Defining risks and predicting adverse events after lower extremity bypass for critical limb ischemia

Abstract

Successful treatment of patients with critical limb ischemia (CLI), hinges on the adequacy of revascularization. However, CLI is associated with a severe burden of systemic atherosclerosis, and patients often suffer from multiple cardiovascular comorbidities. Therefore, CLI patients in general represent a cohort at increased risk for procedural complications and adverse events. Although endovascular therapy represents a minimally invasive alternative to open surgical bypass, the durability of surgical reconstruction is superior, and it remains the “gold standard” approach to revascularization in CLI. Therefore, selection of the optimal treatment modality for individual patients requires careful consideration of the procedural risks and likelihood of adverse events associated with surgery. Individualized decision-making with regard to revascularization strategy requires a comprehensive understanding of the likelihood of adverse outcomes after major surgery. Here we review the risks of surgical bypass in patients with CLI, with particular emphasis on the identification of preoperative variables that predict poor outcome.

Infrainguinal open reconstruction: a review of surgical considerations and expected outcomes

“…As prosthetic grafts are susceptible to infection, autologous conduits for infrainguinal bypass or endovascular revascularization are recommended in high-risk patients 51. Although graft infections may not increase postoperative mortality, they often contribute to lower limb amputation and may require removal or attempts at rescue with vacuum-assisted devices and rotational muscle flaps 52–55…”

“… 51 Although graft infections may not increase postoperative mortality, they often contribute to lower limb amputation and may require removal or attempts at rescue with vacuum-assisted devices and rotational muscle flaps. 52 – 55 …”

Using Machine Learning (XGBoost) to Predict Outcomes following Infrainguinal Bypass for Peripheral Artery Disease

“…Bonde et al 11 built ML algorithms using a cohort of NSQIP patients undergoing over 2900 distinct procedures to predict perioperative complications, achieving AUROCs of 0.85 to 0.88. Given that patients undergoing infrainguinal bypass represent a unique population with a high number of vascular comorbidities, the applicability of general surgical risk prediction tools may be limited 28 . By developing ML algorithms specific to patients undergoing infrainguinal bypass, we achieved AUROCs >0.90.…”