title: Optimizing risk stratification in cardiac rehabilitation with inclusion of a comorbidity index.
abstract: OBJECTIVE
  The risk stratification criteria of the American Association of Cardiovascular and Pulmonary Rehabilitation include guidelines to be used in stratifying cardiac rehabilitation (CR) patients for risk of disease progression (long term) and clinical events (short term). Noncardiac comorbidities are not included as indicators in these criteria. This study was designed to ascertain the prevalence of noncardiac comorbidities among CR patients, and to assess their relation to the current risk stratification algorithm for clinical events.
  
  
  METHODS
  Patients were stratified into high-, intermediate-, and low-risk groups according to the American Association of Cardiovascular and Pulmonary Rehabilitation risk stratification criteria for clinical events (ARSE) at program entry. Within each risk group, age, gender, race, and noncardiac comorbidities were ascertained. Comorbidities were summarized in a comorbidity index (CMI). The relation between clinical events and risk status by ARSE and CMI was evaluated by logistic regression.
  
  
  RESULTS
  Among 490 patients (age, 60 +/- 12 years; 35% women; 30% nonwhite) enrolled in CR with ischemic heart disease, the number of comorbidities ranged from 0 to 7 (median, 2; 75th percentile, 3). The patients categorized in the three ARSE groups differed significantly in age and comorbidities. Although ARSE tended to identify patients with a greater comorbidity burden, 38% of the patients with a comorbidity index exceeding the 75th percentile were not classified in the highest ARSE group. Clinical events increased across ARSE and CMI risk strata. Both ARSE and CMI were independent predictors of events in an age-, gender-, and race-adjusted logistic regression analysis (ARSE odds ratio [OR], 1.56; 95% confidence interval [CI], 1.14-2.12; CMI OR, 1.23, 95% CI, 1.03a-1.47). Events were predicted best when both classifications were combined. Exploratory gender-specific analyses suggested that ARSE performed better among men than among women, whereas CMI was a more important predictor among women.
  
  
  CONCLUSIONS
  To appreciate more fully the overall complexity of disease among CR patients, ARSE should be supplemented not only with the inclusion of cardiac risk factors, as suggested in the current guidelines, but also with an assessment of noncardiac comorbidities.
authors.affiliation: Division of Cardiovascular Disease, University of Alabama at Birmingham, 35294-0007, USA. gzoghbi@cardio.dom.uab.edu
authors.forename: Gilbert J
authors.initials: GJ
authors.lastname: Zoghbi
authors.forename: Bonnie
authors.initials: B
authors.lastname: Sanderson
authors.forename: Jenny
authors.initials: J
authors.lastname: Breland
authors.forename: Carla
authors.initials: C
authors.lastname: Adams
authors.forename: Chris
authors.initials: C
authors.lastname: Schumann
authors.forename: Vera
authors.initials: V
authors.lastname: Bittner
mesh_terms: D000367:Age Factors; D000368:Aged; D015897:Comorbidity; D018450:Disease Progression; D005260:Female; D006331:Heart Diseases / Q000453:epidemiology* / Q000503:physiopathology / Q000534:rehabilitation*; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012307:Risk Factors; D012737:Sex Factors; D013318:Stroke Volume / Q000502:physiology; D016896:Treatment Outcome