title: A prognostic score for prediction of cardiac mortality risk after adenosine stress myocardial perfusion scintigraphy.
abstract: OBJECTIVE
  We sought to derive and validate a score to estimate risk after adenosine stress.
  
  
  BACKGROUND
  Maximizing the prognostic information extracted from adenosine stress myocardial perfusion scintigraphy, a commonly performed test, is often challenging for referring physicians.
  
  
  METHODS
  A split-set validation of a score predicting cardiovascular mortality was performed in 5,873 consecutive patients studied by adenosine stress, dual-isotope single-photon emission computed tomography (SPECT; follow-up 94% complete, mean 2.2 +/- 1.1 years).
  
  
  RESULTS
  On follow-up, 387 cardiac deaths occurred (6.6%). The Cox proportional hazards model most predictive of cardiac death included age, % myocardium ischemic, % myocardium fixed, early revascularization, dyspnea, diabetes mellitus, rest and peak stress heart rates, abnormal rest electrocardiogram (ECG), and an interaction between % myocardium ischemic and early revascularization (chi-square = 376). The final prognostic score was calculated as follows: (age [decades] x 5.19) + (% myocardium ischemic [per 10%] x 4.66) + (% myocardium fixed [per 10%] x 4.81) + (diabetes mellitus x 3.88) + (if patient treated with early revascularization, 4.51) + (if dyspnea was a presenting symptom, 5.47) + (resting heart rate [per 10 beats] x 2.88) - (peak heart rate [per 10 beats] x 1.42) + (ECG score x 1.95) - (if patient treated with early revascularization, % myocardium ischemic [per 10%] x 4.47). Scores of <49, 49 to 57, and >57 identified low, intermediate, and high risk (0.9%, 3.3%, and 9.5% cardiac death/year, respectively). Score results further risk stratified patients with respect to cardiac death in all categories of SPECT abnormality.
  
  
  CONCLUSIONS
  We derived and validated a score incorporating data available after adenosine stress perfusion SPECT. This score maximizes the prognostic information extracted from this test and may enhance the application of this test as part of an overall strategy.
authors.affiliation: Division of Cardiovascular Medicine, Department of Medicine, Keck School of Medicine, University of Southern California, USA.
authors.forename: Rory
authors.initials: R
authors.lastname: Hachamovitch
authors.forename: Sean W
authors.initials: SW
authors.lastname: Hayes
authors.forename: John D
authors.initials: JD
authors.lastname: Friedman
authors.forename: Ishac
authors.initials: I
authors.lastname: Cohen
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Berman
mesh_terms: D000241:Adenosine; D000368:Aged; D000369:Aged, 80 and over; D002423:Cause of Death; D003326:Coronary Circulation / Q000502:physiology*; D003327:Coronary Disease / Q000000981:diagnostic imaging* / Q000401:mortality; D004562:Electrocardiography / Q000187:drug effects; D005080:Exercise Test; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D009203:Myocardial Infarction / Q000401:mortality*; D011237:Predictive Value of Tests; D011379:Prognosis; D018570:Risk Assessment; D015899:Tomography, Emission-Computed, Single-Photon
chemical_list: D000241:Adenosine