Journal of Nuclear Cardiology

, Volume 13, Issue 6, pp 768–778 | Cite as

Predicting therapeutic benefit from myocardial revascularization procedures: Are measurements of both resting left ventricular ejection fraction and stress-induced myocardial ischemia necessary?

  • Rory Hachamovitch
  • Alan Rozanski
  • Sean W. Hayes
  • Louise E. J. Thomson
  • Guido Germano
  • John D. Friedman
  • Ishac Cohen
  • Daniel S. BermanEmail author



We hypothesized that ejection fraction (EF) best predicts cardiovascular death but only measures of ischemia predict relative survival benefit from revascularization compared with medical therapy.

Methods and Result

We followed up 5366 consecutive patients without prior revascularization who underwent stress electrocardiography-gated myocardial perfusion single photon emission computed tomography (MPS) for 2.8 ± 1.2 years, during which 146 cardiac deaths occurred (2.7%, 1.0%/y). The treatment received within 60 days after MPS was used to define the subgroups (revascularization in 402 patients, with cardiac death occurring in 6.2%, vs medical therapy in 4964 patients, with cardiac death occurring in 2.4%; P < .0001, χ2 = 18.7). Adjustment for nonrandomized treatment assignment used a propensity score based on logistic regression modeling of referral to revascularization. The percent of myocardium that was ischemic was the most important predictor of revascularization. The overall model (multivariate χ2 = 728, c index = 0.89, P < 10-5) was used as a propensity score. Cox proportional hazards analysis, assessing the relationship between MPS results, non-MPS covariates, and cardiac death, revealed that EF was superior to percent ischemic myocardium in the prediction of cardiac death after adjustment for pre-MPS data and the propensity score. However, an interaction between percent ischemic myocardium and revascularization was present such that, irrespective of EF, patients with little or no ischemia had an improved survival rate with medical therapy, whereas with increasing ischemia, progressive improvements in survival rate were noted with revascularization.


Although EF predicts cardiac death, only inducible ischemia identifies which patients have a short-term benefit from revascularization.

Key Words

Technetium 99m sestamibi single photon emission computed tomography myocardial perfusion prognosis outcomes 


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  1. 1.
    Gibbons RJ, Chatterjee K, Daley J, Douglas JS, Fihn SD, Gardin JM, et al. ACC/AHA/ACP-ASIM guidelines for the management of patients with chronic stable angina: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on Management of Patients With Chronic Stable Angina). J Am Coll Cardiol 1999;33:2092–197.PubMedCrossRefGoogle Scholar
  2. 2.
    Berman DS, Hachamovitch R, Shaw LJ, Germano G, Hayes S. Nuclear cardiology. In: Fuster V, Alexander R, King S, O’Rourke RA, Wellens HJJ, editors. Hurst’s the heart. New York: McGraw-Hill; 2004. p. 525–65.Google Scholar
  3. 3.
    Hachamovitch R, Hayes SW, Friedman JD, Cohen I, Berman DS. Identification of a threshold of inducible ischemia associated with a short-term survival benefit with revascularization compared to medical therapy in patients with no prior CAD undergoing stress myocardial perfusion SPECT. Circulation 2003;107:2899–906.CrossRefGoogle Scholar
  4. 4.
    Weiner DA, Ryan TJ, Parsons L, Fisher LD, Chaitman BR, Sheffield LT, et al. Long-term prognostic value of exercise testing in men and women from the Coronary Artery Surgery Study (CASS) registry. Am J Cardiol 1995;75:865–70.PubMedCrossRefGoogle Scholar
  5. 5.
    Weiner DA, Ryan TJ, McCabe CH, Chaitman BR, Sheffield LT, Fisher LD, et al. The role of exercise testing in identifying patients with improved survival after coronary artery bypass surgery. J Am Coll Cardiol 1986;8:741–8.PubMedGoogle Scholar
  6. 6.
    Berman DS, Kiat H, Friedman JD, Wang FP, van Train K, Matzer L, et al. Separate acquisition rest thallium-201/stress technetium-99m sestamibi dual-isotope myocardial perfusion single-photon emission computed tomography: a clinical validation study. J Am Coll Cardiol 1993;22:1455–64.PubMedGoogle Scholar
  7. 7.
    Germano G, Kiat H, Kavanagh PB, Moriel M, Mazzanti M, Su HT, et al. Automatic quantification of ejection fraction from gated myocardial perfusion SPECT. J Nucl Med 1995;36:2138–47.PubMedGoogle Scholar
  8. 8.
    Berman DS, Hachamovitch R, Kiat H, Cohen I, Cabico JA, Wang FP, et al. Incremental value of prognostic testing in patients with known or suspected ischemic heart disease: a basis for optimal utilization of exercise technetium-99m sestamibi myocardial perfusion single-photon emission computed tomography. J Am Coll Cardiol 1995;26:639–47.PubMedCrossRefGoogle Scholar
  9. 9.
    Hachamovitch R, Berman DS, Kiat H, Cohen I, Cabico JA, Friedman J, et al. Exercise myocardial perfusion SPECT in patients without known coronary artery disease: incremental prognostic value and use in risk stratification. Circulation 1996;93:905–14.PubMedGoogle Scholar
  10. 10.
    Ladenheim ML, Pollock BH, Rozanski A, Berman DS, Staniloff HM, Forrester JS, et al. Extent and severity of myocardial hypoperfusion as predictors of prognosis in patients with suspected coronary artery disease. J Am Coll Cardiol 1986;7:464–71.PubMedGoogle Scholar
  11. 11.
    Califf RM, Harrell FE Jr, Lee KL, Rankin JS, Hlatky MA, Mark DB, et al. The evolution of medical and surgical therapy for coronary artery disease. A 15-year perspective [see comments]. JAMA 1989;261:2077–86.PubMedCrossRefGoogle Scholar
  12. 12.
    Mark DB, Nelson CL, Califf RM, Harrell FE Jr, Lee KL, Jones RH, et al. Continuing evolution of therapy for coronary artery disease. Initial results from the era of coronary angioplasty. Circulation 1994;89:2015–25.PubMedGoogle Scholar
  13. 13.
    Staniloff HM, Forrester JS, Berman DS, Swan HJ. Prediction of death, myocardial infarction, and worsening chest pain using thallium scintigraphy and exercise electrocardiography. J Nucl Med 1986;27:1842–8.PubMedGoogle Scholar
  14. 14.
    Rosenbaum PR, Rubin DB. Difficulties with regression analyses of age-adjusted rates. Biometrics 1984;40:437–43.PubMedCrossRefGoogle Scholar
  15. 15.
    Rubin DB, Thomas N. Matching using estimated propensity scores: relating theory to practice. Biometrics 1996;52:249–64.PubMedCrossRefGoogle Scholar
  16. 16.
    Rubin DB. Practical implications of modes of statistical inference for causal effects and the critical role of the assignment mechanism. Biometrics 1991;47:1213–34.PubMedCrossRefGoogle Scholar
  17. 17.
    Rubin D. Estimating causal effects from large data sets using propensity scores. Ann Intern Med 1997;127:757–63.PubMedGoogle Scholar
  18. 18.
    Rosenbaum P, Rubin DB. The central role of the propensity index in observational studies for causal effects. Biometrika 1983;70:41–55.CrossRefGoogle Scholar
  19. 19.
    Greenland S. Modeling and variable selection in epidemiologic analysis. Am J Public Health 1989;79:340–9.PubMedCrossRefGoogle Scholar
  20. 20.
    Hosmer DW Jr, Lemeshow S. Applied logistic regression. New York:Wiley; 1989.Google Scholar
  21. 21.
    Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996;15:361–87.PubMedCrossRefGoogle Scholar
  22. 22.
    Harrell FJ. Predicting outcomes: applied survival analysis and logistic regression. Charlottesville: University of Virginia; 2000.Google Scholar
  23. 23.
    Cox D. Regression models and life tables (with discussion). J R Stat Soc Ser B 1972;34:187–220.Google Scholar
  24. 24.
    Solomon AJ, Gersh BJ. Management of chronic stable angina: medical therapy, percutaneous transluminal coronary angioplasty, and coronary artery bypass graft surgery. Lessons from the randomized trials. Ann Intern Med 1998;128:216–23.PubMedGoogle Scholar
  25. 25.
    Yusuf S, Zucker D, Peduzzi P, Fisher LD, Takaro T, Kennedy JW, et al. Effect of coronary artery bypass graft surgery on survival: overview of 10-year results from randomised trials by the Coronary Artery Bypass Graft Surgery Trialists Collaboration. Lancet 1994;344:563–70.PubMedCrossRefGoogle Scholar
  26. 26.
    Bucher HC, Hengstler P, Schindler C, Guyatt GH. Percutaneous transluminal coronary angioplasty versus medical treatment for non-acute coronary heart disease: meta-analysis of randomised controlled trials. BMJ 2000;321:73–7.PubMedCrossRefGoogle Scholar
  27. 27.
    Weiner DA, Ryan TJ, McCabe CH, Chaitman BR, Sheffield LT, Fisher LD, et al. Value of exercise testing in determining the risk classification and the response to coronary artery bypass grafting in three-vessel coronary artery disease: a report from the Coronary Artery Surgery Study (CASS) registry. Am J Cardiol 1987;60:262–6.PubMedCrossRefGoogle Scholar
  28. 28.
    Pryor DB, Harrell FE Jr, Lee KL, Rosati RA, Coleman RE, Cobb FR, et al. Prognostic indicators from radionuclide angiography in medically treated patients with coronary artery disease. Am J Cardiol 1984;53:18–22.PubMedCrossRefGoogle Scholar
  29. 29.
    Johnson LL, Verdesca SA, Aude WY, Xavier RC, Nott LT, Campanella MW, et al. Postischemic stunning can affect left ventricular ejection fraction and regional wall motion on poststress gated sestamibi tomograms [see comments]. J Am Coll Cardiol 1997;30:1641–8.PubMedCrossRefGoogle Scholar
  30. 30.
    Harrell FE Jr, Lee KL, Matchar DB, Reichert TA. Regression models for prognostic prediction: advantages, problems, and suggested solutions. Cancer Treat Rep 1985;69:1071–7.PubMedGoogle Scholar
  31. 31.
    Harrell FE Jr, Lee KL, Califf RM, Pryor DB, Rosati RA. Regression modelling strategies for improved prognostic prediction. Stat Med 1984;3:143–52.PubMedCrossRefGoogle Scholar
  32. 32.
    Hlatky MA, Califf RM, Harrell FE Jr, Lee KL, Mark DB, Pryor DB. Comparison of predictions based on observational data with the results of randomized controlled clinical trials of coronary artery bypass surgery. J Am Coll Cardiol 1988;11:237–45.PubMedCrossRefGoogle Scholar
  33. 33.
    Blackstone EH. Comparing apples and oranges. J Thorac Cardiovasc Surg 2002;123:8–15.PubMedCrossRefGoogle Scholar

Copyright information

© American Society of Nuclear Cardiology 2006

Authors and Affiliations

  • Rory Hachamovitch
    • 1
  • Alan Rozanski
    • 2
  • Sean W. Hayes
    • 3
  • Louise E. J. Thomson
    • 3
  • Guido Germano
    • 3
    • 4
  • John D. Friedman
    • 3
    • 4
  • Ishac Cohen
    • 3
    • 4
  • Daniel S. Berman
    • 3
    • 4
    Email author
  1. 1.Cardiovascular Division, Department of Medicine, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCalif
  2. 2.Division of Cardiology, Department of MedicineSt Luke’s Roosevelt Hospital Center, College of Physicians and Surgeons, Columbia UniversityNew York
  3. 3.Departments of Imaging (Division of Nuclear Medicine) and Medicine (Division of Cardiology)Cedars-Sinai Medical CenterLos Angeles
  4. 4.Department of Medicine, School of MedicineUniversity of California, Los AngelesLos AngelesCalif

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