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Using Risk Models to Improve Patient Selection for High-Risk Vascular Surgery

Vascular surgeons frequently perform procedures aimed at limiting death, stroke, or amputation on patients who present with diseases such as aortic aneurysms, carotid atherosclerosis, and peripheral arterial occlusive disease. However, now more than ever surgeons must balance the potential benefits...

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Detalles Bibliográficos
Autor principal: Goodney, Philip P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3820539/
https://www.ncbi.nlm.nih.gov/pubmed/24278669
http://dx.doi.org/10.6064/2012/132370
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author Goodney, Philip P.
author_facet Goodney, Philip P.
author_sort Goodney, Philip P.
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description Vascular surgeons frequently perform procedures aimed at limiting death, stroke, or amputation on patients who present with diseases such as aortic aneurysms, carotid atherosclerosis, and peripheral arterial occlusive disease. However, now more than ever surgeons must balance the potential benefits associated with these interventions with the risks of physiologic insult for these elderly patients, who often have significant comorbidity burdens and the potential for costly complications. In this paper, we highlight how regional and national datasets can help surgeons identify which patients are most likely to benefit from vascular operations and which patients are most likely to suffer complications in the postoperative period. By using these guidelines to improve patient selection, our risk models can help patients, physicians, and policymakers improve the clinical effectiveness of surgical and endovascular treatments for vascular disease.
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spelling pubmed-38205392013-11-25 Using Risk Models to Improve Patient Selection for High-Risk Vascular Surgery Goodney, Philip P. Scientifica (Cairo) Review Article Vascular surgeons frequently perform procedures aimed at limiting death, stroke, or amputation on patients who present with diseases such as aortic aneurysms, carotid atherosclerosis, and peripheral arterial occlusive disease. However, now more than ever surgeons must balance the potential benefits associated with these interventions with the risks of physiologic insult for these elderly patients, who often have significant comorbidity burdens and the potential for costly complications. In this paper, we highlight how regional and national datasets can help surgeons identify which patients are most likely to benefit from vascular operations and which patients are most likely to suffer complications in the postoperative period. By using these guidelines to improve patient selection, our risk models can help patients, physicians, and policymakers improve the clinical effectiveness of surgical and endovascular treatments for vascular disease. Hindawi Publishing Corporation 2012 2012-12-13 /pmc/articles/PMC3820539/ /pubmed/24278669 http://dx.doi.org/10.6064/2012/132370 Text en Copyright © 2012 Philip P. Goodney. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Goodney, Philip P.
Using Risk Models to Improve Patient Selection for High-Risk Vascular Surgery
title Using Risk Models to Improve Patient Selection for High-Risk Vascular Surgery
title_full Using Risk Models to Improve Patient Selection for High-Risk Vascular Surgery
title_fullStr Using Risk Models to Improve Patient Selection for High-Risk Vascular Surgery
title_full_unstemmed Using Risk Models to Improve Patient Selection for High-Risk Vascular Surgery
title_short Using Risk Models to Improve Patient Selection for High-Risk Vascular Surgery
title_sort using risk models to improve patient selection for high-risk vascular surgery
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3820539/
https://www.ncbi.nlm.nih.gov/pubmed/24278669
http://dx.doi.org/10.6064/2012/132370
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