Cardiothoracic & vascular anaesthesia
A Preoperative Prediction Model for Acute Kidney Injury After Off-Pump Coronary Artery Bypass Grafting
Authors' conclusion
We developed a preoperative AKI prediction model based solely on 7 simple variables, which demonstrated good performance comparable to models incorporating postoperative factors and was also applicable to RRT prediction.
Study context
- Population
- Off-pump coronary artery bypass (OPCAB) patients at 2 university hospitals and 10 tertiary care centres
- Participants
- 1,640 participants
- Comparison
- Preoperative vs postoperative acute kidney injury (AKI) prediction model
- Outcome
- AKI after OPCAB (model discrimination, calibration, net benefit)
Methodological detailsmulticentre
- Multicentre
Performance
As reported in the abstract
AKI prediction
| Test or model | AUC |
|---|---|
| Preoperative model | 0.715 |
| Postoperative model | 0.753 |
AUC
Preoperative model0.715
Postoperative model0.753
- Preoperative model vs Postoperative model: P < 0.001
- AKI incidence
- 290 patients (17.7%)
Further findings
| Outcome | Preoperative model | Postoperative model | P value |
|---|---|---|---|
| RRT prediction | P = 0.441 | ||
| AUC | 0.776 | 0.800 |
- Renal replacement therapy (RRT) prediction — RRT required
- 33 patients (2.0%)
Original publication
A Preoperative Prediction Model for Acute Kidney Injury After Off-Pump Coronary Artery Bypass Grafting. J Cardiothorac Vasc Anesth. Published 16 September 2026. doi:10.
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