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Rate of Obstructive Coronary Disease in Elective Diagnostic Cath. Manesh R. Patel, MD Assistant Professor of Medicine Director Cath Lab Research – Duke University Medical Center. Disclosures. Interventional cardiologist Clinical Cardiovascular MRI and Vascular Ultrasound
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Rate of Obstructive Coronary Disease in Elective Diagnostic Cath Manesh R. Patel, MD Assistant Professor of Medicine Director Cath Lab Research – Duke University Medical Center
Disclosures • Interventional cardiologist • Clinical Cardiovascular MRI and Vascular Ultrasound • Division of Cardiology • Majority of Revenue from cardiovascular imaging • Genzyme • Advisory Board • Chair of Writing Group for ACC/AHA Coronary Revascularization Appropriateness Criteria
Patient Case - Mrs. M • 58 years old with DM • Lives independently • Shops, Cleans, works in bank • 7/08 seen by PCP • Occasional Chest “ache” with walking at grocery store • Cramping in calves • Referred to Duke Cardiology / Vascular Clinic for evaluation
What would you do? • How do you determine risk and identify disease? • What data do you need to determine if invasive angiography and subsequent coronary revascularization will improve here symptoms and/or longevity
Clinical Decision Making - Question 1 • Which is the best model to calculate pretest probability of CAD in this patient? • A. Framingham Risk Score • B. Diamond Forrester Score • C. TIMI UA/NSTEMI Score • D. GRACE Score
Decision Question 2 • Based on the Diamond-Forrester classification, the pretest probability of this patient having CAD is: • Very Low • Low • Intermediate • High
Stratifying patients with Chest pain Intermediate Probability = 10-90% ACC/AHA Chronic Stable Angina Guidelines
Question # 1 • In patients with intermediate pre-test probability of coronary artery disease - what cardiovascular test should be done to diagnose and risk stratify for coronary artery disease?
Imaging Use • Non-invasive cardiac imaging has improved assessment of cardiac function, anatomy, and pathology.
Imaging Use • Medicare spending on imaging services more than doubled from 2000 through 2006 Dollars (billions) 13% annual growth Source: GAO Analysis of Medicare Data, Report GAO-08-452.
How good are we at identifying obstructive CAD? Rate of Obstructive CAD* All ACC-NCDR patients who had cardiac catheterization 1,989,779 patients at 663 sites 60.3% Exclude: Prior MI, PCI, CABG, Cardiac Transplant, Valve surgery 51.7% 1,148,405 patients at 663 sites Exclude: Emergent admission symptoms (AMI and ACS) and cardiogenic shock 36.2% 629,325 patients at 663 sites Exclude: other diagnostic cath indications 37.5% 397,954 patients at 663 sites January 2004-April 2008
Rate of Obstructive CAD • Obstructive CAD • ≥ 50% LM or ≥ 70% Epicardial Vessel • 38% • ≥ 50% Any vessel • 41% • Minimal CAD • < 20% stenosis in any vessel • 39%entire cohort
Obstructive CAD Disease At Cath (NCDR data) • 397,954 patients 2004-2008 without known CAD/MI or prior PCI/CABG undergoing diagnostic cath to R/O CAD • 59% of patients with positive non-invasive tests have no obstructive CAD on invasive angiography (False positive)
ACC-NCDR Study • Current risk stratification including non-invasive testing used to inform decisions to perform angiography to identify obstructive CAD need significant improvement