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American Heart Association November 18, 2013 Dallas, Texas

Factors influencing treatment decisions for coronary artery disease after cardiac catheterization. American Heart Association November 18, 2013 Dallas, Texas. Brian R. Englum, MD, Phillip Schulte, PhD, Brian Gulack, MD, Manesh R. Patel, MD, John H. Alexander, MD, MHS, Peter K. Smith, MD.

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American Heart Association November 18, 2013 Dallas, Texas

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  1. Factors influencing treatment decisions for coronary artery disease after cardiac catheterization American Heart Association November 18, 2013 Dallas, Texas Brian R. Englum, MD, Phillip Schulte, PhD, Brian Gulack, MD, Manesh R. Patel, MD, John H. Alexander, MD, MHS, Peter K. Smith, MD

  2. Disclosure information • Project funding • Duke University Medical Center • Conflict of interest to disclose • None

  3. Coronary Revascularization Trends in the United States, 2001-2008. JAMA. 2011;305(17):1769-1776.

  4. Coronary Revascularization Trends in the United States, 2001-2008. JAMA. 2011;305(17):1769-1776.

  5. Coronary Revascularization Trends in the United States, 2001-2008. JAMA. 2011;305(17):1769-1776.

  6. Previous studies – CAD revasc strategy • SYNTAX • PCI vs. CABG • FREEDOM • PCI vs. CABG in diabetics • COURAGE • PCI vs. Medical therapy in stable CAD • Observational studies • Differential benefit: diabetes, smoking, PAD, CHF

  7. Purpose • Describe trends in treatment strategy for CAD • Identify factors associated with treatment strategy • Revascularization vs. medical therapy • PCI vs. CABG • Evaluate changes in these factor with evolving PCI technology

  8. Methods – population • Study population • Duke Databank for Cardiovascular Disease • CAD: ≥ 1 diseased vessel (50% stenosis) by coronary angiography • No prior PCI or CABG • Study eras • Angioplasty: 1986-1995 • Bare metal stent: 1996-2003 • Drug-eluting stent: 2004-2012

  9. Methods – statistical analysis • Summarized annual rates and patient characteristics by treatment strategy • Developed a model of patient characteristics predicting treatment decision • Multivariable logistic regression model • Stepwise variable selection • Estimated interaction of each variable with era in overall model

  10. Results – revasc strategy over time

  11. Results – patient characteristics

  12. Results – cardiac disease

  13. Results – cardiac factors associated with revasc strategy

  14. Results – comorbidities associated with revasc strategy

  15. Limitations • Single institution data • Patient preferences • Provider reasoning • Anatomic details

  16. Conclusions • Temporal trends in treatment strategies demonstrate dramatic changes over time • Decisions in CAD dominated by cardiac factors • Comorbidities play a lesser role • Most factors influencing treatment decisions appear stable over time

  17. Factors associated with treatment decisions Revascularization vs. Medical therapy

  18. Factors associated with treatment decision CABG vs. PCI

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