Coronary Disease Morbidity and Mortality in a Population

  • Roger, Veronique Lee (CoPI)

Project: Research project

Project Details

Description

DESCRIPTION (provided by applicant): Coronary heart disease (CHD) is the leading cause of death and the decline in age-adjusted mortality reflects a shift in the occurrence of death towards older persons. Further, the staggering morbidity of cardiovascular disease will likely increase with the obesity and diabetes epidemics. The American Heart Association and Healthy People 2010 defined goals to improve cardiovascular health, which require population surveillance to assess progress. Our study responds to this need by measuring CHD events, evaluating their prognosis and management in a geographically-defined population. We demonstrated that the incidence of myocardial infarction (MI) remained stable over time while trends diverged by age and sex with an increase in women and the elderly. CHD mortality trends also showed a shift in the burden of CHD towards women and the elderly. Trends in MI incidence paralleled CHD incidence, supporting the conventional approach of relying on MI to assess CHD trends. The definition of MI was then changed to recommend troponin as the preferred biomarker. As troponin is more sensitive than previous biomarkers (creatine kinase and its MB fraction), it was hypothesized that the new definition would change the number and case mix of MI. To test this hypothesis, we amplified our passive surveillance with a novel prospective approach, measured both new and previous biomarkers in all cases in the same population and determined that the new criteria markedly increased the number of MIs but the increment varied according to the clinical acceptance of the new criteria. Importantly, the new definition obscured the boundaries between unstable angina (UA) and MI such that CHD surveillance must now pertain to acute coronary syndromes (ACS) including UA. The biomarker change also altered case mix and outcome. Finally, while troponin predicts risk in ACS, other markers also offer prognostic information. We showed that C-Reactive Protein (CRP) was associated with heart failure (HF) and death while lipoprotein- associated phospholipase A2 (Lp-PLA2), was associated with death but not HF or ischemia post MI. This underscores the challenges of a multimarker strategy for risk prediction as risk differs by time or type of event. Further, the added value of novel markers over known indicators should be evaluated. We propose in Aim 1, to examine the incidence and survival of ACS (MI and UA) to test the hypotheses that incidence of ACS remained stable, but the incidence of MI increased while that of UA decreased and that the survival of ACS improved while MIs had worse survival than UA cases. In Aim 2, to prospectively characterize case mix and test the hypothesis that cases meeting only troponin criteria have better outcomes than those meeting CKMB- criteria. In Aim 3: to test the hypothesis that novel biomarkers predict risk after ACS but that the associations vary according to the type of biomarker and event. We will assess the added value of biomarkers over that of known predictors. Our research is uniquely possible in this setting as it builds on the proven method and findings of previous grant cycles to integrate passive surveillance and prospective studies in the community. PUBLIC HEALTH RELEVANCE: This research will provide important information on the burden of heart disease in the community as measured by acute coronary syndromes, including unstable angina and myocardial infarction. It will determine the importance of novel biomarkers to predict the risk of adverse events in clinical practice.
StatusFinished
Effective start/end date1/15/985/31/14

Funding

  • National Heart, Lung, and Blood Institute: $366,612.00
  • National Heart, Lung, and Blood Institute: $417,696.00
  • National Heart, Lung, and Blood Institute: $423,107.00
  • National Heart, Lung, and Blood Institute: $379,620.00

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.