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This article explores the complexities of disease prevention from a clinical standpoint, emphasizing the differences between risk factors and disease. The work discusses the fluid nature of risk assessment, highlighting how arbitrary cut-off numbers can suddenly redefine millions as patients. It critically analyzes the paradox of prevention, the role of public awareness campaigns, and the importance of early detection methods in cardiovascular health. By focusing on a patient-centered approach, the piece argues for better strategies in addressing hidden cardiovascular disease and enhancing overall well-being.
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Problems with Prevention:A Clinical Perspective Michel Accad, MD October 17, 2011 GABA Panel Discussion
Disease Risk Factor Compatible with well-being over a wide range of values Continuum of risk Risk is target for therapy (risk reduction) Statistical • Symptoms • Sharp demarcation from normal • Disease is target for therapy • Deterministic (present or not)
Risk Factor ≠ Disease
T H ED I S T I N C T I O NB E T W E E NR I S K F A C T O RA ND D I S E A S EH A SB E E NB L U R R E D
Risk Assessment:A Fluid Concept • Imperfect Quantitative Models • Doctor’s perspective • Patient’s perspective • Patient’s means
Risk Factors:Disease by fiat • Cut-off numbers “define” disease • Numbers selected by super-committees • Changing cut-off numbers creates millions of patients overnight
Risk factors as disease… …doctors as weathermen?
118 CVD Risk Factors And counting…
Risk factor as disease • The problem of the J-curve Bad outcome Risk factor
Public Awareness Campaigns… (the answer is most certainly yes…)
“It is not the healthy who need a doctor, but the sick.” Matthew 9:12
A better approach? Dr. is everything OK? DO I HAVE LATENT CVD?
Focus on the early detection • Atherosclerosis • Hypertensive Cardiovascular Disease
Vascular elasticity • Endothelial function • Digital retinal scan • CIMT • Microalbumin • Cardiac stress markers (eg. BNP) • Vascular calcium • Others
Early detection approach PROS CONS Does not avoid problem of prediction Must distinguish disease patterns from age-related changes in the vasculature More expensive Not “validated” • Focused on the individual • Not a statistical assessment • Can be monitored in response to intervention • May identify patients without risk factors who have CVD • Facilitates dialogue regarding future risk
The conundrum for early detection technologies A role for the private sector?