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Analysis of Risk Factors in Patients with Subclinical Atherosclerosis and Increased Cardiovascular Risk Using Factor

Zuzana Pella1, Dominik Pella2,3, Ján Paralič1

  • 1Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, 040 01 Košice, Slovakia.

Diagnostics (Basel, Switzerland)
|August 7, 2021
PubMed

Insights

Factor analysis identified six key factors for cardiovascular disease (CVD) risk, including patient characteristics, renal and lifestyle factors, and medical history. This improves understanding for personalized cardiovascular medicine.

Area of Science:

  • Cardiology
  • Medical Informatics
  • Biostatistics

Background:

  • Current cardiovascular disease (CVD) risk quantification methods often lack accuracy.
  • Personalized medicine offers a path to improved CVD diagnostics and treatment.
  • Understanding complex interrelationships among CVD risk factors is crucial.

Purpose of the Study:

  • To apply factor analysis to identify significant risk factors for cardiovascular disease.
  • To explore connections between numerous risk factors in hospitalized patients.
  • To refine cardiovascular risk assessment through data-driven insights.

Main Methods:

  • Factor analysis was employed on data from 808 patients at the East Slovak Institute of Cardiovascular Diseases.
  • Data included symptomatic and coronarography characteristics.
  • Clustering techniques were used to group identified factors.

Main Results:

  • Six significant factors were identified: patient demographics, renal parameters/fibrinogen, family history of CVD, personal CVD history, lifestyle, and echocardiogram/ECG results.
  • Factor analysis confirmed established CVD risk factors.
  • The study identified key clusters of interrelated risk indicators.

Conclusions:

  • The identified factors provide a more nuanced understanding of cardiovascular risk.
  • These findings support the advancement of personalized medicine in cardiology.
  • Further research into explanatory methods for CVD risk factors is warranted.

Keywords:
cardiovascular diseasesfactor analysisrisk factors

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