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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.

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Presentation on theme: "Rate of Obstructive Coronary Disease in Elective Diagnostic Cath Manesh R. Patel, MD Assistant Professor of Medicine Director Cath Lab Research – Duke."— Presentation transcript:

1 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

2 Disclosures n Interventional cardiologist l Clinical Cardiovascular MRI and Vascular Ultrasound n Division of Cardiology l Majority of Revenue from cardiovascular imaging n Genzyme l Advisory Board n Chair of Writing Group for ACC/AHA Coronary Revascularization Appropriateness Criteria

3 The Challenge in Cardiology Practice

4 Patient Case - Mrs. M n 58 years old with DM n Lives independently l Shops, Cleans, works in bank n 7/08 seen by PCP l Occasional Chest “ache” with walking at grocery store l Cramping in calves n Referred to Duke Cardiology / Vascular Clinic for evaluation

5 What would you do? n How do you determine risk and identify disease? n What data do you need to determine if invasive angiography and subsequent coronary revascularization will improve here symptoms and/or longevity

6 Step 1 - How do you decide pre-test probability

7 Clinical Decision Making - Question 1 n Which is the best model to calculate pretest probability of CAD in this patient? n A. Framingham Risk Score n B. Diamond Forrester Score n C. TIMI UA/NSTEMI Score n D. GRACE Score

8 Decision Question 2 n Based on the Diamond-Forrester classification, the pretest probability of this patient having CAD is: A. Very Low B. Low C. Intermediate D. High

9 Stratifying patients with Chest pain Intermediate Probability = 10-90% ACC/AHA Chronic Stable Angina Guidelines

10 Question # 1 n 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?

11 Imaging Use n Non-invasive cardiac imaging has improved assessment of cardiac function, anatomy, and pathology.

12 Imaging Use n Medicare spending on imaging services more than doubled from 2000 through 2006 Source: GAO Analysis of Medicare Data, Report GAO-08-452. Dollars (billions)

13

14 How good are we at identifying obstructive CAD ? All ACC-NCDR patients who had cardiac catheterization 1,989,779 patients at 663 sites Exclude: Prior MI, PCI, CABG, Cardiac Transplant, Valve surgery 629,325 patients at 663 sites 1,148,405 patients at 663 sites Exclude: Emergent admission symptoms (AMI and ACS) and cardiogenic shock 397,954 patients at 663 sites Exclude: other diagnostic cath indications Rate of Obstructive CAD* 60.3% 36.2% 37.5% 51.7% January 2004-April 2008

15 Rate of Obstructive CAD n Obstructive CAD l ≥ 50% LM or ≥ 70% Epicardial Vessel l 38% l ≥ 50% Any vessel l 41% n Minimal CAD l < 20% stenosis in any vessel 39%entire cohort 39%entire cohort

16 Obstructive CAD Disease At Cath (NCDR data) n 397,954 patients 2004-2008 without known CAD/MI or prior PCI/CABG undergoing diagnostic cath to R/O CAD n 59% of patients with positive non-invasive tests have no obstructive CAD on invasive angiography (False positive)

17 Obstructive CAD over time

18 ACC-NCDR Study n Current risk stratification including non-invasive testing used to inform decisions to perform angiography to identify obstructive CAD need significant improvement


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