BACKGROUND: As cardiovascular disease (CVD) is one of the most common causes of mortality worldwide, much interest has been focused on reliable methods to predict cardiovascular risk. DESIGN: A cross-sectional, population-based screening study with 17-year follow-up in Southern Sweden. METHODS: We compared a non-laboratory, consultation-based risk assessment method comprising age, sex, present smoking, prevalent diabetes or hypertension at baseline, blood pressure (systolic > or =140 or diastolic > or =90), waist/height ratio and family history of CVD to Systemic COronary Risk Evaluation (SCORE) and a third model including several laboratory analyses, respectively, in predicting CVD risk. The study included clinical baseline data on 689 participants aged 40-59 years without CVD. Blood samples were analyzed for blood glucose, serum lipids, insulin, insulin-like growth factor-I, insulin-like growth factor binding protein-1, C-reactive protein, asymmetric dimethyl arginine and symmetric dimethyl arginine. During 17 years, the incidence of total CVD (first event) and death was registered. RESULTS: A non-laboratory-based risk assessment model, including variables easily obtained during one consultation visit to a general practitioner, predicted cardiovascular events as accurately [hazard ratio (HR): 2.72; 95% confidence interval (CI): 2.18-3.39, P<0.001] as the established SCORE algorithm (HR: 2.73; 95% CI: 2.10-3.55, P<0.001), which requires laboratory testing. Furthermore, adding a combination of sophisticated laboratory measurements covering lipids, inflammation and endothelial dysfunction, did not confer any additional value to the prediction of CVD risk (HR: 2.72; 95% CI: 2.19-3.37, P<0.001). The c-statistics for the consultation model (0.794; 95% CI: 0.762-0.823) was not significantly different from SCORE (0.767; 95% CI: 0.733-0.798, P=0.12) or the extended model (0.806; 95% CI: 0.774-0.835, P=0.55). CONCLUSION: A risk algorithm based on non-laboratory data from a single primary care consultation predicted long-term cardiovascular risk as accurately as either SCORE or an elaborate laboratory-based method in a defined middle-aged population.
BACKGROUND: As cardiovascular disease (CVD) is one of the most common causes of mortality worldwide, much interest has been focused on reliable methods to predict cardiovascular risk. DESIGN: A cross-sectional, population-based screening study with 17-year follow-up in Southern Sweden. METHODS: We compared a non-laboratory, consultation-based risk assessment method comprising age, sex, present smoking, prevalent diabetes or hypertension at baseline, blood pressure (systolic > or =140 or diastolic > or =90), waist/height ratio and family history of CVD to Systemic COronary Risk Evaluation (SCORE) and a third model including several laboratory analyses, respectively, in predicting CVD risk. The study included clinical baseline data on 689 participants aged 40-59 years without CVD. Blood samples were analyzed for blood glucose, serum lipids, insulin, insulin-like growth factor-I, insulin-like growth factor binding protein-1, C-reactive protein, asymmetric dimethyl arginine and symmetric dimethyl arginine. During 17 years, the incidence of total CVD (first event) and death was registered. RESULTS: A non-laboratory-based risk assessment model, including variables easily obtained during one consultation visit to a general practitioner, predicted cardiovascular events as accurately [hazard ratio (HR): 2.72; 95% confidence interval (CI): 2.18-3.39, P<0.001] as the established SCORE algorithm (HR: 2.73; 95% CI: 2.10-3.55, P<0.001), which requires laboratory testing. Furthermore, adding a combination of sophisticated laboratory measurements covering lipids, inflammation and endothelial dysfunction, did not confer any additional value to the prediction of CVD risk (HR: 2.72; 95% CI: 2.19-3.37, P<0.001). The c-statistics for the consultation model (0.794; 95% CI: 0.762-0.823) was not significantly different from SCORE (0.767; 95% CI: 0.733-0.798, P=0.12) or the extended model (0.806; 95% CI: 0.774-0.835, P=0.55). CONCLUSION: A risk algorithm based on non-laboratory data from a single primary care consultation predicted long-term cardiovascular risk as accurately as either SCORE or an elaborate laboratory-based method in a defined middle-aged population.
Authors: Mei Yong; Michael Nasterlack; Christina Germann; Stefan Lang; Christoph Oberlinner Journal: Int Arch Occup Environ Health Date: 2013-12-03 Impact factor: 3.015
Authors: Jacob K Kariuki; Eileen M Stuart-Shor; Suzanne G Leveille; Laura L Hayman Journal: BMC Cardiovasc Disord Date: 2013-12-28 Impact factor: 2.298