Verification of the SCORE model for cardiovascular death risk in the Warsaw population

• Autorzy: Walerian Piotrowski
• Języki publikacji: EN

Abstrakty

EN

The aim of this paper was to evaluate the 10 year old SCORE model for global risk of death from cardiovascular diseases using the parameters of the algorithm SCORE, establish the predictors and their importance in determining the incidence of death in the Warsaw population in the 34–54 year age group over a 10 year period and verify the SCORE algorithm for global ten year risk of death due to cardiovascular diseases in the Warsaw population. The research was based on individual data from the Warsaw study carried out in 1984, 1988 and 1993 with observation over a 10 year period from 3 screening visits in the Pol-MONICA programme. Death records included the cause of death, with special reference to incidents involving cardiovascular death. The analysis used were the Kaplan Meier life expectancy curves with the log rank test for comparison of the curves (group homogeneity) and the multifactorial Cox proportional hazards model. The measure of fit was defined as the sum of the independent differences in the percentage frequency of death in the risk quartiles of SCORE and the personal quartile index based on the Cox model. As a result of the analysis beneficial changes on the 10 year death risk due to cardiovascular diseases in the years 1984–1993 with a slower death rate observed for the population in further screenings. The level of total cholestrol is not a predictor of death due to vascular disease for the population of the right bank of the city of Warsaw. The SCORE algorythm differs by some 7–15% from the estimated death rate of the male Warsaw population in the age group 35–64 years. For women the difference in fit is less and is between 4–10% of cardiological death rate.

• Wydawca: Sciendo
• Czasopismo: Studies in Logic, Grammar and Rhetoric
• Rocznik: 2011
• Numer: 25(38)
• Strony: 99-108

Twórcy

autor

Walerian Piotrowski

• Institute of Cardiology, Warsaw