TY - JOUR
T1 - Acute Kidney Injury Following In-Patient Lower Extremity Vascular Intervention
T2 - From the National Cardiovascular Data Registry
AU - Safley, David M.
AU - Salisbury, Adam C.
AU - Tsai, Thomas T.
AU - Secemsky, Eric A.
AU - Kennedy, Kevin F.
AU - Rogers, R. Kevin
AU - Latif, Faisal
AU - Shammas, Nicolas W.
AU - Garcia, Lawrence
AU - Cavender, Matthew A.
AU - Rosenfield, Kenneth
AU - Prasad, Anand
AU - Spertus, John A.
N1 - Funding Information:
This study was funded by a grant from the National Cardiovascular Data Registry. Dr. Latif has received honoraria from Abbott Vascular, Inc. Dr. Shammas has received research and educational grants from Boston Scientific, Bard, VentureMed Group, Phillips, and Intact Vascular; and has served on speaker bureaus for Janssen, Novartis, Boehringer Ingelheim, and Zoll Medical. Dr. Spertus has been the principal investigator of a contract from the American College of Cardiology Foundation to analyze the NCDR data; and has an equity interest in Health Outcomes Sciences. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
Publisher Copyright:
© 2021 American College of Cardiology Foundation
PY - 2021/2/8
Y1 - 2021/2/8
N2 - 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.
AB - 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.
KW - acute kidney injury
KW - peripheral intervention
KW - risk model
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U2 - 10.1016/j.jcin.2020.10.028
DO - 10.1016/j.jcin.2020.10.028
M3 - Article
C2 - 33541543
AN - SCOPUS:85099659425
VL - 14
SP - 333
EP - 341
JO - JACC. Cardiovascular interventions
JF - JACC. Cardiovascular interventions
SN - 1936-8798
IS - 3
ER -