Identifying and treating classic CV risk factors is important in patients with diabetes to reduce their CV risk. In this presentation, prof. Hobbs discusses the classic CV risk factors one by one.
Thomas Gaziano presents data on worldwide trends in CV mortality and CV risk factors. He gives a brief update on different programs on CVD prevention, both in high and low income countries.
A study of real-world data of 4 large European primary care databases demonstrates that NAFLD is not associated with increased risk of AMI and stroke, after correction for traditional risk factors.
In data of the Look AHEAD trial, the effects on CV risk factors of maintaining weight loss were compared with those of weight regain, in year 1 to 4 after a 1-year intensive lifestyle intervention.
Data of the Framingham Original and Offspring Cohorts show that parental smoking during childhood is associated with a higher AF risk, partly because offspring show higher propensity of smoking.
Large community-based study with repeated weight and height measurements shows that long-term obesity and change in BMI over time are more informative to assess AF risk than current weight.
ESC 2019 In community-based studies in Colombia and Malaysia, HOPE-4 achieved reduced CV risk, better treatment adherence and healthier behavior with an intervention that targeted previously identified barriers to care.
Data of US postmenopausal women with normal BMI show that trunk fat and higher leg fat have opposing associations with CVD risk, while total body fat was not significantly related to CVD risk.
ESC 2019 Data of the HOPE-4 and PURE studies confirm the impact of reducing common risk factors, and point at less acknowledged risk factors, such as home air pollution and educational level.
ESC 2019 The PURE study shows that in high-income countries, cancer accounts for more deaths than CVD, while in low-income countries CVD mortality is higher, although risk factors are lower there.
ESC 2019 Using genetic scores to assess lifelong exposure to LDL-c and SBP levels, suggests that relatively small differences in this exposure associated large proportional risk reductions.
The new, interactive online tool U-Prevent helps to translate trial data to information relevant to the individual patient: which treatment gives the greatest health benefits?