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Author Spotlight: A Pharmacodissection Approach to Uncover Mechanisms in Cardiovascular Disease Risk Populations
Published on: July 21, 2023
Overlaps of risk factors between different cardiovascular phenotypes
Christian-Alexander Behrendt1,2,3, Alena Haack1,4,5, Benjamin Bay1,2,4,5
1Center for Population Health Innovation (POINT), University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Insights
Atherosclerotic cardiovascular disease (ASCVD) subgroups show varying risk factors and medication rates. Tailoring treatments to specific vascular beds may improve outcomes for patients with ASCVD.
Area of Science:
- Cardiology
- Vascular Medicine
- Public Health
Background:
- Atherosclerotic cardiovascular disease (ASCVD) includes coronary, peripheral artery disease (PAD), carotid, and polyvascular disease.
- Limited data exists on ASCVD subgroup prevalence, risk factors, and secondary prevention medication rates.
- The Hamburg City Health Study (HCHS) provides population-based data for this investigation.
Purpose of the Study:
- To investigate the prevalence, risk factors, and secondary preventive medication rates across different ASCVD subgroups.
- To compare baseline characteristics, risk factor profiles, and cardiovascular risk scores among ASCVD patient groups.
- To identify potential targets for improving cardiovascular event rates in ASCVD patients.
Main Methods:
- Cross-sectional analysis of 10,000 randomly recruited HCHS participants (aged 45-74).
- Stratification of participants based on affected arterial vascular beds (carotid, PAD, coronary, polyvascular).
- Comparison of baseline characteristics, risk factors, prescribed medications, and cardiovascular risk scores (ESC SCORE 2, Stroke score).
Main Results:
- 6,324 individuals with complete data were analyzed.
- Prevalence: isolated carotid artery disease (35.7%), PAD (11.6%), coronary artery disease (2.8%), polyvascular disease (11.7%).
- Polyvascular disease patients were oldest, most likely unemployed, diabetic, and smokers. Coronary and polyvascular disease groups had highest risk scores and medication rates.
Conclusions:
- ASCVD subgroups exhibit distinct risk factor profiles, cardiovascular risk scores, and secondary preventive medication patterns.
- Findings highlight variations in optimal medical treatment strategies across different ASCVD manifestations.
- Targeted interventions based on vascular bed affected could enhance cardiovascular event reduction in ASCVD patients.
Abstract:
Background: Atherosclerotic cardiovascular disease (ASCVD) encompasses a diverse range of disease manifestations including coronary, lower extremity peripheral (PAD), carotid, or extensive (e.g., polyvascular) arterial disease. However, a paucity of data exists with regard to the prevalence, shared risk factors, and rate of prescribed secondary preventive medications in different ASCVD subgroups. We sought to investigate this from a population-based perspective using data derived from the contemporary Hamburg City Health Study (HCHS). Patients and methods: In the population-based HCHS participants between 45 and 74 years were recruited at random. In the current cross-sectional analysis of the first 10,000 participants enrolled between February 2016 and November 2018, participants were stratified by the arterial vascular bed affected by atherosclerosis, e.g., carotid artery disease, lower extremity PAD, or coronary artery disease, as well as a combination of at least two entities (polyvascular disease). Baseline characteristics including risk factor profiles, prescribed preventive medications as well as cardiovascular risk scores (ESC SCORE 2, Stroke score) were compared. Results: A total of 6,324 individuals with complete cardiovascular screening data were included. Overall, 2,258 (35.7%), 732 (11.6%) and 174 (2.8%) participants were diagnosed with isolated carotid artery disease, lower extremity PAD, or coronary artery disease, respectively. In 739 (11.7%) participants polyvascular disease was noted. Across the subgroups, different patterns of risk factor profiles were documented. Participants with polyvascular disease were the oldest, most often unemployed, diabetic, and current smokers. Individuals with coronary artery disease or polyvascular disease were noted to have the highest cardiovascular risk scores and highest rates of prescribed preventive medications. Conclusions: In this contemporary population-based analysis, different risk factor profiles, cardiovascular risk scores and prescribed secondary preventive medications were noted according to the diseased vascular bed. Our findings suggest differences between best medical treatment which could be targeted to improve cardiovascular event rates in patients with ASCVD.
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