Objectives: The authors analyzed data from the NCDR (National Cardiovascular Data Registry) PVI Registry and defined acute kidney injury (AKI) as increased creatinine of ≥0.3 mg/dl or 50%, or a new requirement for dialysis after PVI. Background: AKI is an important and potentially modifiable complication of peripheral vascular intervention (PVI). The incidence, predictors, and outcomes of AKI after PVI are incompletely characterized. Methods: A hierarchical logistic regression risk model using pre-procedural characteristics associated with AKI was developed, followed by bootstrap validation. The model was validated with data submitted after model creation. An integer scoring system was developed to predict AKI after PVI. Results: Among 10,006 procedures, the average age of patients was 69 years, 58% were male, and 52% had diabetes. AKI occurred in 737 (7.4%) and was associated with increased in-hospital mortality (7.1% vs. 0.7%). Reduced glomerular filtration rate, hypertension, diabetes, prior heart failure, critical or acute limb ischemia, and pre-procedural hemoglobin were independently associated with AKI. The model to predict AKI showed good discrimination (optimism corrected c-statistic = 0.68) and calibration (corrected slope = 0.97, intercept of −0.07). The integer point system could be incorporated into a useful clinical tool because it discriminates risk for AKI with scores ≤4 and ≥12 corresponding to the lower and upper 20% of risk, respectively. Conclusions: AKI is not rare after PVI and is associated with in-hospital mortality. The NCDR PVI AKI risk model, including the integer scoring system, may prospectively estimate AKI risk and aid in deployment of strategies designed to reduce risk of AKI after PVI.
- acute kidney injury
- peripheral intervention
- risk model
ASJC Scopus subject areas
- Cardiology and Cardiovascular Medicine