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This work has proposed a methodology based on the concept of entropy rates to study the complexity of the short-term heart-rate variability (HRV) for improving risk stratification to predict sudden cardiac death (SCD) of patients with established ischemic-dilated cardiomyopathy (IDC). The short-term HRV was analyzed during daytime and nighttime by means of RR series. An entropy rate was calculated on the RR series, previously transformed to symbol sequences by means of an alphabet. A statistical analysis permitted to stratify high- and low-risk patients of suffering SCD, with a specificity (SP) of 95% and sensitivity (SE) of 83.3%. To get a better characterization of short-term HRV, the study has also considered the adjustment of the parameters involved in the proposed methodology. Finally, a statistical analysis was applied to recognize valid prognostic markers.