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Challenges in Disease Prevention: A Clinical View

Discusses difficulties in prevention, distinction between risk factors and disease, and early detection of cardiovascular issues. Explores the pros and cons of early detection technologies. Reflects on the role of the private sector in healthcare innovations.

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Challenges in Disease Prevention: A Clinical View

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  1. Problems with Prevention:A Clinical Perspective Michel Accad, MD October 17, 2011 GABA Panel Discussion

  2.  Prevention is bound to be difficult

  3. Ann Intern Med 1961

  4. Commonly Identified RFs

  5. 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)

  6. Risk Factor ≠ Disease

  7. 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

  8. Risk Assessment:A Fluid Concept • Imperfect Quantitative Models • Doctor’s perspective • Patient’s perspective • Patient’s means

  9. Treating Populations:The Paradox of Prevention

  10. Risk Factors:Disease by fiat • Cut-off numbers “define” disease • Numbers selected by super-committees • Changing cut-off numbers creates millions of patients overnight

  11. Risk factors as disease… …doctors as weathermen?

  12. 118 CVD Risk Factors And counting…

  13. Risk factor as disease • The problem of the J-curve Bad outcome Risk factor

  14. Public Awareness Campaigns… (the answer is most certainly yes…)

  15. “It is not the healthy who need a doctor, but the sick.” Matthew 9:12

  16. A better approach? Dr. is everything OK? DO I HAVE LATENT CVD?

  17. Focus on the early detection • Atherosclerosis • Hypertensive Cardiovascular Disease

  18. Vascular elasticity • Endothelial function • Digital retinal scan • CIMT • Microalbumin • Cardiac stress markers (eg. BNP) • Vascular calcium • Others

  19. 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

  20. The conundrum for early detection technologies A role for the private sector?

  21. The good news for the people

  22. Thank you

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