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. 2011 Apr;14(2):111–118. doi: 10.1089/rej.2010.1058

FIG. 1.

FIG. 1.

Identification of subgroups at different risks for mortality: Results of RECPAM analysis. REPCAM analysis identified patient subgroups at different risks for mortality. The tree-growing algorithm modeled odds ratios (OR) after a logistic regression with age, diabetes, and ischemic cardiomyopathy as global variables. Splitting variables are shown between branches, whereas a condition sending patients to left or right sibling is on a relative branch. Class 1 with lowest mortality was the reference category (OR = 1). Circles indicate subgroups of patients; squares indicate the patient subgroup REPCAM class. Numbers inside circles and squares represent the number of events (top) and the number of nonevents (bottom), respectively. (A) Females. Global adjustment variables: Age OR = 1.11 (1.06–1.16, diabetes OR = 1.15 (0.57–2.34, ischemic cardiomyopathy OR = 0.71 (0.28–1.81. (B) Males. Global adjustment variables: Age OR = 1.03 (1.00–1.07), diabetes OR = 1.59 (0.81–3.08), ischemic cardiomyopathy OR = 0.52 (0.26–1.03).