Factors Associated with Amputation after Peripheral Vascular Intervention for Intermittent Claudication

Abstract Background The natural history of intermittent claudication (IC) is that only 25% of patients will experience worsening of their claudication symptoms and only ∼1-3% will progress to major amputation. The impact of increasing use of endovascular therapies on the natural history of IC has not been well established. The purpose of this study is to evaluate the incidence and identify predictors of major and minor amputation following peripheral vascular intervention (PVI) for IC. Methods A retrospective cohort of patients treated for IC was derived from the national PVI Vascular Quality Initiative database evaluating both preoperative and intraoperative variables from 2003 to 2017. We examined rates of major or minor amputations following ipsilateral PVI for IC. Multivariable logistic regression models were created to identify predictors of amputation along with Kaplan-Meier plots to estimate amputation free survival. Results We identified 11,887 PVI procedures for patients undergoing elective treatment for IC without a previous history of lower extremity PVI or bypass. Major and minor amputations occurred at a combined rate of 1.08% (n=128). Minor amputations occurred in 0.56% (n=67) of patients at one year while major amputations were reported in 0.51% (n=61) of cases. Kaplan-Meier plots of amputation free survival revealed that patients with preoperative ABIs 1.3) had significantly higher rates of any amputation compared to subjects with ABIs between 0.20-0.49, 0.50-0.89 and 0.90-1.30 (log rank Conclusion With relation to amputation, the natural history of IC does not appear to be impacted by PVI Sicker patients with higher ASA or symptomatic CHF, and those with isolated tibial interventions are at higher risk for amputation, and we cannot determine if this is due to patient substrate, presentation or the intervention itself. Importantly, there are key prognostic preoperative and intraoperative indicators that can assist the clinician with predicting patients who are at a higher risk of amputation.