Prognostic significance of heart rate variability in dilated cardiomyopathy

Int J Cardiol. 2003 Jan;87(1):75-81. doi: 10.1016/s0167-5273(02)00207-3.

Abstract

Background: Identifying high-risk individuals among patients with nonischemic dilated cardiomyopathy (DCM) is a major and unsolved task of clinical cardiology. We aimed to determine prognostic significance of heart rate variability (HRV) for predicting cardiac events in DCM patients with markedly depressed left ventricular function.

Methods: In 69 DCM patients in sinus rhythm, with normal coronary angiography and mean ejection fraction 32 (11%) cardiac events defined as cardiac death or heart transplantation during a mean 20-month follow-up were related to baseline time-domain HRV parameters calculated from 24-h digital Holter monitoring.

Results: There were 18 (26%) cardiac events (10 deaths and 8 heart transplantations). In multivariate Cox analysis, standard deviation of normal-to-normal intervals (SDNN) (hazard ratio: 1.35; 95% confidence interval 1.11-1.63; P=0.002) and ejection fraction (hazard ratio: 4.21; confidence interval 1.64-10.78; P=0.003) were significant and independent predictors of cardiac events. One-year event-free survival was significantly lower in patients with SDNN<80 ms compared to those with SDNN>or=80 ms (35% vs. 89%, respectively; P<0.00005). Low SDNN was identifying high-risk patients among those with both depressed and relatively preserved left ventricular function.

Conclusions: Broadly available time-domain HRV analysis adds independent prognostic information improving risk stratification of DCM patients and therefore it should be incorporated in routine clinical evaluation to determine patients' priority for heart transplantation.

MeSH terms

  • Adult
  • Cardiomyopathy, Dilated / physiopathology*
  • Chi-Square Distribution
  • Echocardiography
  • Electrocardiography, Ambulatory
  • Female
  • Heart Rate / physiology*
  • Humans
  • Male
  • Predictive Value of Tests
  • Prognosis
  • Proportional Hazards Models
  • Prospective Studies
  • Statistics, Nonparametric