Heart rate variability and red cell distribution width in patients with systolic left heart failure

Scand Cardiovasc J. 2013 Aug;47(4):225-9. doi: 10.3109/14017431.2012.755561. Epub 2013 Jan 3.

Abstract

Objective: Red cell distribution width (RDW) is a strong prognostic marker for systolic left heart failure regardless of the anemia status, and heart rate variability (HRV) is negatively associated with mortality and sudden cardiac death in patients with systolic left heart failure. Their relationship has not been investigated in the previous literature.

Design: One hundred eighty four patients who had been previously diagnosed with systolic left heart failure (with ischemic or non-ischemic etiology) were retrospectively enrolled in our study. Patients underwent 24-h electrocardiographic monitoring, and blood samples for RDW and other variables were analyzed. Study population was grouped into tertiles of RDW (Tertile 1: 13.4 ± 1.4%, Tertile 2: 14.6 ± 1.4%, and Tertile 3: 17.1 ± 1.2%).

Results: Most of the characteristics of patients were similar among RDW tertiles. Standard deviation of all normal RR intervals (SDNN), standard deviation of the averages of RR intervals in all 5-min segments (SDANN) and root-mean square of difference of successive RR intervals (RMSSD) values significantly differed among groups (p < 0.001). The highest RDW tertile had the lowest HRV values, and Pearson correlation analysis yielded a negative correlation between HRV parameters and RDW (for SDNN, SDANN, RMSSD; r = 0.373, 0.340, 0.362, respectively, p < 0.001 for all). In stepwise multivariate analysis HRV was independently associated with RDW.

Conclusions: The HRV parameters were independently associated with RDW in patients with systolic left heart failure.

MeSH terms

  • Aged
  • Chi-Square Distribution
  • Electrocardiography, Ambulatory
  • Erythrocyte Indices*
  • Female
  • Heart Failure, Systolic / blood*
  • Heart Failure, Systolic / diagnosis
  • Heart Failure, Systolic / physiopathology*
  • Heart Rate*
  • Humans
  • Linear Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Retrospective Studies