Heart Rhythm Complexity Research Articles

Heart rhythm complexity analysis in patients with inferior ST-elevation myocardial infarction

Heart rhythm complexity (HRC), a subtype of heart rate variability (HRV), is an important tool to investigate cardiovascular disease. In this study, we aimed to analyze serial changes in HRV and HRC metrics in patients with inferior ST-elevation myocardial infarction (STEMI) within 1 year postinfarct and explore the association between HRC and postinfarct left ventricular (LV) systolic impairment. We prospectively enrolled 33 inferior STEMI patients and 74 control subjects and analyzed traditional linear HRV and HRC metrics in both groups, including detrended fluctuation analysis (DFA) and multiscale entropy (MSE). We also analyzed follow-up postinfarct echocardiography for 1 year. The STEMI group had significantly lower standard deviation of RR interval (SDNN), and DFAα2 within 7 days postinfarct (acute stage) comparing to control subjects. LF power was consistently higher in STEMI group during follow up. The MSE scale 5 was higher at acute stage comparing to control subjects and had a trend of decrease during 1-year postinfarct. The MSE area under scale 1–5 showed persistently lower than control subjects and progressively decreased during 1-year postinfarct. To predict long-term postinfarct LV systolic impairment, the slope between MSE scale 1 to 5 (slope 1–5) had the best predictive value. MSE slope 1–5 also increased the predictive ability of the linear HRV metrics in both the net reclassification index and integrated discrimination index models. In conclusion, HRC and LV contractility decreased 1 year postinfarct in inferior STEMI patients, and MSE slope 1–5 was a good predictor of postinfarct LV systolic impairment.

The autonomic balance of heart rhythm complexity after renal artery denervation: insight from entropy of entropy and average entropy analysis

BackgroundThe current method to evaluate the autonomic balance after renal denervation (RDN) relies on heart rate variability (HRV). However, parameters of HRV were not always predictive of response to RDN. Therefore, the complexity and disorder of heart rhythm, measured by entropy of entropy (EoE) and average entropy (AE), have been used to analyze autonomic dysfunction. This study evaluated the dynamic changes in autonomic status after RDN via EoE and AE analysis.MethodsFive patients were prospectively enrolled in the Global SYMPLICITY Registry from 2020 to 2021. 24-h Holter and ambulatory blood pressure monitoring (ABPM) was performed at baseline and 3 months after RDN procedures. The autonomic status was analyzed using the entropy-based AE and EoE analysis and the conventional HRV-based low frequency (LF), high frequency (HF), and LF/HF.ResultsAfter RDN, the ABPM of all patients showed a significant reduction in blood pressure (BP) and heart rate. Only AE and HF values of all patients had consistent changes after RDN (p < 0.05). The spearman rank-order correlation coefficient of AE vs. HF was 0.86, but AE had a lower coefficient of variation than HF.ConclusionsMonitoring the AE and EoE analysis could be an alternative to interpreting autonomic status. In addition, a relative change of autonomic tone, especially an increasing parasympathetic activity, could restore autonomic balance after RDN.

The Value of Heart Rhythm Complexity in Identifying High-Risk Pulmonary Hypertension Patients.

Pulmonary hypertension (PH) is a fatal disease—even with state-of-the-art medical treatment. Non-invasive clinical tools for risk stratification are still lacking. The aim of this study was to investigate the clinical utility of heart rhythm complexity in risk stratification for PH patients. We prospectively enrolled 54 PH patients, including 20 high-risk patients (group A; defined as WHO functional class IV or class III with severely compromised hemodynamics), and 34 low-risk patients (group B). Both linear and non-linear heart rate variability (HRV) variables, including detrended fluctuation analysis (DFA) and multiscale entropy (MSE), were analyzed. In linear and non-linear HRV analysis, low frequency and high frequency ratio, DFAα1, MSE slope 5, scale 5, and area 6–20 were significantly lower in group A. Among all HRV variables, MSE scale 5 (AUC: 0.758) had the best predictive power to discriminate the two groups. In multivariable analysis, MSE scale 5 (p = 0.010) was the only significantly predictor of severe PH in all HRV variables. In conclusion, the patients with severe PH had worse heart rhythm complexity. MSE parameters, especially scale 5, can help to identify high-risk PH patients.

Heart rhythm complexity as predictors for the prognosis of end-stage renal disease patients undergoing hemodialysis

BackgroundHeart rhythm complexity, a measure of heart rate dynamics and a risk predictor in various clinical diseases, has not been systematically studied in patients with end-stage renal disease. The aim of this study is to investigate the heart rhythm complexity and its prognostic value for mortality in end-stage renal disease patients undergoing hemodialysis.MethodsTo assess heart rhythm complexity and conventional heart rate variability measures, 4-h continuous electrocardiography for a retrospective cohort of 202 ostensibly healthy control subjects and 51 hemodialysis patients with end-stage renal disease were analyzed. Heart rhythm complexity was quantified by the complexity index from the measurement of the multiscale entropy profile.ResultsDuring a follow-up of 13 months, 8 people died in the patient group. Values of either traditional heart rate variability measurements or complexity indices were found significantly lower in patients than those in healthy controls. In addition, the complexity indices (Area 1–5, Area 6–15 and Area 6–20) in the mortality group were significantly lower than those in the survival group, while there were no significant differences in traditional heart rate variability parameters between the two groups. In receiver operating characteristic curve analysis, Area 6–20 (AUC = 0.895, p < 0.001) showed the strongest predictive power between mortality and survival groups.ConclusionThe results suggest that heart rhythm complexity is impaired for patients with end-stage renal disease. Furthermore, the complexity index of heart rate variability quantified by multiscale entropy may be a powerful independent predictor of mortality in end-stage renal disease patients undergoing hemodialysis.

Usefulness of heart rhythm complexity in heart failure detection and diagnosis

Heart failure (HF) is a major cardiovascular disease worldwide, and the early detection and diagnosis remain challenges. Recently, heart rhythm complexity analysis, derived from non-linear heart rate variability (HRV) analysis, has been proposed as a non-invasive method to detect diseases and predict outcomes. In this study, we aimed to investigate the diagnostic value of heart rhythm complexity in HF patients. We prospectively analyzed 55 patients with symptomatic HF with impaired left ventricular ejection fraction and 97 participants without HF symptoms and normal LVEF as controls. Traditional linear HRV parameters and heart rhythm complexity including detrended fluctuation analysis (DFA) and multiscale entropy (MSE) were analyzed. The traditional linear HRV, MSE parameters and DFAα1 were significantly lower in HF patients compared with controls. In regression analysis, DFAα1 and MSE scale 5 remained significant predictors after adjusting for multiple clinical variables. Among all HRV parameters, MSE scale 5 had the greatest power to differentiate the HF patients from the controls in receiver operating characteristic curve analysis (area under the curve: 0.844). In conclusion, heart rhythm complexity appears to be a promising tool for the detection and diagnosis of HF.

Heart Rhythm Complexity Predicts Long-Term Cardiovascular Outcomes in Peritoneal Dialysis Patients: A Prospective Cohort Study.

BackgroundCardiovascular disease is the leading cause of morbidity and mortality in patients with end‐stage renal disease. Heart rhythm complexity analysis has been shown to be useful in predicting outcomes in various diseases; however, data on patients with end‐stage renal disease are limited. In this study, we analyzed the association between heart rhythm complexity and long‐term cardiovascular outcomes in patients with end‐stage renal disease receiving peritoneal dialysis.Methods and ResultsWe prospectively enrolled 133 patients receiving peritoneal dialysis and analyzed linear heart rate variability and heart rhythm complexity variables including detrended fluctuation analysis (DFA) and multiscale entropy. The primary outcome was cardiovascular mortality, and the secondary outcome was the occurrence of major adverse cardiovascular events. After a median of 6.37 years of follow‐up, 21 patients (22%) died from cardiovascular causes. These patients had a significantly lower low‐frequency band of heart rate variability, low/high‐frequency band ratio, total power band of heart rate variability, heart rate turbulence slope, deceleration capacity, short‐term DFA (DFAα1); and multiscale entropy slopes 1 to 5, scale 5, area 1 to 5, and area 6 to 20 compared with the patients who did not die from cardiovascular causes. Time‐dependent receiver operating characteristic curve analysis showed that DFAα1 had the greatest discriminatory power for cardiovascular mortality (area under the curve: 0.763) and major adverse cardiovascular events (area under the curve: 0.730). The best cutoff value for DFAα1 was 0.98 to predict both cardiovascular mortality and major adverse cardiovascular events. Multivariate Cox regression analysis showed that DFAα1 (hazard ratio: 0.076; 95% CI, 0.016–0.366; P=0.001) and area 1 to 5 (hazard ratio: 0.645; 95% CI, 0.447–0.930; P=0.019) were significantly associated with cardiovascular mortality.ConclusionsHeart rhythm complexity appears to be a promising noninvasive tool to predict long‐term cardiovascular outcomes in patients receiving peritoneal dialysis.

Heart Rhythm Complexity Impairment in Patients with Pulmonary Hypertension

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, pNN20, 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.

Predictors of seizure reduction outcome after vagus nerve stimulation in drug-resistant epilepsy

PurposeTo evaluate the predictors of seizure reduction outcome after vagus nerve stimulation (VNS) in patients with drug-resistant epilepsy (DRE). MethodsA meta-analysis was performed using relevant research from databases such as PubMed, Embase, Cochrane Online Library, and Clinicaltrials.gov. Studies were selected according to predefined inclusion and exclusion criteria. The quality of studies was evaluated by using the Newcastle-Ottawa Scale (NOS) scale. All data was pooled by STATA 12.0 software for meta-analysis. ResultsThe review considered 1281 articles, and 16 articles with NOS score ≥6 were included in the analysis. The meta-analysis showed that at 6 m, 1, 2, 3, 4, 6 and 12 years after implantation, 33.99, 43.42, 46.50, 63.31, 52.71, 54.64, 70.37 and 82.90% of patients exhibited >50% reduction of seizure frequency after VNS. The duration of epilepsy showed a significant difference between the good responders and poor responders (p = 0.038), whereas age at VNS implantation (p = 0.305), age at seizure onset (p = 0.530), seizure type (p = 0.11), etiology (p = 0.187), and history of previous epilepsy surgery (p = 0.075) were not predictors of seizure reduction outcome after VNS. Several features about the electroencephalogram (EEG) feature and heart rhythm complexity (HRV) have not been analyzed by a sufficient number of studies. ConclusionsDRE patients with shorter duration of epilepsy may be better candidates for VNS rather than those who are younger at onset and implantation. Several EEG or HRV features may have predictive value but more research is needed.

The association between heart rhythm complexity and the severity of abdominal aorta calcification in peritoneal dialysis patients

Abdominal aorta calcification (AAC) has been associated with clinical outcomes in peritoneal dialysis (PD) patients. Heart rhythm complexity analysis has been shown to be a promising tool to predict outcomes in patients with cardiovascular disease. In this study, we aimed to analyze the association between heart rhythm complexity and AAC in PD patients. We prospectively analyzed 133 PD patients. Heart rhythm complexity including detrended fluctuation analysis and multiscale entropy was performed. In linear analysis, the patients in the higher AAC group (AAC ≥15%) had a significantly lower standard deviation of normal RR intervals, very low frequency, low frequency, high frequency and low/high frequency ratio. In non-linear analysis, DFAα1, slope 1–5, scale 5 and area 6–20 were significantly lower in the patients with higher AAC. Receiver operating characteristic curve analysis showed that DFAα1 had the greatest discriminatory power to differentiate these two groups. Multivariate logistic regression analysis showed that DFAα1 and HbA1c were significantly associated with higher AAC ratio. Adding DFAα1 significantly improved the discriminatory power of the linear parameters in both net reclassification improvement and integrated discrimination improvement models. In conclusion, DFAα1 is highly associated with AAC and a potential cardiovascular marker in PD patients.

Chronic vagus nerve stimulation reverses heart rhythm complexity in patients with drug-resistant epilepsy: An assessment with multiscale entropy analysis

ObjectiveVagus nerve stimulation (VNS) is an adjunctive treatment in drug-resistant epilepsy. The alterations in heart rate dynamics through VNS are not well understood. This study aimed to determine changes in heart rhythm complexity in association with VNS and to relate the findings to the outcome of VNS treatment in patients with drug-resistant epilepsy. MethodsWe prospectively analyzed 32 patients with drug-resistant epilepsy, who underwent VNS implantation, and 32 age- and sex-matched healthy control subjects. The interictal heartbeat intervals were analyzed using the heart rhythm complexity with multiscale entropy (MSE) and traditional heart rate variability (HRV) analyses based on ambulatory 24-hour electrocardiograms (ECGs). ResultsPatients had significantly decreased complexity indices (Slope 5, Area 1–5, Area 6–15, Area 6–20) on MSE analysis and decreased HRV measurements (standard deviation of the heartbeat interval (SDNN), square root of the mean of sum of squares of the differences between adjacent RR intervals (RMSSD), pNN50, very low frequency (VLF), low frequency (LF), high frequency (HF), total power (TP)) in time and frequency domain analyses. After one year of VNS treatment in patients with drug-resistant epilepsy, there was a trend in an elevated MSE profile with significant higher values between the scales 1 and 9. Vagus nerve stimulation induces a more significant increase of MSE in VNS responders than those in the nonresponders. The conventional HRV measurements did not change. ConclusionOur results suggest that heart rhythm complexity is impaired in patients with drug-resistant epilepsy, and this is at least partially reversed by VNS treatment. Furthermore, VNS-induced effects on heart rate complexity may be associated with the therapeutic response to VNS in patients with drug-resistant epilepsy.

Preoperative Heart Rate Variability as Predictors of Vagus Nerve Stimulation Outcome in Patients with Drug-resistant Epilepsy

Vagus nerve stimulation (VNS) is an adjunctive treatment for drug-resistant epilepsy (DRE). However, it is still difficult to predict which patients will respond to VNS treatment and to what extent. We aim to explore the relationship between preoperative heart rate variability (HRV) and VNS outcome. 50 healthy control subjects and 63 DRE patients who had received VNS implants and had at least one year of follow up were included. The preoperative HRV were analyzed by traditional linear methods and heart rhythm complexity analyses with multiscale entropy (MSE). DRE patients had significantly lower complexity indices (CI) as well as traditional linear HRV measurements than healthy controls. We also found that non-responders0 had significantly lower preoperative CI including Area 1–5, Area 6–15 and Area 6–20 than those in the responders0 while those of the non-responders50 had significantly lower RMSSD, pNN50, VLF, LF, HF, TP and LF/HF than the responders50. In receiver operating characteristic (ROC) curve analysis, Area 6–20 and RMSSD had the greatest discriminatory power for the responders0 and non-responders0, responders50 and non-responders50, respectively. Our results suggest that preoperative assessment of HRV by linear and MSE analysis can help in predicting VNS outcomes in patients with DRE.

Impairment of heart rhythm complexity in patients with drug-resistant epilepsy: An assessment with multiscale entropy analysis

ObjectiveEpilepsy and seizures can have dramatic effects on the cardiac function. The aim of this study was to investigate the heart rhythm complexity in patients with drug-resistant epilepsy (DRE). MethodsAmbulatory 24-h electrocardiograms (ECG) from 70 DRE patients and 50 healthy control subjects were analyzed using conventional heart rate variability (HRV) and multiscale entropy (MSE) methods The variation of complexity indices (CI), which was calculated from MSE profile, was determined. ResultsDRE patients had significantly lower time domain (Mean RR, SDNN, RMSSD, pNN50) and frequency domain (VLF, LF, HF, TP) HRV measurements than healthy controls. Of the MSE analysis, MSE profile, CI including Slope 5, Area 1–5, Area 6–15 and Area 6–20 were significantly lower than those in the healthy control group. In receiver operating characteristic (ROC) curve analysis, VLF had the greatest discriminatory power for the two groups. In both net reclassification improvement (NRI) model and integrated discrimination improvement (IDI) models, CI derived from MSE profiles significantly improved the discriminatory power of Mean RR, SDNN, RMSSD, pNN50, VLF, LF, HF and TP. SignificanceThe heart rate complexity is impaired for DRE patients. CI are useful to discriminate DRE patients from subjects with normal cardiac complexity. These findings indicate that MSE method may serve as a complementary approach for characterizing and understanding abnormal heart rate dynamics in epilepsy. Furthermore, the CI may potentially be used as a biomarker in monitoring epilepsy.

Serial heart rhythm complexity changes in patients with anterior wall ST segment elevation myocardial infarction

Heart rhythm complexity analysis has been shown to have good prognostic power in patients with cardiovascular disease. The aim of this study was to analyze serial changes in heart rhythm complexity from the acute to chronic phase of acute myocardial infarction (MI). We prospectively enrolled 27 patients with anterior wall ST segment elevation myocardial infarction (STEMI) and 42 control subjects. In detrended fluctuation analysis (DFA), the patients had significantly lower DFAα2 in the acute stage (within 72 hours) and lower DFAα1 at 3 months and 12 months after MI. In multiscale entropy (MSE) analysis, the patients had a lower slope 5 in the acute stage, which then gradually increased during the follow-up period. The areas under the MSE curves for scale 1 to 5 (area 1–5) and 6 to 20 (area 6–20) were lower throughout the chronic stage. Area 6–20 had the greatest discriminatory power to differentiate the post-MI patients (at 1 year) from the controls. In both the net reclassification improvement and integrated discrimination improvement models, MSE parameters significantly improved the discriminatory power of the linear parameters to differentiate the post-MI patients from the controls. In conclusion, the patients with STEMI had serial changes in cardiac complexity.

Heart rhythm complexity impairment in patients undergoing peritoneal dialysis.

Cardiovascular disease is one of the leading causes of death in patients with advanced renal disease. The objective of this study was to investigate impairments in heart rhythm complexity in patients with end-stage renal disease. We prospectively analyzed 65 patients undergoing peritoneal dialysis (PD) without prior cardiovascular disease and 72 individuals with normal renal function as the control group. Heart rhythm analysis including complexity analysis by including detrended fractal analysis (DFA) and multiscale entropy (MSE) were performed. In linear analysis, the PD patients had a significantly lower standard deviation of normal RR intervals (SDRR) and percentage of absolute differences in normal RR intervals greater than 20 ms (pNN20). Of the nonlinear analysis indicators, scale 5, area under the MSE curve for scale 1 to 5 (area 1–5) and 6 to 20 (area 6–20) were significantly lower than those in the control group. In DFA anaylsis, both DFA α1 and DFA α2 were comparable in both groups. In receiver operating characteristic curve analysis, scale 5 had the greatest discriminatory power for two groups. In both net reclassification improvement model and integrated discrimination improvement models, MSE parameters significantly improved the discriminatory power of SDRR, pNN20, and pNN50. In conclusion, PD patients had worse cardiac complexity parameters. MSE parameters are useful to discriminate PD patients from patients with normal renal function.

Reversible heart rhythm complexity impairment in patients with primary aldosteronism.

Excess aldosterone secretion in patients with primary aldosteronism (PA) impairs their cardiovascular system. Heart rhythm complexity analysis, derived from heart rate variability (HRV), is a powerful tool to quantify the complex regulatory dynamics of human physiology. We prospectively analyzed 20 patients with aldosterone producing adenoma (APA) that underwent adrenalectomy and 25 patients with essential hypertension (EH). The heart rate data were analyzed by conventional HRV and heart rhythm complexity analysis including detrended fluctuation analysis (DFA) and multiscale entropy (MSE). We found APA patients had significantly decreased DFAα2 on DFA analysis and decreased area 1–5, area 6–15, and area 6–20 on MSE analysis (all p < 0.05). Area 1–5, area 6–15, area 6–20 in the MSE study correlated significantly with log-transformed renin activity and log-transformed aldosterone-renin ratio (all p < = 0.01). The conventional HRV parameters were comparable between PA and EH patients. After adrenalectomy, all the altered DFA and MSE parameters improved significantly (all p < 0.05). The conventional HRV parameters did not change. Our result suggested that heart rhythm complexity is impaired in APA patients and this is at least partially reversed by adrenalectomy.