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Predicting Amputation using Local Circulating Mononuclear Progenitor Cells in Angioplasty-treated Patients with Critical Limb Ischemia
Published on: September 22, 2020
The need for improved risk stratification in chronic critical limb ischemia
Jayer Chung1, J Gregory Modrall1, R James Valentine1
1Division of Vascular and Endovascular Surgery, Department of Surgery The University of Texas Southwestern Medical Center, Dallas, Tex.
Abstract:
Vascular surgeons are well acquainted with chronic critical limb ischemia (CLI), the most severe manifestation of peripheral arterial disease, with patients presenting with ischemic rest pain or ulcerations, or both. Epidemiologic data predict a burgeoning epidemic of CLI within the United States, commensurate with the increasing incidence and prevalence of atherosclerotic risk factors, especially age and diabetes. Untreated, the risk of major amputation (above the ankle) or death, or both, ranges between 20% and 40% at 1 year. Current open and endovascular therapies have imperfect results, diverse treatment options, and recommendations that are often conflicting and confuse physicians, industry, and patients alike. The best treatment options are ideally evaluated by prospective, randomized controlled trials. However, these have proven impractical in CLI because the rapid evolution of devices and techniques has outstripped the ability to measure outcomes and compare treatment options. Alternatively, risk-stratifying models have been proposed to allow physicians, patients, and industry to objectively evaluate new therapeutics and devices as they evolve. These models are developed from prospective cohorts to identify and quantify variables that can subsequently predict outcome in individual patients. The risk stratification models can also compare CLI outcomes between physicians and institutions, supporting quality assessments, and compensation decisions within Accountable Care Organizations under the Affordable Health Care Act (ACA). Widespread adoption of risk-stratification schemes has yet to occur, despite the critical need for such a tool in CLI, because present models lack optimal predictive ability and generalizability. The passage of the ACA amplifies the importance of developing an improved risk-stratification tool to ensure equitable quality assessments and compensation. This review presents current risk-stratification models for CLI with a summary of the respective strengths and limitations of each. Future research is needed to simplify and improve the accuracy and generalizability of risk stratification in CLI.
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