A prospective observational study had found that, in asymptomatic persons, subclinical obstructive coronary is associated with a more than eight-fold elevated risk for myocardial infarction (MI).
Carried out by Andreas Fuchs (Georg-August-Universität Göttingen, Göttingen, Germany) and others, the research—published in the Annals of Internal Medicine—was founded on their understanding that coronary atherosclerosis can develop at an early age and remain latent for many years, and so set about defining the subclinical characteristics which are associated with the development of MI.
In order to assess coronary atherosclerosis and clinical outcome, the study authors employed computed tomography angiography (CTA) which they opined has been “established” in the last 20 years as a non-invasive test to diagnose and guide treatment strategies for patients presenting with symptoms indicative of ischaemic heart disease. This technology, the researchers state, provides a “unique opportunity” to safely evaluate the correlation between their variables.
Fuchs et al focused solely on The Copenhagen General Population Study (CGPS) in Denmark, identifying 9,533 asymptomatic patients aged 40 years or older without known ischaemic disease. Each potential participant was required to complete a questionnaire which included medical history, cardiovascular risk profile, chest pain symptoms, smoking habits and education-economic factors, and any prescribed medications. Additionally, body mass and hypertension metrics were also recorded in these patients.
Their primary end point was MI, while the authors outlined their secondary end point to be a composite of all-cause death and heart attack, as well as the frequency of clinically-driven revascularisation.
For a median of 3.5 years (range, 0.1 to 8.9 years), patients were followed and evaluated. Fuchs and colleagues identified 5,114 (54%) patients with no subclinical coronary atherosclerosis, 3,483 (36%) with nonobstructive disease, and 936 (10%) with obstructive disease.
During the follow-up period 193 participants died and 71 developed MI—the authors convey that risk of heart attack increased in persons with obstructive (adjusted relative risk, 9.19 (95% CI, 4.49 to 18.11) and extensive, 7.65 (CI, 3.53 to 16.57) disease. However, they convey that obstructive subclinical coronary atherosclerosis was associated with a more than eight-fold increased risk for MI, and the risk for either death or MI was increased two-fold in persons with extensive disease.
Drawing from their results, Fuchs and colleagues direct attention to an “[interesting]” outcome, explaining that obstructive disease in both proximal and distal coronary segments was associated an “elevated risk” for heart attack, which they say suggests that “obstruction per se and, to a lesser degree anatomical location, is an important feature of elevated risk”.
Concerning the limitations of their study, Fuchs et al point to the limited generalisability of their cohort having pulled participant data from the CGPS which concerns the Nordic European region, meaning “mostly white” participants were included. Moreover, they highlight that persons undergoing coronary CTA recorded in the CGPS tended to have fewer “cardiovascular risk factors, a higher education level, and higher income class”, adding to the limited applicability of their findings which should therefore be “interpreted accordingly”, the authors remark.
Reflecting on the contribution their research makes on the cotemporary natural history of coronary artery disease, Fuchs and colleagues comment that it will be of “substantial interest” in future studies to “assess the individual contributions of atherosclerotic morphologic characteristics of coronary calcification, extent, luminal obstruction, and segmental and total plaque burden, in addition to high-risk plaque features, including positive remodelling to overall cardiovascular risk”. Continuing, they conclude that research to come will, “importantly”, require the implementation of quantitative coronary CTA, including deep learning-based image analysis tools.
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