David M Safley1, Adam C Salisbury2, Thomas T Tsai3, Eric A Secemsky4, Kevin F Kennedy2, R Kevin Rogers5, Faisal Latif6, Nicolas W Shammas7, Lawrence Garcia8, Matthew A Cavender9, Kenneth Rosenfield10, Anand Prasad11, John A Spertus2. 1. Cardiology Department, Saint Luke's Mid America Heart Institute, Kansas City, Missouri, USA; Division of Cardiology, University of Missouri-Kansas City, Kansas City, Missouri, USA. Electronic address: dsafley@saint-lukes.org. 2. Cardiology Department, Saint Luke's Mid America Heart Institute, Kansas City, Missouri, USA; Division of Cardiology, University of Missouri-Kansas City, Kansas City, Missouri, USA. 3. Interventional Cardiology, Institute for Health Research, Kaiser Permanente Colorado, Denver, Colorado, USA. 4. Vascular Intervention, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA. 5. Vascular Medicine & Intervention, University of Colorado, Aurora, Colorado, USA. 6. Interventional Cardiology, University of Oklahoma & VA Medical Center, Oklahoma City, Oklahoma, USA. 7. Midwest Cardiovascular Research Foundation, Davenport, Iowa, USA. 8. Section of Interventional Cardiology, Tufts University School of Med, Boston, Massachusetts, USA. 9. Interventional Cardiology, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina, USA. 10. Interventional Cardiology, Massachusetts General Hospital, Boston, Massachusetts, USA. 11. Cardiovascular Disease, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.
Abstract
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.
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.
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