The Year in Cardiology 2014: Prevention
The Year in Cardiology 2014: Prevention
In guidelines on CVD prevention it is a strong recommendation to adapt the intensity of intervention to the overall CV risk of the patient. In otherwise healthy individuals, CV risk estimation requires adequate algorithms. Different models have been developed over the past years; in Europe the SCORE model, based on 12 large European cohorts, is in widespread use. SCORE provides two risk charts, one for high-risk countries and another for low-risk countries. Vikhireva et al. tested the SCORE model in cohorts from the MONICA project and from the HAPIEE study in the Czech republic, Poland, Lithuania and Russia. The results show that one size does not fit all. The high-risk SCORE model underestimated the risk of a fatal CV event in the Russian MONICA centre but performed well in most other MONICA cohorts and in the Russian HAPIEE centre; however, it overestimated risk in the more contemporary Czech and Polish cohorts. So, once a model has been developed it will overestimate CV risk in a country where CV mortality has declined. Cardiovascular disease mortality is very dynamic; it changes rapidly over time as societies change lifestyles on the basis of socio-economic developments. In Figure 1, age-standardized CHD mortality rates are presented from 1970 to 2006 for men from Lithuania, the Russian Federation, Poland, Czech republic, former Czechoslovakia, Scandinavian-, Eastern European-, and Southern European countries; these time trends are more related to changes in lifestyle than to improvements in therapies.
(Enlarge Image)
Figure 1.
Age-standardized coronary heart disease mortality rates in men, aged <65 in different European countries and regions—WHO statistics; reprinted from Ref.
Several attempts have been made to improve risk estimation models; Ian Graham and MT Cooney elegantly summarized the vulnerability of the performance of all models.
In addition, numerous novel biomarkers have been proposed to improve existing risk estimation models but in only a few the incremental predictive value was of clinical importance. One could improve risk stratification at the population level by detecting subclinical atherosclerosis and identifying patients at high or very high CV risk; this has been proposed using the ankle brachial index which seems to carry incremental predictive value in people at intermediate CV risk.
The SCORE model also has the advantage that it can be re-calibrated using national statistics and this has already been undertaken in several European countries.
The Joint British Societies' consensus recommendations for the prevention of CVD (JBS3) has chosen QRISK lifetime as the basis for guiding preventive strategies. However, questions remain as to how this risk estimate was derived, validated, and presented.
One should use these models with caution especially in countries where the actual CV risk is different from that of the cohort from which the model was derived. This also indicates the need for new cohort studies in Europe that could be used to develop current and precise algorithms to estimate total CV risk at the level of the asymptomatic population.
The association between psychological symptoms such as anxiety and depression and CVD remains an intense subject of debate. Different mechanisms have been put forward to explain these associations. In a large population-based cohort of 57 953 Norwegians, followed for 11.4 years, self-reported symptoms of depression and anxiety were associated with an increased risk of an acute myocardial infarction (AMI). But further analyses suggest that this association partly reflects reverse causation and confounding by co-morbidities; in a review by Hare et al. depression was also a major determinant of quality of life in patients with CVD; in another systematic review of 53 studies on depression and adverse medical outcomes after an acute coronary syndrome consistent associations were found; so, it seems that the debate is not closed as of yet.
Environmental factors such as the exposure to excessive noise and to air pollution have been associated with CVD for many years but have gained little attention. More recently, better exposure measurements and increasing levels of exposure in certain areas of Europe have re-activated this interest.
In a population-based cohort study of 4814 participants in the German Heinz Nixdorf Recall study, exposure to air pollution and to road traffic noise were measured and related to thoracic aorta calcification; both exposures were independently associated with subclinical atherosclerosis. In the prospective Nurses' Health Study, roadway proximity was studied as a proxy for air pollution and for road traffic noise; it was associated with a significant increased risk of sudden cardiac death and of fatal coronary heart disease (CHD), even after controlling for other CV risk factors.
The CV consequences of excessive noise exposure were reviewed by Münzel et al. and it was concluded that noise contributes to the incidence of arterial hypertension and CVD. The relative risk of these exposures might be limited but the population attributable risk may be much larger when a large proportion of the population is exposed, such as certain social classes that are more exposed to noise at home and at work. Part of the large inequalities in CV health may be related to differences in exposure to these environmental factors.
Cardiovascular Risk Estimation and Epidemiological Studies of Novel Risk Markers
Estimation of Total Cardiovascular Risk
In guidelines on CVD prevention it is a strong recommendation to adapt the intensity of intervention to the overall CV risk of the patient. In otherwise healthy individuals, CV risk estimation requires adequate algorithms. Different models have been developed over the past years; in Europe the SCORE model, based on 12 large European cohorts, is in widespread use. SCORE provides two risk charts, one for high-risk countries and another for low-risk countries. Vikhireva et al. tested the SCORE model in cohorts from the MONICA project and from the HAPIEE study in the Czech republic, Poland, Lithuania and Russia. The results show that one size does not fit all. The high-risk SCORE model underestimated the risk of a fatal CV event in the Russian MONICA centre but performed well in most other MONICA cohorts and in the Russian HAPIEE centre; however, it overestimated risk in the more contemporary Czech and Polish cohorts. So, once a model has been developed it will overestimate CV risk in a country where CV mortality has declined. Cardiovascular disease mortality is very dynamic; it changes rapidly over time as societies change lifestyles on the basis of socio-economic developments. In Figure 1, age-standardized CHD mortality rates are presented from 1970 to 2006 for men from Lithuania, the Russian Federation, Poland, Czech republic, former Czechoslovakia, Scandinavian-, Eastern European-, and Southern European countries; these time trends are more related to changes in lifestyle than to improvements in therapies.
(Enlarge Image)
Figure 1.
Age-standardized coronary heart disease mortality rates in men, aged <65 in different European countries and regions—WHO statistics; reprinted from Ref.
Several attempts have been made to improve risk estimation models; Ian Graham and MT Cooney elegantly summarized the vulnerability of the performance of all models.
In addition, numerous novel biomarkers have been proposed to improve existing risk estimation models but in only a few the incremental predictive value was of clinical importance. One could improve risk stratification at the population level by detecting subclinical atherosclerosis and identifying patients at high or very high CV risk; this has been proposed using the ankle brachial index which seems to carry incremental predictive value in people at intermediate CV risk.
The SCORE model also has the advantage that it can be re-calibrated using national statistics and this has already been undertaken in several European countries.
The Joint British Societies' consensus recommendations for the prevention of CVD (JBS3) has chosen QRISK lifetime as the basis for guiding preventive strategies. However, questions remain as to how this risk estimate was derived, validated, and presented.
One should use these models with caution especially in countries where the actual CV risk is different from that of the cohort from which the model was derived. This also indicates the need for new cohort studies in Europe that could be used to develop current and precise algorithms to estimate total CV risk at the level of the asymptomatic population.
Psychological Symptoms and Cardiovascular Disease Risk
The association between psychological symptoms such as anxiety and depression and CVD remains an intense subject of debate. Different mechanisms have been put forward to explain these associations. In a large population-based cohort of 57 953 Norwegians, followed for 11.4 years, self-reported symptoms of depression and anxiety were associated with an increased risk of an acute myocardial infarction (AMI). But further analyses suggest that this association partly reflects reverse causation and confounding by co-morbidities; in a review by Hare et al. depression was also a major determinant of quality of life in patients with CVD; in another systematic review of 53 studies on depression and adverse medical outcomes after an acute coronary syndrome consistent associations were found; so, it seems that the debate is not closed as of yet.
Air Pollution, Noise, and Cardiovascular Disease Risk
Environmental factors such as the exposure to excessive noise and to air pollution have been associated with CVD for many years but have gained little attention. More recently, better exposure measurements and increasing levels of exposure in certain areas of Europe have re-activated this interest.
In a population-based cohort study of 4814 participants in the German Heinz Nixdorf Recall study, exposure to air pollution and to road traffic noise were measured and related to thoracic aorta calcification; both exposures were independently associated with subclinical atherosclerosis. In the prospective Nurses' Health Study, roadway proximity was studied as a proxy for air pollution and for road traffic noise; it was associated with a significant increased risk of sudden cardiac death and of fatal coronary heart disease (CHD), even after controlling for other CV risk factors.
The CV consequences of excessive noise exposure were reviewed by Münzel et al. and it was concluded that noise contributes to the incidence of arterial hypertension and CVD. The relative risk of these exposures might be limited but the population attributable risk may be much larger when a large proportion of the population is exposed, such as certain social classes that are more exposed to noise at home and at work. Part of the large inequalities in CV health may be related to differences in exposure to these environmental factors.
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