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A thorough health history and physical assessment are essential for identifying cardiovascular disease (CVD) symptoms and distinguishing them from other health issues.
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Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
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Coronary Artery Disease (CAD): An Overview with Scientific InsightsCoronary Artery Disease (CAD), often referred to as C-A-D, is a prevalent blood vessel disorder classified under the broader category of atherosclerosis. Atherosclerosis is a pathological process characterized by the hardening and narrowing of arteries due to the accumulation of atherosclerotic plaques. These plaques are composed of cholesterol, fatty substances, inflammatory cells, calcium, and fibrin, reducing blood flow to...
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The Role of Visualization in Estimating Cardiovascular Disease Risk: Scoping Review.

Adrijana Svenšek1, Mateja Lorber1, Lucija Gosak1

  • 1Faculty of Health Sciences, University of Maribor, Maribor, Slovenia.

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|October 14, 2024
PubMed
Summary
This summary is machine-generated.

Visualization techniques are rarely integrated into cardiovascular disease (CVD) risk models, despite their potential to improve patient understanding and outcomes. Further research is needed to explore the effectiveness of digital health interventions for CVD risk management.

Keywords:
PRISMAcardiovascular disease preventionmobile phonerisk factorsvisual analyticsvisualization

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Area of Science:

  • Digital Health
  • Biomedicine
  • Bioinformatics

Background:

  • Managing chronic diseases and cardiovascular disease (CVD) risk presents significant challenges.
  • Health data visualization is crucial for patient understanding and behavior modification.
  • Digital health technologies can promote healthy lifestyles and aid in CVD risk estimation.

Purpose of the Study:

  • To review and present the most commonly used visualization techniques for estimating CVD risk.

Main Methods:

  • A scoping review was conducted following PRISMA-ScR guidelines.
  • Searches included PubMed, CINAHL Ultimate, MEDLINE, Web of Science, and Google Scholar.
  • Included English-language articles on digital health, mobile health, and decision support systems for CVD risk estimation.

Main Results:

  • Seventeen studies were included, utilizing diverse methodologies.
  • Commonly used risk factors included age, sex, blood pressure, smoking status, and diabetes.
  • Visual cues (59%), bar charts (29%), and graphs (24%) were the most frequent visualization techniques.

Conclusions:

  • Visualization is underutilized in CVD risk prognostic models, despite its benefits.
  • Technology-based interventions can enhance healthcare worker performance and patient compliance.
  • Evidence on the effectiveness of mobile health in improving CVD outcomes remains limited.