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  • Title: Riskard 2005. New tools for prediction of cardiovascular disease risk derived from Italian population studies.
    Author: Menotti A, Lanti M, Agabiti-Rosei E, Carratelli L, Cavera G, Dormi A, Gaddi A, Mancini M, Motolese M, Muiesan ML, Muntoni S, Muntoni S, Notarbartolo A, Prati P, Remiddi S, Zanchetti A.
    Journal: Nutr Metab Cardiovasc Dis; 2005 Dec; 15(6):426-40. PubMed ID: 16314229.
    Abstract:
    BACKGROUND AND AIM: The need to update tools for the estimate of cardiovascular risk prompted the "Gruppo di Ricerca per la Stima del Rischio Cardiovascolare in Italia" to produce a new chart and new software called Riskard 2005. METHODS AND RESULTS: Data from 9 population studies in 8 Italian regions, for a grand total of 17,153 subjects (12,045 men and 5,108 women) aged 35-74 and for a total exposure of about 194,000 person/years were available. A chart for the estimate of cardiovascular risk (major coronary, cerebrovascular and peripheral artery disease events) in 10 years was produced for men and women aged 45-74 free from cardiovascular diseases. Risk factors employed in the estimate were sex, age (6 classes), systolic blood pressure (4 classes), serum cholesterol (5 classes), diabetes, and cigarette smoking (4 classes). Estimates were produced for absolute risk and for relative risk, the latter against levels expected in the general population that produced the risk functions. Software was produced for the separate estimate of major coronary, cerebrovascular and cardiovascular events (the latter made by coronary, cerebrovascular and peripheral artery disease of atherosclerotic origin) for follow-up at 5, 10 or 15 years, in men a women aged 35-74 years at entry and free from cardiovascular diseases. Risk factors employed here were sex, age, body mass index, mean physiological blood pressure, HDL cholesterol, non-HDL cholesterol, cigarette smoking, diabetes and heart rate. The output is based on several indicators: absolute risk, relative risk (as defined above), ideal risk (for a very favourable risk profile), biological age of risk, comparisons among the above indicators, the percent contribution of risk factors to the excess of estimated risk above the level of the ideal risk, and the description of trends in risk estimate in relation to repeated measurements. CONCLUSIONS: These tools represent progress compared to similar tools produced some years ago by the same Research Group.
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