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.

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