Heart Rhythm Complexity Impairment in Patients with Pulmonary Hypertension

Abstract

Pulmonary hypertension is a fatal disease, however reliable prognostic tools are lacking. Heart rhythm complexity analysis is derived from non-linear heart rate variability (HRV) analysis and has shown excellent performance in predicting clinical outcomes in several cardiovascular diseases. However, heart rhythm complexity has not previously been studied in pulmonary hypertension patients. We prospectively analyzed 57 patients with pulmonary hypertension (31 with pulmonary arterial hypertension and 26 with chronic thromboembolic pulmonary hypertension) and compared them to 57 age- and sex-matched control subjects. Heart rhythm complexity including detrended fluctuation analysis (DFA) and multiscale entropy (MSE) and linear HRV parameters were analyzed. The patients with pulmonary hypertension had significantly lower mean RR, SDRR, pNN 20 , VLF, LF, LF/HF ratio, DFAα1, MSE slope 5, scale 5, area 1–5 and area 6–20 compared to the controls. Receiver operating characteristic curve analysis showed that heart rhythm complexity parameters were better than traditional HRV parameters to predict pulmonary hypertension. Among all parameters, scale 5 had the greatest power to differentiate the pulmonary hypertension patients from controls (AUC: 0.845, P < 0.001). Furthermore, adding heart rhythm complexity parameters significantly improved the discriminatory power of the traditional HRV parameters in both net reclassification improvement and integrated discrimination improvement models. In conclusion, the patients with pulmonary hypertension had worse heart rhythm complexity. MSE parameters, especially scale 5, had excellent single discriminatory power to predict whether or not patients had pulmonary hypertension.

Non-linear analysis of heart rate variability for evaluating the acute effects of caffeinated beverages in young adults

“…It has shown that the complexity decreased in the presence of a systemic disease. 12,14 The main reason of the difference may be the existence of a disease in the participants and the breakdown of the balance in the systems.…”

“…Also, Tsai et al reported that detrended fluctuation analysis shown better predictive ability for clinical outcomes when compared to traditional heart rate variability analysis methods. 14 In the literature, there are some studies which investigated heart rate variability time series with detrended fluctuation analysis and reported the accuracy of the method. 15,16 To our knowledge, there are no reports in the literature on non-linear analysis of heart rate variability used to investigate the acute effects of caffeinated beverages on cardiovascular system.…”

Multiscale Entropy of Cardiac and Postural Control Reflects a Flexible Adaptation to a Cognitive Task

“…In agreement with these interpretations, experimental applications have demonstrated a degraded entropy in cardiac and postural dynamics associated with frailty, aging, impairments, or diseases [ 1 , 3 , 4 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. By contrast, high entropy is generally associated with an elevated capacity to adjust to an ever-changing environment [ 8 ], and elevated values are often observed in young healthy people [ 1 ].…”

Usefulness of heart rhythm complexity in heart failure detection and diagnosis

“…However, previous HRV studies have mainly focused on linear analysis, and its ability to predict outcomes remains limited compared with non-linear HRV 8,12 . Non-linear HRV has also been studied with regards to the diagnosis and outcome prediction in many diseases with excellent results, including the outcomes of acute stroke 34 , primary aldosteronism 16 , severity of abdominal aorta calcification 35 , critical illnesses requiring extracorporeal life support 36 , post-myocardial infarction heart function 37 , and pulmonary hypertension 17 .…”

“…Heart rhythm complexity derived from non-linear HRV measures the complexity of heart rate interval, and is composed of multiscale entropy (MSE) and detrended fluctuation analysis (DFA). Compared to linear parameters, heart rhythm complexity has shown a much greater ability to detect diseases such as end-stage renal disease, primary aldosteronism, and pulmonary hypertension 15 – 17 . Therefore, it would seem to be reasonable to use heart rate complexity in the detection and diagnosis of HF.…”