Acute kidney injury (AKI) following peripheral vascular intervention (PVI) is not uncommon, and the AKI risk model may help clinicians estimate AKI risk and deploy strategies aimed at reducing risk of AKI after PVI, according to a study published Feb. 1 in JACC: Cardiovascular Interventions.

Using data from ACC's PVI Registry, operated in collaboration with the Society for Vascular Surgery Vascular Quality Initiative, David M. Safley, MD, FACC, et al., identified incidence and predictors of AKI following PVI using the Acute Kidney Injury Network criteria. The researchers developed and validated an AKI risk prediction model and a derivative simple integer-based risk model. Patients who underwent PVI between March 30, 2014, and June 30, 2017, were included in the derivation cohort. Patients undergoing PVI from July 1, 2017, to Dec. 31, 2018, were included in the validation cohort. The primary outcome was AKI, assessed as the difference between pre-procedural serum creatinine and peak creatinine level six to 24 hours after the procedure.

In a total of 10,006 procedures in the derivation cohort, the average age was 69.4 years and 58% of patients were male. At baseline, more than half of patients had diabetes (52.4%) and coronary artery disease (51.7%), while 90% had hypertension and 91% had hyperlipidemia. AKI occurred in 737 patients (7.4%), including Stage 1 AKI in 605 patients (6%), Stage 2 in 50 (0.5%) and Stage 3 in 82 (0.8%). Among patients with AKI, 41 (0.4%) had a new need for hemodialysis. AKI was associated with increased in-hospital mortality (7.1% vs. 0.7%). Variables independently associated with AKI included reduced glomerular filtration rate, hypertension, diabetes, prior heart failure, critical or acute limb ischemia, and pre-procedural hemoglobin.

The model to predict AKI showed good discrimination (optimism corrected c-statistic=0.68) and calibration (corrected slope=0.97, intercept of -0.07). In the validation cohort, the simple integer point system showed good discrimination of risk for AKI, with scores ≤4 and ≥12 corresponding to the lower and upper 20% of risk, respectively.

The AKI risk model "could serve as the basis for a practical clinical tool to improve the safety of PVI," but "knowing the risks of an individual patient is 1 step in a systematic approach to reducing AKI," according to the researchers. They note that AKI is "relatively common after PVI," concluding that this "clinical tool can be used to identify patients for preventative strategies to reduce the risk of AKI and should also foster further study focused on decreasing the incidence of AKI following PVI."

The risk "model facilitates clinical routine use, as all variables needed are usually available before the procedure," Sabine Steiner, MD, writes in an accompanying editorial comment. She notes that the "additive value of employing a risk score for AKI prevention compared with standard care has still to be elucidated," but that "recognizing the risk of individual patients in a standardized fashion could facilitate the implementation of a number of preventive measures, as well as support post-interventional strategies for AKI detection and handling."

Clinical Topics: Dyslipidemia, Heart Failure and Cardiomyopathies, Prevention, Vascular Medicine, Atherosclerotic Disease (CAD/PAD), Acute Heart Failure, Hypertension

Keywords: Creatinine, Coronary Artery Disease, Hospital Mortality, Hyperlipidemias, Glomerular Filtration Rate, Acute Kidney Injury, Renal Dialysis, Peripheral Vascular Diseases, Registries, National Cardiovascular Data Registries, Diabetes Mellitus, Heart Failure, Ischemia, Hypertension, Hemoglobins, Risk Factors, PVI Registry

< Back to Listings