Multimodal coupling and HRV assessment characterize autonomic functional changes in congestive heart failure patients with sinus rhythm or severe arrhythmia

Abstract

Autonomic nervous system (ANS) dysfunction is a significant characteristic of patients with congestive heart failure (CHF). Respiratory sinus arrhythmia (RSA) serves as an index of parasympathetic nervous system (PNS) function usually quantified by the high-frequency power of heart rate variability (HRV). However, the high breathing rate of CHF patients results in deviations when estimating RSA by HRV. Multimodal coupling analysis (MMCA) is a novel method of quantifying RSA which decomposes the R-R signal adaptively into intrinsic mode functions (IMFs) followed by identification of the RSA-related IMF. MMCA also calculates the phase synchronization between RSA-related IMF and respiratory signals to exclude the influences that are unrelated to RSA. In this study, we introduced HRV and MMCA-derived parameters to quantify ANS function for CHF patients, along with their comparisons in the clinical efficacy evaluation. Thirty-seven CHF patients were recruited, including 17 with sinus rhythm (SRHF) and 20 with severe arrhythmia (ARHF). Our results showed that all parameters for SRHF patients increased after treatment except for LF/HF. Only LF/HF, α2, and MMCA-derived RSA showed significant differences after treatment for ARHF patients, wherein the MMCA-derived RSA significantly decreased regardless of the left ventricular ejection fraction. The PNS function and ANS balance were recovered in all the CHF patients after treatment. Metrics including MeanRR, SDRR, LF, HF, TPower, SD1, SD2, and MMCA-derived RSA showed more significant improvements in SRHF patients whose New York Heart Association functional class improved after treatment. These metrics can be used to guide prognosis and therapeutic efficacy monitoring.