title: Sometimes higher heart rate variability is not better heart rate variability: results of graphical and nonlinear analyses.
abstract: OBJECTIVE
  To determine the prevalence and effect on traditional heart rate variability (HRV) indices of abnormal HRV patterns in the elderly.
  
  
  METHODS
  Hourly Poincaré plots and plots of spectral HRV from normal-to-normal interbeat intervals and hourly nonlinear HRV values were examined in a subset of 290 consecutive participants in the Cardiovascular Health Study. Only subjects in normal sinus rhythm with > or = 18 hours of usable data were included. Eligible subjects were 71 +/- 5 years. During 7 years of follow-up, 21.7% had died. Hours were scored as normal (0), borderline (0.5), or abnormal (1) from a combination of plot appearance and HRV. Summed scores were normalized to 100% to create an abnormality score (ABN). Short-term HRV versus each 5th percentile of ABN was plotted and a cutpoint for markedly increased HRV identified. The t-tests compared HRV for subjects above and below this cutpoint. Cox regression evaluated the association of ABN and mortality.
  
  
  RESULTS
  Of 5,815 eligible hourly plots, 64.4% were normal, 14.5% borderline, and 21.1% abnormal. HR, SDNN, SDNNIDX, ln VLF and LF power, and power law slope did not differ by the cutpoint for increased short-term HRV, while SDANN and ln ULF power were significantly lower for those above the cutpoint. However, many HRV indices including LF/HF ratio and normalized LF and HF power were significantly different between groups (P < 0.001). Increased ABN was significantly associated with mortality (P = 0.019). Despite similar values for many HRV indices, being in the group above the cutpoint was significantly associated with mortality (P = 0.04).
  
  
  CONCLUSIONS
  Abnormal HR patterns that elevate many HRV indices are prevalent among the elderly and associated with higher risk of mortality. Consideration of abnormal HRV may improve HRV-based risk stratification.
authors.affiliation: Washington University School of Medicine, St. Louis, Missouri 63108, USA. pstein@im.wustl.edu
authors.forename: Phyllis K
authors.initials: PK
authors.lastname: Stein
authors.forename: Peter P
authors.initials: PP
authors.lastname: Domitrovich
authors.forename: Nelson
authors.initials: N
authors.lastname: Hui
authors.forename: Pentti
authors.initials: P
authors.lastname: Rautaharju
authors.forename: John
authors.initials: J
authors.lastname: Gottdiener
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001146:Arrhythmia, Sinus / Q000175:diagnosis* / Q000401:mortality* / Q000503:physiopathology; D015331:Cohort Studies; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D006339:Heart Rate; D006801:Humans; D008297:Male; D008955:Models, Cardiovascular; D017711:Nonlinear Dynamics; D009716:Numerical Analysis, Computer-Assisted; D015995:Prevalence; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012680:Sensitivity and Specificity; D014481:United States / Q000453:epidemiology