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Risk factors for atherosclerosis--can they be used to identify the patient with multisystem atherosclerosis?

A M Travers1, J M van Zyl, C J Nel

  • 1Department of Surgery, Universitas Hospital, Bloemfontein.

Insights

Identifying atherosclerosis risk factors aids in early detection and screening. Key indicators include family history, existing arterial disease, and elevated lipid levels, improving diagnostic accuracy.

Area of Science:

  • Cardiovascular Medicine
  • Medical Diagnostics
  • Public Health

Background:

  • Atherosclerosis risk factors are crucial for preventive care and identifying patients at high risk.
  • These factors also correlate with the presence of existing atherosclerosis, aiding in screening for additional disease in known arteriopaths.

Purpose of the Study:

  • To investigate the association between known risk factors and the presence of additional atherosclerotic disease in patients admitted with various atherosclerotic conditions.
  • To evaluate the predictive value of specific risk factors for concomitant atherosclerosis in different patient cohorts.

Main Methods:

  • Retrospective analysis of 471 patients admitted with symptoms of atherosclerosis.
  • Logistic regression was used to identify significant risk factors and calculate odds ratios.
  • Sensitivity and specificity were determined for predictive models based on identified risk factors.

Main Results:

  • In peripheral vascular disease patients, risk factors for coronary artery disease included family history of ischemic heart disease (OR=2.6), carotid artery disease (OR=1.9), and high triglycerides (P<0.04).
  • In carotid artery disease patients, risk factors for ischemic heart disease included peripheral vascular disease (OR=1.9) and high cholesterol (P<0.02).
  • In acute myocardial infarction/coronary artery bypass surgery patients, female gender (OR=2.9) and increased age (P<0.001) predicted additional atherosclerosis.

Conclusions:

  • Specific risk factor combinations can predict additional atherosclerotic disease in patients presenting with various forms of atherosclerosis.
  • Risk factor profiles vary depending on the primary atherosclerotic condition, necessitating tailored screening approaches.
  • Logistic regression models incorporating age demonstrated moderate sensitivity and high specificity for predicting additional atherosclerosis in certain patient groups.

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