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Cardiovascular Prevention: Migrating From a Binary to a Ternary Classification

Migrating from a binary approach to risk assessment to a ternary model of disease identification allows for individualized, optimal disease management. Redefining the disease/inflammatory approach has been proven to identify, stabilize, and regress atherosclerosis while adding understanding to the p...

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Detalles Bibliográficos
Autores principales: Doneen, Amy Lynn, Bale, Bradley Field, Vigerust, David John, Leimgruber, Pierre P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7256212/
https://www.ncbi.nlm.nih.gov/pubmed/32528979
http://dx.doi.org/10.3389/fcvm.2020.00092
Descripción
Sumario:Migrating from a binary approach to risk assessment to a ternary model of disease identification allows for individualized, optimal disease management. Redefining the disease/inflammatory approach has been proven to identify, stabilize, and regress atherosclerosis while adding understanding to the progression of vascular disease. Our previously published results show the beneficial effect of comprehensive, evidence-based management on subclinical atherosclerosis and vulnerable plaque. We argue that this approach does not mitigate the value of utilizing standard risk factor identification, but rather augments it for the benefit of the individual patient.