Nonlinear Measures of Heart Rate Variability and Mortality Risk in Hemodialysis Patients

HRV measures predicted mortality, only decreased scaling exponent a1 remained significant after adjusting for clinical risk factors (hazard ratio per a 0.25 decrement, 1.46; 95% confidence interval [95% CI], 1.16–1.85). The inclusion of a1 into a prediction model composed of clinical risk factors increased the C statistic from 0.84 to 0.87 (P=0.03), with 50.8% (95% CI, 20.2–83.7) continuous net reclassification improvement for 5-year mortality. The predictive power of a1 showed an interaction with age (P=0.02) and was particularly strong in patients aged ,70 years (n=208; hazard ratio, 1.87; 95% CI, 1.38–2.53), among whom a1 increased the C statistic from 0.85 to 0.89 (P=0.01), with a 93.1% (95% CI, 59.3–142.0) continuous net reclassification improvement. Conclusions Scaling exponent a1 that reflects fractal organization of short-term HRV improves risk stratification for mortality when added to the prediction model by conventional risk factors in hemodialysis patients, particularly those aged ,70 years. Clin J Am Soc Nephrol 7: ccc–ccc, 2012. doi: 10.2215/CJN.09430911