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- Open Access
Best prediction for need of dialysis following cardiac surgery is obtained with the Thakar model
© Kiers et al. 2011
- Published: 1 March 2011
- Kidney Disease
- Serum Creatinine
- Cardiopulmonary Bypass
- Acute Kidney Injury
- Serum Creatinine Level
Postoperative acute kidney injury requiring dialysis (AKI-D) occurs in 1 to 5% of patients after cardiac surgery with cardiopulmonary bypass (CPB) and is associated with a high mortality (30 to 60%) and prolonged increased ICU length of stay. There are four models using different covariates that aim to predict the risk for postoperative AKI-D in cardiac surgery patients [1–4]. We aim to investigate which model best predicts AKI and AKI-D in our cardiac surgery population.
AUC-ROC for four models for the prediction of AKI-D and AKI
AKI-D (95% CI)
AKI (95% CI)
0.80 (67 to 93)
0.65 (58 to 72)
0.95 (90 to 99)
0.77 (70 to 83)
0.81 (66 to 96)
0.74 (67 to 81)
0.93 (90 to 97)
0.73 (67 to 80)
A total of 966 patients were included in this study, of which 926 medical records were available for review. The procedures performed were coronary artery bypass grafting CABG (n = 733, 79%), single valve surgery (n = 79, 9%) or CABG and valve or other surgery (n = 114, 12%).
The median change in serum creatinine was +6% (IQR -24% to +17%) during the first 6 days after surgery. AKI developed in 32 (3.4%) and in 19 (2.0%) patients classified as Risk and Injury, respectively. AKI-D developed in 13 (1.7%) patients. Table 1 shows the AUC-ROC curve value for each model (P < 0.001 for all data) for the prediction of AKI and AKI-D.
The model of Thakar is the best predictor of AKI and AKI-D in our population.
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