognostic power compared to AKIN and RIFLE in this study cohort.
- These findings support the use of KDIGO for enhanced risk stratification and management of AKI in this vulnerable patient population.
Background:
Coronary artery bypass grafting is applicable with very low mortality and morbidity rates around the world. However, exposure to even one of the risk factors increases mortality and morbidity significantly. There are three acute kidney injury definitions, and classification methods are applicable (Kidney Disease: Improving Global Outcomes (KDIGO); Risk, Injury, Failure, Loss of kidney function and End-stage kidney disease (RIFLE);" (for accuracy) and Acute Kidney Injury Network (AKIN)), for understanding and grading of renal impairment. With these definitions, it became possible to take measures at an early stage and start the management process. Methods for assessing renal impairment after coronary artery bypass grafting (CABG) specifically in patients with diabetes mellitus require further investigation. We compared these three acute kidney injury definitions for prediction of outcomes in diabetic patients undergoing coronary artery bypass grafting procedure.
Methods:
Between January 2010 and December 2013, a total of 617 consecutive patients with diabetes mellitus undergoing coronary artery bypass grafting (CABG) with cardiopulmonary bypass in our institution were included in the study.
Results:
We considered 617 CABG operations on diabetes mellitus patients for this study from January 2010 to December 2013. The three scores provided good discriminative capacity in the global patient sample, with the area under the ROC curve (AUC) being higher, RIFLE (0.803, 95% CI: 0.724-0.882). The goodness of fit was good for all scales.
Conclusions:
Especially in on-pump CABG patients with diabetes mellitus, we can use AKIN, RIFLE, and KDIGO scoring systems to predict early diagnosis for acute kidney injury (AKI). In our analysis, the KDIGO criterion was superior to AKIN and RIFLE with regard its prognostic power.
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