Zhang Y, de Peuter OR, Kamphuisen PW, Karemaker JM. Search for HRV-parameters that detect a sympathetic shift in heart failure patients on β-blocker treatment.
Front Physiol 2013;
4:81. [PMID:
23596424 PMCID:
PMC3627138 DOI:
10.3389/fphys.2013.00081]
[Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2013] [Accepted: 03/26/2013] [Indexed: 11/13/2022] Open
Abstract
Background: A sympathetic shift in heart rate variability (HRV) from high to lower frequencies may be an early signal of deterioration in a monitored patient. Most chronic heart failure (CHF) patients receive β-blockers. This tends to obscure HRV observation by increasing the fast variations. We tested which HRV parameters would still detect the change into a sympathetic state.
Methods and results: β-blocker (Carvedilol®) treated CHF patients underwent a protocol of 10 min supine rest, followed by 10 min active standing. CHF patients (NYHA Class II–IV) n = 15, 10m/5f, mean age 58.4 years (47–72); healthy controls n = 29, 18m/11f, mean age 62.9 years (49–78). Interbeat intervals (IBI) were extracted from the finger blood pressure wave (Nexfin®). Both linear and non-linear HRV analyses were applied that (1) might be able to differentiate patients from healthy controls under resting conditions and (2) detect the change into a sympathetic state in the present short recordings.
Linear: mean-IBI, SD-IBI, root mean square of successive differences (rMSSD), pIBI-50 (the proportion of intervals that differs by more than 50 ms from the previous), LF, HF, and LF/HF ratio.
Non-linear: Sample entropy (SampEn), Multiscale entropy (MSE), and derived: Multiscale variance (MSV) and Multiscale rMSSD (MSD). In the supine resting situation patients differed from controls by having higher HF and, consequently, lower LF/HF. In addition their longer range (τ = 6–10) MSE was lower as well. The sympathetic shift was, in controls, detected by mean-IBI, rMSSD, pIBI-50, and LF/HF, all going down; in CHF by mean-IBI, rMSSD, pIBI-50, and MSD (τ = 6–10) going down. MSD6–10 introduced here works as a band-pass filter favoring frequencies from 0.02 to 0.1 Hz.
Conclusions: In β-blocker treated CHF patients, traditional time domain analysis (mean-IBI, rMSSD, pIBI-50) and MSD6–10 provide the most useful information to detect a condition change.
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