Atherosclerotic disease is a chronic disorder developing insidiously throughout the life and usually progressing to an advanced stage by the time symptoms occur. In order to realize cardiovascular (CV) prevention, the detection of asymptomatic but diseased patients is crucial for an early intervention, since in these subjects there are opportunities to alter the progression of disease and the outcome (1). However, the simply analysis of risk factors don’t permits to identify always these subjects since it doesn’t informs about the effect that risk factors (RF) had already provoked and may more provoke on the individual vasculature. Besides, the risk factors known predict can explain only the 90 percent of cardiovascular disease (CVD) and traditional algorithms for prediction of CV risk failed to predict a proportion of cardiovascular events (CVE), realizing a “risk factors prediction gap” (2). It may be explained by several reasons: the epidemiology-derived models, based on the prediction of long-term risk, may not accurately predict short-term events, they don’t take into consideration emerging and novel risk factors; risk algorithms don’t identify, among patients with neither a previous history of CVD nor an high risk for atherosclerotic disease, those who will develop acute myocardial infarction and/or sudden coronary death as first CVD manifestation, and this may be due to the fact that the factors responsible of plaque formation and growth are not necessarily the same responsible of its instability and rupture, being the latter related to inflammation, thrombosis and plaque morphology (3).So, a possible approach to evaluate the individual global cardiovascular risk with more accurateness is to identify risk factors combination that more easily produces vascular damage, or alternatively, to evaluate directly the arterial wall and its damage degree. The former approach is performed by the evaluation of metabolic syndrome, the latter by the non-invasive study of pre-ATS markers.

Preclinical atherosclerosis, metabolic syndrome and risk of cardiovascular events

PEDRINELLI, ROBERTO
2014-01-01

Abstract

Atherosclerotic disease is a chronic disorder developing insidiously throughout the life and usually progressing to an advanced stage by the time symptoms occur. In order to realize cardiovascular (CV) prevention, the detection of asymptomatic but diseased patients is crucial for an early intervention, since in these subjects there are opportunities to alter the progression of disease and the outcome (1). However, the simply analysis of risk factors don’t permits to identify always these subjects since it doesn’t informs about the effect that risk factors (RF) had already provoked and may more provoke on the individual vasculature. Besides, the risk factors known predict can explain only the 90 percent of cardiovascular disease (CVD) and traditional algorithms for prediction of CV risk failed to predict a proportion of cardiovascular events (CVE), realizing a “risk factors prediction gap” (2). It may be explained by several reasons: the epidemiology-derived models, based on the prediction of long-term risk, may not accurately predict short-term events, they don’t take into consideration emerging and novel risk factors; risk algorithms don’t identify, among patients with neither a previous history of CVD nor an high risk for atherosclerotic disease, those who will develop acute myocardial infarction and/or sudden coronary death as first CVD manifestation, and this may be due to the fact that the factors responsible of plaque formation and growth are not necessarily the same responsible of its instability and rupture, being the latter related to inflammation, thrombosis and plaque morphology (3).So, a possible approach to evaluate the individual global cardiovascular risk with more accurateness is to identify risk factors combination that more easily produces vascular damage, or alternatively, to evaluate directly the arterial wall and its damage degree. The former approach is performed by the evaluation of metabolic syndrome, the latter by the non-invasive study of pre-ATS markers.
2014
Novo, S; Graceffa, A; Cameli, M; Ciccone, Mm; Maiello, M; Modesti, Pa; Muiesan, Ml; Muratori, I; Novo, G; Palmiero, P; Peritore, A; Saba, Ps; Scicchitano, P; Trovato, R; Pedrinelli, Roberto
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/500869
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