How to Use Heart Rate Changes to Improve Exercise Test Results

1. How to Use Heart Rate Changes to Improve Exercise Test Results V. Froelicher, MD Professor of Medicine Stanford University VA Palo Alto HCS

2. What are the Questions being asked regarding Coronary Disease and Exercise Testing • Does this patient have or not have Coronary Disease? • Is this patient going to experience a Cardiac Event? • Is an invasive intervention appropriate?

3. Why do we need more than ST depression? • Classic criteria of one mm ST depression has low sensitivity and hi specificity • Other more expensive modalities appear to have better discriminatory characteristics • Exercise ST depression has not been prognostic in all studies

4. Goal is convince you: • Functional capacity is the strongest predictor of prognosis and Heart rate recovery adds to it. • Maximal Heart rate is an important part of diagnostic scores • We should stop worshipping ST segments and cardiac cath for prognostic and diagnostic assessments.

6. Statistical Prediction Rules • Based on mathematical models or equations that can be simplified as scores • They increase accuracy by enhancing the odds that any decision will be correct (a reliable second opinion)

7. Clinical Scores • Predicting Outcomes • Follow up required (time, complete) • Endpoint Limitations (Death, CABG) • No Natural History • Predicting Angiographic Findings • Instant Epidemiology • Limitations of Angiography • Sub-ischemic Lesions cause events

8. Making any of these Five Mistakes Evaluating Diagnostic Tests can invalidate Scores & Stats • Limiting the population Challenge by choosing extremes • Failure to reduce Work up bias • Use of Heart rate targets • Inclusion of MI patients • Use of Surrogates

9. Making any of these Four Mistakes Evaluating Prognostic Tests can invalidate Scores & Stats • Limited Challenge and work up bias • Incomplete Follow up • Failure to Censor • Using Misleading Endpoints

10. Population Selection Critical!! • Consecutive patients presenting with the problem for evaluation • Limit work up bias • Avoid limited challenge

11. Duke Treadmill Score (uneven lines, the elderly?)

12. The HR Recovery Studies Hi-light problems with Prediction of Prognosis • Failure to remove patients with interventions results in prediction of outcome after application of standard therapies • Failure to use infarct-free survival or cardiovascular death as outcome negates development of strategies or scores for treatment of CAD • Does not allow for prediction of who should receive therapies or interventions

14. The ST/HR index studies highlight the problem of limited challenge • Comparison of the sickest to the most well exaggerates the discriminatory value • The well have high heart rates , the sick have low maximal HRs

16. Males Choose only one per group <40=low prob 40-60= intermediate probability >60=high probability

17. Comparison of Tests

18. Therefore scores, ST/HR index and Heart rate recovery should be part of every standard ECG Exercise test