Automatic measurement of long-term heart rate variability by implanted single-chamber devices

Heart rate variability (HRV) measurement is an established technology for the assessment of cardiac autonomic status. Recently 24 h HRV has been shown to correlate with disease severity in heart failure. This potentially makes continuous 24 h HRV measurement suitable for monitoring of heart-failure patients. Day-to-day 24 h measurement of HRV is, in principle, feasible when implemented using implanted devices (pacemakers and defibrillators) used in patients who are predominantly in the sinus rhythm. However, a number of such devices used in heart-failure patients are single-chamber devices, in which the distinction between sinus rhythm beats and ectopic beats is problematic. The study investigates whether a reasonably accurate 24 h HRV measurement can be achieved by automatic algorithms, suitable for implementation using implanted devices, without the need for identification of ectopic beats. A set of 5321 nominal 24 h Holter recordings of cardiac patients are used. Each of the recordings contains at least one ectopic beat; approximately 30% of the recordings have more than 1% of ectopic beats. Conventional 24 h measures of HRV, that is the SDNN, HRV index, and SDANN indices, are obtained from each recording after elimination of the ectopic beats and are approximated by HRV measures computed by the same formulas without exclusion of the ectopic beats. The SDANN values are also approximated by the standard deviation of 5 min medians of all RR intervals (SDMRR measure). The errors introduced by including the ectopic beats in the HRV computation were evaluated using the Bland-Altman statistics and by Cohen's kappa statistics investigating the precision of identifying patients with depressed and preserved 24 h HRV. The SDNN measure is very sensitive to the quality of the RR interval sequence and cannot be reasonably used without distinction between sinus rhythm and ectopic beats. The HRV index measure is marginally more acceptable when used without ectopic elimination. The SDANN is rather insensitive, and its replacement by SDMRR values leads to relative errors in the region of 2-5% that are almost independent of the number of ectopic beats included. Even in recordings with a substantial proportion of ectopic beats, a practically acceptable (kappa > 0.9) identification of depressed and preserved SDANN values is possible without ectopic elimination. Thus, continuous monitoring of 24 h HRV is technically feasible within implanted devices, provided the SDANN measure is monitored and either computed from the sequence of all RR intervals or, potentially preferably, replaced by the SDMRR measure.