Contemporary Methods for Predicting Acute Kidney Injury After Coronary Intervention
Authors' conclusion
The updated NCDR AKI risk model further refines AKI prediction after PCI, facilitating enhanced clinical care, benchmarking, and quality improvement.
Study context
- Population
- All 2020 percutaneous coronary intervention (PCIs) in the National Cardiovascular Data Registry (NCDR) CathPCI Registry, excluding those on dialysis or lacking postprocedural creatinine
- Participants
- 455,806 PCI procedures
- Outcome
- AKI (absolute creatinine increase of 0.3 mg/dL or 50% increase from baseline) and AKI requiring dialysis; model calibration and discrimination
Methodological detailsregistry-based (NCDR CathPCI Registry), 70% derivation / 30% validation random split, logistic regression risk model, Bedside risk scores and threshold contrast doses created
- Registry-based (NCDR CathPCI Registry)
- 70% derivation / 30% validation random split
- Logistic regression risk model
- Bedside risk scores and threshold contrast doses created
Main finding
As reported in the abstract
- Incidence of acute kidney injury (AKI)
- 7.2%
- Incidence of new dialysis
- 0.7%
- Final AKI model variables
- 13
- C-statistic (validation cohort)
- 0.798
- Calibration intercept (validation cohort)
- −0.03
- Calibration slope (validation cohort)
- 0.97
Observational data: associations, not effects.
Original publication
Contemporary Methods for Predicting Acute Kidney Injury After Coronary Intervention. JACC Cardiovasc Interv. Published 25 September 2023. doi:10.
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