title: The incremental prognostic value of percentage of heart rate reserve achieved over myocardial perfusion single-photon emission computed tomography in the prediction of cardiac death and all-cause mortality: superiority over 85% of maximal age-predicted heart rate.
abstract: OBJECTIVE
  We sought to determine whether chronotropic incompetence (CI) adds incremental value in predicting cardiac death (CD) and all-cause mortality and to determine which marker of CI is superior.
  
  
  BACKGROUND
  Chronotropic incompetence, defined by either a low percent heart rate (HR) reserve achieved or failure to achieve 85% maximal age-predicted heart rate (MA-PHR), is a predictor of mortality. These variables have not been examined together in a comprehensive myocardial perfusion single-photon emission computed tomographic (SPECT), or MPS, model.
  
  
  METHODS
  A total of 10,021 patients who underwent exercise MPS, evaluated by a summed stress score (SSS), were followed up for 719 +/- 252 days. Percent HR reserve = (peak HR - rest HR)/(220 - age - rest HR) x 100, with <80% considered abnormal.
  
  
  RESULTS
  A total of 2,956 patients (29.5%) had low %HR reserve; 1,331 (13.3%) achieved <85% MA-PHR; and 1,296 (13.0%) had both. There were 234 deaths (93 CDs). On multivariate analysis, the SSS, %HR reserve, and inability to achieve 85% MA-PHR were predictors of all-cause mortality and CD (all p < 0.01). Myocardial perfusion SPECT was the most powerful predictor of CD (chi-square = 50). When the %HR reserve and ability to achieve 85% MA-PHR were considered, only the former remained a predictor of CD (p = 0.006 vs. p = 0.59).
  
  
  CONCLUSIONS
  In a comprehensive MPS model, CI was an important predictor of CD and all-cause mortality. Percent HR reserve was superior to the ability to achieve 85% MA-PHR in predicting CD; MPS was superior to both. Combined with previous studies, the findings suggest that %HR reserve should become the standard for assessing the adequacy of HR response during exercise testing, and that it should be routinely incorporated in risk stratification algorithms.
authors.affiliation: Department of Medicine (Division of Cardiology), University of California, Los Angeles, School of Medicine, Los Angeles, California, USA.
authors.forename: Babak
authors.initials: B
authors.lastname: Azarbal
authors.forename: Sean W
authors.initials: SW
authors.lastname: Hayes
authors.forename: Howard C
authors.initials: HC
authors.lastname: Lewin
authors.forename: Rory
authors.initials: R
authors.lastname: Hachamovitch
authors.forename: Ishac
authors.initials: I
authors.lastname: Cohen
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Berman
mesh_terms: D000367:Age Factors; D002318:Cardiovascular Diseases / Q000401:mortality; D003326:Coronary Circulation; D016757:Death, Sudden, Cardiac; D018572:Disease-Free Survival; D005080:Exercise Test; D006339:Heart Rate; D006801:Humans; D009026:Mortality; D011379:Prognosis; D016016:Proportional Hazards Models; D012307:Risk Factors; D015996:Survival Rate; D015899:Tomography, Emission-Computed, Single-Photon