title: Myocardial perfusion imaging is a strong predictor of death in women.
abstract: OBJECTIVE
  We sought to assess the prognostic value and risk classification improvement using contemporary single-photon emission computed tomography myocardial perfusion imaging (SPECT-MPI) to predict all-cause mortality.
  
  
  BACKGROUND
  Myocardial perfusion is a strong estimator of prognosis. Evidence published to date has not established the added prognostic value of SPECT-MPI nor defined an approach to detect improve classification of risk in women from a developing nation.
  
  
  METHODS
  A total of 2,225 women referred for SPECT-MPI were followed by a mean period of 3.7 ± 1.4 years. SPECT-MPI results were classified as abnormal on the presence of any perfusion defect. Abnormal scans were further classified as with mild/moderate reversible, severe reversible, partial reversible, or fixed perfusion defects. Risk estimates for incident mortality were categorized as <1%/year, 1% to 2%/year, and >2%/year using Cox proportional hazard models. Risk-adjusted models incorporated clinical risk factors, left ventricular ejection fraction (LVEF), and perfusion variables.
  
  
  RESULTS
  All-cause death occurred in 139 patients. SPECT-MPI significantly risk stratified the population; patients with abnormal scans had significantly higher death rates compared with patients with normal scans, 13.1% versus 4.0%, respectively (p < 0.001). Cox analysis demonstrated that after adjusting for clinical risk factors and LVEF, SPECT-MPI improved the model discrimination (integrated discrimination index = 0.009; p = 0.02), added significant incremental prognostic information (global chi-square increased from 87.7 to 127.1; p < 0.0001), and improved risk prediction (net reclassification improvement = 0.12; p = 0.005).
  
  
  CONCLUSIONS
  SPECT-MPI added significant incremental prognostic information to clinical and left ventricular functional variables while enhancing the ability to classify this Brazilian female population into low- and high-risk categories of all-cause mortality.
authors.affiliation: Setor de Ciências da Saúde, Universidade Federal do Paraná, Curitiba, Brazil. cerci@hospitalcoracao.com.br
authors.forename: Mario Sergio Julio
authors.initials: MS
authors.lastname: Cerci
authors.forename: Juliano Julio
authors.initials: JJ
authors.lastname: Cerci
authors.forename: Rodrigo Julio
authors.initials: RJ
authors.lastname: Cerci
authors.forename: Carlos Cunha
authors.initials: CC
authors.lastname: Pereira Neto
authors.forename: Evelinda
authors.initials: E
authors.lastname: Trindade
authors.forename: Dominique
authors.initials: D
authors.lastname: Delbeke
authors.forename: Claudio L Pereira
authors.initials: CL
authors.lastname: da Cunha
authors.forename: João Vicente
authors.initials: JV
authors.lastname: Vitola
mesh_terms: D000368:Aged; D000704:Analysis of Variance; D001938:Brazil; D016009:Chi-Square Distribution; D003326:Coronary Circulation; D005260:Female; D006331:Heart Diseases / Q000000981:diagnostic imaging* / Q000401:mortality* / Q000503:physiopathology; D006801:Humans; D053208:Kaplan-Meier Estimate; D008875:Middle Aged; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D012737:Sex Factors; D013318:Stroke Volume; D015899:Tomography, Emission-Computed, Single-Photon; D016277:Ventricular Function, Left