Unravelling COVID-19 waves in Rio de Janeiro city: Qualitative insights from nonlinear dynamic analysis

Since the COVID-19 pandemic was first reported in 2019, it has rapidly spread around the world. Many countries implemented several measures to try to control the virus spreading. The healthcare system and consequently the general quality of life population in the cities have all been significantly impacted by the Coronavirus pandemic. The different waves of contagious were responsible for the increase in the number of cases that, unfortunately, many times lead to death. In this paper, we aim to characterize the dynamics of the six waves of cases and deaths caused by COVID-19 in Rio de Janeiro city using techniques such as the Poincaré plot, approximate entropy, second-order difference plot, and central tendency measures. Our results reveal that by examining the structure and patterns of the time series, using a set of non-linear techniques we can gain a better understanding of the role of multiple waves of COVID-19, also, we can identify underlying dynamics of disease spreading and extract meaningful information about the dynamical behavior of epidemiological time series. Such findings can help to closely approximate the dynamics of virus spread and obtain a correlation between the different stages of the disease, allowing us to identify and categorize the stages due to different virus variants that are reflected in the time series.

Poincaré plot can help predict the curative effect of metoprolol for pediatric postural orthostatic tachycardia syndrome

Purpose

To study whether a Poincaré plot can help predict the curative effect of metoprolol for postural orthostatic tachycardia syndrome (POTS) in children.

Methods

Pediatric patients with POTS who were administered metoprolol were retrospectively included. The collected data included general data (sex, age, height, weight, and body mass index), the manifestations and treatment (baseline orthostatic intolerance symptom score and course of metoprolol treatment), vital signs (supine heart rate [HR], supine blood pressure, and increased HR during the standing test), HR variability indexes (standard deviation of normal-to-normal intervals [SDNN]; standard deviation of the averages of normal-to-normal intervals [SDANN]; mean standard deviation of the NN intervals for each 5-min segment [SDNNI]; root mean square of the successive differences [rMSSD]; percentage of adjacent NN intervals that differ by >50 ms [pNN50]; triangular index; ultra-low [ULF], very low [VLF], low [LF], and high frequency [HF]; total power [TP]; and LF/HF ratio), and graphical parameters of the Poincaré plot (longitudinal axis [L], transverse axis [T], and L/T). Receiver operator characteristic curves were used to calculate the predictive function of the indexes with significant differences between patients who responded and those who did not. The index combination with the highest predictive value was obtained through series-parallel analysis.

Results

Overall, 40 responders and 23 non-responders were included. The L and T in the Poincaré plots and rMSSD, pNN50, HF, and TP of the HR variability data were significantly lower in participants who responded to metoprolol than in participants who did not (p < 0.001). The L/T of participants who responded to metoprolol was greater than that of non-responders (p < 0.001). Moreover, we noted a strong correlation between every two indexes among L, T, rMSSD, pNN50, HF, TP, and L/T (p < 0.05). T < 573.9 ms combined with L/T > 2.9 had the best performance for predicting the effectiveness of metoprolol, with a sensitivity of 85.0%, specificity of 82.6%, and accuracy of 84.1%.

Conclusion

In the Poincaré plot, a T < 573.9 ms combined with an L/T > 2.9 helps predict good outcomes of using metoprolol to treat pediatric POTS.

Analysis of Poincaré plot derived from five-minute electrocardiography in dogs with myxomatous mitral valve disease

Background: Evaluation of heart rate variability (HRV) is used for risk assessment in a variety of cardiac diseases including myxomatous mitral valve degeneration (MMVD).Objectives: To compare the geometric analysis of HRV using visual patterns of Poincaré plot among different classes of MMVD in dogs and to analyse the differences in beat-to-beat variability using tachograms and sequential Poincaré plots among different shapes.Animals and methods: Healthy and MMVD dogs were retrospectively reviewed. Five-minute ECG data was used to create Poincaré plots and shapes were compared among groups. Furthermore, a sub-analysis of 50 consecutive R-R intervals was performed. Pearson Chi-Square with adjusted standardized residuals was used to compare the categorical data between groups.Results: Fifteen healthy dogs and 157 dogs with MMVD were included in the study. Normal and B1 groups showed a predominance of triangular shape (73% and 60% respectively; p < 0.05). In B2 group the predominant shape was comet (40%; p < 0.05) while comet and torpedo were predominant in Ca group (41% and 36% respectively; p < 0.05). Visual geometric analysis revealed a lower dispersion of the cloud clustering towards the left lower corner of the plot with MMVD progression. Diamond and triangle revealed a lower mean heart rate compared to comet and torpedo shapes (P < 0.01). Interclass correlation between 3 observers was 0.906 (95% CI of 0.8 - 0.96).Conclusions: Poincaré plot shape changes with MMVD progression suggesting that geometrical analysis of HRV in dogs with cardiac conditions could be a useful tool in the risk assessment and further studies are warranted.

An assessment of heart rate and blood pressure asymmetry in the diagnosis of vasovagal syncope in females

Introduction: Heart Rate Asymmetry (HRA) describes a phenomenon of differences between accelerations and decelerations in human heart rate. Methods used for HRA assessment can be further implemented in the evaluation of asymmetry in blood pressure variations (Blood Pressure Asymmetry-BPA). Methods: We have analyzed retrospectively the series of heartbeat intervals extracted from ECG and beat-to-beat blood pressure signals from 16 vasovagal patients (age: 32.1 ± 13.3; BMI: 21.6 ± 3.8; all female) and 19 healthy subjects (age: 34.6 ± 7.6; BMI: 22.1 ± 3.4; all female) who have undergone tilt test (70°). Asymmetry was evaluated with Poincaré plot-based methods for 5 min recordings from supine and tilt stages of the test. The analyzed biosignals were heart rate (RR), diastolic (dBP) and systolic Blood Pressure (sBP) and Pulse Pressure (PP). In the paper we explored the differences between healthy and vasovagal women. Results: The changes of HRA indicators between supine and tilt were observed only in the control group (Porta Index p = 0.026 and Guzik Index p = 0.005). No significant differences in beat-to-beat variability (i.e. spread of points across the line of identity in Poincaré plot-SD1) of dBP was noted between supine and tilt in the vasovagal group (p = 0.433 in comparison to p = 0.014 in healthy females). Moreover, in vasovagal patients the PP was significantly different (supine: 41.47; tilt: 39.27 mmHg) comparing to healthy subjects (supine: 35.87; tilt: 33.50 mmHg) in supine (p = 0.019) and in tilt (p = 0.014). Discussion: Analysis of HRA and BPA represents a promising method for the evaluation of cardiovascular response to orthostatic stressors, however currently it is difficult to determine a subject's underlying health condition based only on these parameters.

Detecting Metabolic Thresholds from Nonlinear Analysis of Heart Rate Time Series: A Review

Heart rate time series are widely used to characterize physiological states and athletic performance. Among the main indicators of metabolic and physiological states, the detection of metabolic thresholds is an important tool in establishing training protocols in both sport and clinical fields. This paper reviews the most common methods, applied to heart rate (HR) time series, aiming to detect metabolic thresholds. These methodologies have been largely used to assess energy metabolism and to identify the appropriate intensity of physical exercise which can reduce body weight and improve physical fitness. Specifically, we focused on the main nonlinear signal evaluation methods using HR to identify metabolic thresholds with the purpose of identifying a method which can represent a useful tool for the real-time settings of wearable devices in sport activities. While the advantages and disadvantages of each method, and the possible applications, are presented, this review confirms that the nonlinear analysis of HR time series represents a solid, robust and noninvasive approach to assess metabolic thresholds.

Poincaré Plot Nonextensive Distribution Entropy: A New Method for Electroencephalography (EEG) Time Series

As a novel form of visual analysis technique, the Poincaré plot has been used to identify correlation patterns in time series that cannot be detected using traditional analysis methods. In this work, based on the nonextensive of EEG, Poincaré plot nonextensive distribution entropy (NDE) is proposed to solve the problem of insufficient discrimination ability of Poincaré plot distribution entropy (DE) in analyzing fractional Brownian motion time series with different Hurst indices. More specifically, firstly, the reasons for the failure of Poincaré plot DE in the analysis of fractional Brownian motion are analyzed; secondly, in view of the nonextensive of EEG, a nonextensive parameter, the distance between sector ring subintervals from the original point, is introduced to highlight the different roles of each sector ring subinterval in the system. To demonstrate the usefulness of this method, the simulated time series of the fractional Brownian motion with different Hurst indices were analyzed using Poincaré plot NDE, and the process of determining the relevant parameters was further explained. Furthermore, the published sleep EEG dataset was analyzed, and the results showed that the Poincaré plot NDE can effectively reflect different sleep stages. The obtained results for the two classes of time series demonstrate that the Poincaré plot NDE provides a prospective tool for single-channel EEG time series analysis.

Poincaré Plot Is Useful for Distinguishing Vasovagal Syncope From Postural Tachycardia Syndrome in Children

OBJECTIVES

To explore the role of the Poincaré plot derived from a 24-hour Holter recording in distinguishing vasovagal syncope (VVS) from postural tachycardia syndrome (POTS) in pediatric patients.

MATERIALS AND METHODS

Pediatric patients with VVS or POTS, hospitalized in Peking University First Hospital between January 2012 and December 2018, were included in a derivation study. The transverse axis (T), longitudinal axis (L), T/L ratio, product T × L, distance between the origin and the proximal end of the longitudinal axis (pro-D), and distance between the origin and distal end of the longitudinal axis (dis-D) of the Poincaré plot were compared between the VVS and POTS groups, and the differential diagnostic performance of the above-mentioned graphic parameters was evaluated using receiver operating characteristic curve analysis. A validation study was conducted in pediatric patients hospitalized between January 2019 and December 2020.

RESULTS

In school-aged children, the T, L, T/L, T × L, and dis-D values of patients with VVS were greater than those of patients with POTS; in adolescents, the T, T/L, T × L, and pro-D values of patients with VVS were greater than those of patients with POTS. Using a T/L cut-off value of 0.3 to distinguish between the two diseases, the sensitivity and specificity were 91.0 and 90.5%, respectively, for the total participants; 91.6 and 88.9%, respectively, for the school-aged children; and 82.1 and 95.7%, respectively, for the adolescents. In the validation study, a T/L cut-off value of 0.3 yielded an accuracy, sensitivity, and specificity of 81.8, 87.2, and 77.6%, respectively, in the total participants; 76.5, 82.6, and 71.4%, respectively, in the school-aged children; and 89.2, 93.8, and 85.7%, respectively, in the adolescents, in distinguishing VVS from POTS validated by clinical diagnosis.

CONCLUSIONS

The graphic parameters of the Poincaré plot are significantly different between VVS and POTS in pediatric patients, and the T/L of the Poincaré plot may be a useful measure to help differentiate VVS from POTS in children and adolescents.

Predicting Post-operative Blood Inflammatory Biomarkers Using Pre-operative Heart Rate Variability in Patients With Cervical Cancer

Blood inflammatory biomarkers, including the neutrophil-to-lymphocyte ratio (NLR), the lymphocyte-to-monocyte ratio (LMR), and the platelet-to-lymphocyte ratio (PLR), play a significant role in determining the prognosis of patients with cervical cancer (CC). Currently, no methods are available to predict these indexes pre-operatively. Cardiac autonomic function is determined based on the heart rate variability (HRV), which is also associated with a progressive inflammatory response and cancer. Thus, the main aim of this study was to evaluate the feasibility of using pre-operative HRV parameters in CC patients to predict post-operative blood inflammation biomarkers as a means of determining prognosis. Between 2020 and 2021, 56 patients who were diagnosed with CC and then underwent hysterectomy surgery at the Department of Gynecologic Oncology, First Affiliated Hospital, Bengbu Medical College were enrolled in this study. Five-minute electrocardiogram data were collected 1 day before the operation for analysis of HRV parameters, including frequency domain parameters (LF, HF, and LF/HF) and Poincaré plot parameters (SD1, SD2, and SD2/SD1). Venous blood was collected 2 days post-operatively and inflammatory biomarkers were evaluated, with the NLR, LMR, and PLR determined. Pre-operative SD2 was significantly associated with post-operative PLR, with each 1-unit increase in SD2 decreasing the PLR value by 2.4 ± 0.9 (P < 0.05). Besides, LF/HF was significantly correlated with NLR, with each 1-unit increase in LF/HF increasing the NLR value by 1.1 ± 0.5 (P < 0.05). This association was independent of patient age and body mass index. These results suggest that the pre-operative autonomic nervous system plays a role in the regulation of post-operative cancer inflammation and that pre-operative HRV parameters can potentially predict post-operative inflammation and facilitate clinical treatment decisions.

Research on physical activity variability and changes of metabolic profile in patients with prediabetes using Fitbit activity trackers data

BACKGROUND

Monitoring physical activity with consumers wearables is one of the possibilities to control a patient's self-care and adherence to recommendations. However, clinically approved methods, software, and data analysis technologies to collect data and make it suitable for practical use for patient care are still lacking.

OBJECTIVE

This study aimed to analyze the potential of patient physical activity monitoring using Fitbit physical activity trackers and find solutions for possible implementation in the health care routine.

METHODS

Thirty patients with impaired fasting glycemia were randomly selected and participated for 6 months. Physical activity variability was evaluated and parameters were calculated using data from Fitbit Inspire devices.

RESULTS

Changes in parameters were found and correlation between clinical data (HbA1c, lipids) and physical activity variability were assessed. Better correlation with variability than with body composition changes shows the potential to include nonlinear variability parameters analysing physical activity using mobile devices. Less expressed variability shows better relationship with control of prediabetic and lipid parameters.

CONCLUSIONS

Evaluation of physical activity variability is essential for patient health, and these methods used to calculate it is an effective way to analyze big data from wearable devices in future trials.

Single channel photoplethysmography-based obstructive sleep apnea detection and arrhythmia classification

BACKGROUND

Simplified and easy-to-use monitoring approaches are crucial for the early diagnosis and prevention of obstructive sleep apnea (OSA) and its complications.

OBJECTIVE

In this study, the OSA detection and arrhythmia classification algorithms based on single-channel photoplethysmography (PPG) are proposed for the early screening of OSA.

METHODS

Thirty clinically diagnosed OSA patients participated in this study. Fourteen features were extracted from the PPG signals. The relationship between the number of features as inputs of the support vector machine (SVM) and performance of apnea events detection was evaluated. Also, a multi-classification algorithm based on the modified Hausdorff distance was proposed to recognize sinus rhythm and four arrhythmias highly related with SA.

RESULTS

The feature set composed of meanPP, SDPP, RMSSD, meanAm, and meank1 could provide a satisfactory balance between the performance and complexity of the algorithm for OSA detection. Also, the arrhythmia classification algorithm achieves the average sensitivity, specificity and accuracy of 83.79%, 95.91% and 93.47%, respectively in the classification of all four types of arrhythmia and regular rhythm.

CONCLUSION

Single channel PPG-based OSA detection and arrhythmia classification in this study can provide a feasible and promising approach for the early screening and diagnosis of OSA and OSA-related arrhythmias.

Skin temperature variability is an independent predictor of survival in patients with cirrhosis

Background

Cirrhosis is a disease with multisystem involvement. It has been documented that patients with cirrhosis exhibit abnormal patterns of fluctuation in their body temperature. However, the clinical significance of this phenomenon is not well understood. The aim of this study was to determine if temperature variability analysis can predict survival in patients with cirrhosis.

Methods

Thirty eight inpatients with cirrhosis were enrolled in the study. Wireless temperature sensors were used to record patients’ proximal skin temperature for 24 hr. The pattern of proximal temperature fluctuation was assessed using the extended Poincaré plot to measure short‐term and long‐term proximal temperature variability (PTV). Patients were followed up for 12 months, and information was collected on the occurrence of death/liver transplantation.

Results

During the follow‐up period, 15 patients (39%) died or underwent transplantation for hepatic decompensation. Basal proximal skin temperature absolute values were comparable in survivors and nonsurvivors. However, nonsurvivors showed a significant reduction in both short‐term and long‐term HRV indices. Cox regression analysis showed that both short‐term and long‐term PTV indices could predict survival in these patients. However, only measures of short‐term PTV were shown to be independent of the severity of hepatic failure in predicting survival. Finally, the prognostic value of short‐term PTV was also independent of heart rate variability, that is, a measure of autonomic dysfunction.

Conclusion

Changes in the pattern of patients’ temperature fluctuations, rather than their absolute values, hold key prognostic information, suggesting that impaired thermoregulation may play an important role in the pathophysiology of cirrhosis.

Lorenz Plot Analysis in Dogs with Sinus Rhythm and Tachyarrhythmias

Simple Summary

The Lorenz plot (LP) is a geometrical method to assess the dynamics of heart rate variability. It consists of a two-dimensional Cartesian coordinate system derived from electrocardiographic monitoring, in which each recorded R-R interval is plotted as a function of the previous R-R interval, and the values of each pair of successive R-R interval define a dot in the plot. The resultant clusters of dots can be evaluated quantitatively and qualitatively, and categorized into distinct geometrical patterns. In humans, several studies have demonstrated that the analysis of LP patterns (LPPs) has the potential to speed-up and improve the accuracy of arrhythmia detection and differentiation, especially in patients with tachyarrhythmias. As data on LP analysis are limited in dogs, this study describes the graphic features of LP derived from Holter recordings obtained in dogs with sinus rhythm and tachyarrhythmias, and analyzes the usefulness of LPP recognition in this species. We sought to evaluate if distinct cardiac rhythms imprint distinct and reproducible LPPs in dogs, as previously described in humans, and if each LLP can be used as a sensitive and specific indicator of a particular cardiac rhythm in this species.

Abstract

The Lorenz plot (LP), a graphical representation of heart rate variability, has been poorly studied in dogs to date. The present study aimed to describe the graphic features of LP in dogs with sinus rhythm (SR) and tachyarrhythmias, and to analyze the usefulness of its pattern recognition. One hundred and nineteen canine Holter recordings were retrospectively evaluated. Cardiac rhythms were classified as: SR; SR with frequent (>100) premature ectopies (atrial, SR-APCs; ventricular, SR-VPCs; atrial and ventricular, SR-APCs-VPCs); atrial fibrillation (AF); and AF with frequent VPCs (AF-VPCs). Lorenz plots were studied qualitatively and quantitatively, and classified by distinct LP patterns (LPPs). Repeatability and reproducibility of LPP classification and diagnostic value were determined. Recordings included: 48 SR, 9 SR-APCs, 35 SR-VPCs, 5 SR-APCs-VPCs, 4 AF, and 18 AF-VPCs. Ten LPPs were identified: comet (n = 12), torpedo (n = 3), Y-shaped (n = 6), diamond (n = 10), diamond with a central silent zone (n = 17), double side-lobe (DSL) (n = 47), triple side-lobe (n = 1), quadruple side-lobe (n = 2), fan (n = 18), and fan with DSL (n = 3). Repeatability and reproducibility of LPP classification were excellent. The DSL pattern was both highly sensitive (91.3%) and specific (94.5%) for SR with frequent premature ectopies, either APCs, or VPCs, or both. The remaining LPPs had lower diagnostic value (high specificity but low sensitivity). Distinct rhythms imprint distinct and reproducible LPPs in dogs. The majority of canine LPPs are specific but insensitive indicators of SR and tachyarrhythmias.

Heart Rate Asymmetry Analysis During Head-Up Tilt Test in Healthy Men

The purpose of this study is to assess the cardiovascular system response to orthostatic stress in a group of 133 healthy men using heart rate asymmetry (HRA) methods. HRA is a feature of variability in human heart rate which is dependent upon external and internal body conditions. The initial phases of head-up tilt test (HUTT), namely, supine and tilt, were chosen as the external body affecting factors. Various calculation methods of HRA, such as Porta's index (PI), Guzik's index (GI), and its variance based components, were used to assess the heart rate variability (HRV) and its asymmetry. We compared 5-min ECG recordings from both supine and tilt phases of HUT test. Short-term HRA was observed in 54.1% of men in supine phase and 65.4% of men in tilt phase. The study revealed significant increase of GI (from 0.50 to 0.52, p < 0.001) in the tilt phase as well as significant changes in HRV descriptors between HUTT phases. Our results showed that the variability of human heart rate and its asymmetry are sensitive to orthostatic stress. The study of short-term HRA is a potential additional tool to increase sensitivity in conditions where HUTT is a diagnostic tool, such as vasovagal syncope.

Insights into sinus arrhythmia of the dog: Acetylcholine perfusion of canine right atrium results in beat-to-beat patterns that mimic sinus arrhythmia supporting exit block in the sinoatrial conduction pathways

Sinus arrhythmia of the dog is unique because of the pronounced alternating beat-to-beat intervals. The clustering of these short (faster rates) and long (slower rates) intervals is not just influenced by autonomic input from breathing; sinus arrhythmia can persist in the panting or apneic dog. The multiplicity of central and peripheral influences on the sinus node complicates the unraveling of the mechanisms of sinus arrhythmia. Studies of the sinus node suggest that acetylcholine can slow cellular depolarization and block sinoatrial conduction. Electrocardiographic monitoring of the dog supports this notion in that abrupt bifurcation into short and long intervals develop at lower heart rates. We sought to determine whether this phenomenon could be recapitulated in canine atrial preparations perfused with acetylcholine and whether selective pharmacologic blockade of the voltage and calcium clocks could provide insight into its mechanism. Spontaneous beat to beat (A-A) intervals were obtained from monophasic action potential recordings of perfused canine right atrial preparations before and during perfusion with acetylcholine (2-5 μM). The calcium clock was blocked with ryanodine (2-3 μM). The membrane clock was blocked with diltiazem hydrochloride (I_Ca,L blocker; 0.25 μM) and ZD7288 (I_f blocker; 3 μM). Hyperpolarization was hindered by blockade of I_K,Ado/I_K,Ach with tertiapin Q (100 nM) before and during acetylcholine perfusion. Acetylcholine resulted in beat clusters similar to those seen in sinus arrhythmia of the dog. Beat clusters were consistent with intermittent 2:1 and 3:1 sinoatrial conduction block. Tertiapin Q abolished this patterning suggesting a role of I_K,Ado/I_K,ACh in the mechanism of these acetylcholine-induced beat-to-beat patterns.

Poincaré Plot Area of Gamma-Band EEG as a Measure of Emergence From Inhalational General Anesthesia

The Poincaré plot obtained from electroencephalography (EEG) has been used to evaluate the depth of anesthesia. A standalone EEG Analyzer application was developed; raw EEG signals obtained from a bispectral index (BIS) monitor were analyzed using an on-line monitoring system. Correlations between Poincaré plot parameters and other measurements associated with anesthesia depth were evaluated during emergence from inhalational general anesthesia. Of the participants, 20 were adults anesthetized with sevoflurane (adult_{_SEV}), 20 were adults anesthetized with desflurane (adult_{_DES}), and 20 were pediatric patients anesthetized with sevoflurane (ped_{_SEV}). EEG signals were preprocessed through six bandpass digital filters (f0: 0.5–47 Hz, f1: 0.5–8 Hz, f2: 8–13 Hz, f3: 13–20 Hz, f4: 20–30 Hz, and f5: 30–47 Hz). The Poincaré plot-area ratio (PP_AR = PP_{A_fx}/PP_{A_f0}, fx = f1∼f5) was analyzed at five frequency ranges. Regardless of the inhalational anesthetic used, there were strong linear correlations between the logarithm of PP_AR at f5 and BIS (R² = 0.67, 0.79, and 0.71, in the adult_{_SEV}, adult_{_DES}, and ped_{_SEV} groups, respectively). As an additional observation, a part of EMG activity at the gamma range of 30–47 Hz probably influenced the calculations of BIS and PP_{AR_f5} with a non-negligible level. The logarithm of PP_AR in the gamma band was most sensitive to state changes during the emergence process and could provide a new non-proprietary parameter that correlates with changes in BIS during measurement of anesthesia depth.

Optimizing single-chamber pacing in dogs Part 1: Rate determinations, rate interventions and hysteresis

Determining ideal pacing rates to meet physiological needs and optimizing programming to prevent unnecessary right ventricular pacing in dogs requires an understanding of heart rate profiles and applicable pacing technology. The heart rate and rhythm of the dog is complex necessitating investigation of rate requirements of activity and circadian influences. Overlaying this information are a multiplicity of other factors such as age, breed, temperament, cardiovascular disease and underlining rhythm disorders that contribute to the difficulty in making general conclusions. However, all such information permits better implementation of programming options with the goal of better outcomes. In this review (Part 1 of a two-part review) instantaneous heart rate, rolling average heart rate, simple average heart rate, heart rate tachograms, RR interval tachograms (2D, 3D and dynamic), and Poincaré plots (2D, 3D and dynamic) are discussed as they apply to decisions in the determination and examination of pacing rates for dogs programmed in the VVI pacing mode (Ventricular paced, Ventricular sensed, Inhibited pacing). The applicable pacing operations available for three pacemaker companies are reviewed (Abbott, Biotronik/Dextronix, and Medtronic). The programmable options considered include: slowest pacing rate without additional features to extend the pacing interval, sleep/rest rate preferences, hysteresis to lengthen pacing interval following intrinsic beats, and intermittent increases in pacing following abrupt loss of intrinsic rhythm. Recommendations are suggested for follow-up of individual dogs with examination of pacing statistics and Holter monitoring.

Optimizing single-chamber pacing in dogs. Part 2: Rate adaptive pacing

Proper programming of pacemakers for dogs in the rate adaptive mode requires an understanding of the rate requirements for each individual and the interplay of programmable features. The specific advantages and disadvantages of the rate adaptive mode should be considered on a case by case basis. Fundamentally, two components are linked in the implementation of rate adaptive pacing: (1) sensing the need for a change in rate and (2) responding with the appropriate alteration in pacing rate. The programming interaction of these two components are interdependent and affected by the rates programmed. These features may be adjusted manually or automatically. In this review (Part 2 of a two-part review) the considerations required to program each aspect that optimizes the pacing rate profile are reviewed. These include the lower rate, upper sensor rate, activities of daily life rate, sensor threshold, acceleration and deceleration, slope, activities of daily life zone, exertion zone, automatic versus manual adjustments and closed loop stimulation. The programming features of pacemakers manufactured by three companies are summarized (Abbott, formerly St. Jude; Biotronik/Dextronix; Medtronic). Means of assessing the success of pacemaker programing is examined through examples of pacemaker data, Holter analysis, Poincaré plots and tachograms. Finally, the questions and considerations for rate adaptive pacing in dogs that demand investigation are proposed.

Resting Heart Rate Variability Is Associated With Subsequent Orthostatic Hypotension: Comparison Between Healthy Older People and Patients With Rapid Eye Movement Sleep Behavior Disorder

Background: Orthostatic hypotension (OH) caused by autonomic dysfunction is a common symptom in older people and patients with idiopathic rapid eye movement sleep behavior disorder (iRBD). The orthostatic challenge test is a standard autonomic function test that measures a decrease of blood pressure during a postural change from supine to standing positions. Although previous studies have reported that changes in heart rate variability (HRV) are associated with autonomic dysfunction, no study has investigated the relationship between HRV before standing and the occurrence of OH in an orthostatic challenge test. This study aims to examine the connection between HRV in the supine position and the occurrence of OH in an orthostatic challenge test. Methods: We measured the electrocardiograms of patients with iRBD and healthy older people during an orthostatic challenge test, in which the supine and standing positions were held for 15 min, respectively. The subjects were divided into three groups: healthy controls (HC), OH-negative iRBD [OH (-) iRBD], and OH-positive iRBD [OH (+) iRBD]. HRV measured in the supine position during the test were calculated by time-domain analysis and Poincaré plots to evaluate the autonomic dysfunction. Results: Forty-two HC, 12 OH (-) iRBD, and nine OH (+) iRBD subjects were included. HRV indices in the OH (-) and the OH (+) iRBD groups were significantly smaller than those in the HC group. The multivariate logistic regression analysis for OH identification for the iRBD groups showed the model whose inputs were the HRV indices, i.e., standard deviation 2 (SD2) and the percentage of adjacent intervals that varied by more than 50 ms (pNN50), had a receiver operating characteristic curve with area under the curve of 0.840, the sensitivity to OH (+) of 1.000, and the specificity to OH (-) of 0.583 (p = 0.023). Conclusions: This study showed the possibility that short-term HRV indices in the supine position would predict subsequent OH in iRBD patients. Our results are of clinical importance in terms of showing the possibility that OH can be predicted using only HRV in the supine position without an orthostatic challenge test, which would improve the efficiency and safety of testing.

Consciousness Detection in a Complete Locked-in Syndrome Patient through Multiscale Approach Analysis

Completely locked-in state (CLIS) patients are unable to speak and have lost all muscle movement. From the external view, the internal brain activity of such patients cannot be easily perceived, but CLIS patients are considered to still be conscious and cognitively active. Detecting the current state of consciousness of CLIS patients is non-trivial, and it is difficult to ascertain whether CLIS patients are conscious or not. Thus, it is important to find alternative ways to re-establish communication with these patients during periods of awareness, and one such alternative is through a brain-computer interface (BCI). In this study, multiscale-based methods (multiscale sample entropy, multiscale permutation entropy and multiscale Poincaré plots) were applied to analyze electrocorticogram signals from a CLIS patient to detect the underlying consciousness level. Results from these different methods converge to a specific period of awareness of the CLIS patient in question, coinciding with the period during which the CLIS patient is recorded to have communicated with an experimenter. The aim of the investigation is to propose a methodology that could be used to create reliable communication with CLIS patients.

Linear and nonlinear analyses of normal and fatigue heart rate variability signals for miners in high-altitude and cold areas

BACKGROUND AND OBJECTIVE

Fatigue is an important cause of operational errors, and human errors are the main cause of accidents. This study is an exploratory study in China. Field tests were conducted on heart rate variability (HRV) parameters and physiological indicators of fatigue among miners in high-altitude, cold and low-oxygen areas. This paper studies heart activity patterns during work fatigue in miners.

METHODS

Fatigue affects both the sympathetic and parasympathetic nervous systems, and it is expressed as an abnormal pattern of HRV parameters. Thirty miners were selected as subjects for a field test, and HRV was extracted from 60 groups of electrocardiography (ECG) datasets as basic signals for fatigue analysis. Then, we analyzed the HRV signals of the miners using linear (time domain and frequency domain) and nonlinear dynamics (Poincaré plot and sample entropy (SampEn)), and a Pearson's correlation coefficient analysis and t-tests were performed on the measured indices.

RESULTS

The results showed that the time-domain indices (SDNN, RMSSD, SDSD, pNN50, RRn, heart rate (HR), R-wave humps (RH)) and the coefficient of variation (CV)) and the frequency-domain indices (low frequency/high frequency (LF/HF), LFnorm and HFnorm) clearly changed after fatigue. These features were selected using a Poincaré plot, sample entropy, Pearson's correlation coefficient and a t-test for further analysis. The fatigue characteristics and sensitivity parameters of miners in a high-altitude, cold and hypoxic environment were obtained.

CONCLUSIONS

This study provides deep insight into the use of linear and nonlinear fatigue characteristics to effectively and reliably identify miner fatigue. Furthermore, the study provides a reference for clinical studies of acute mountain sickness in high-altitude, cold and hypoxic environments.

How to Use Heart Rate Variability: Quantification of Vagal Activity in Toddlers and Adults in Long-Term ECG

Recent developments in noninvasive electrocardiogram (ECG) monitoring with small, wearable sensors open the opportunity to record high-quality ECG over many hours in an easy and non-burdening way. However, while their recording has been tremendously simplified, the interpretation of heart rate variability (HRV) data is a more delicate matter. The aim of this paper is to supply detailed methodological discussion and new data material in order to provide a helpful notice of HRV monitoring issues depending on recording conditions and study populations. Special consideration is given to the monitoring over long periods, across periods with different levels of activity, and in adults versus children. Specifically, the paper aims at making users aware of neglected methodological limitations and at providing substantiated recommendations for the selection of appropriate HRV variables and their interpretation. To this end, 30-h HRV data of 48 healthy adults (18–40 years) and 47 healthy toddlers (16–37 months) were analyzed in detail. Time-domain, frequency-domain, and nonlinear HRV variables were calculated after strict signal preprocessing, using six different high-frequency band definitions including frequency bands dynamically adjusted for the individual respiration rate. The major conclusion of the in-depth analyses is that for most applications that implicate long-term monitoring across varying circumstances and activity levels in healthy individuals, the time-domain variables are adequate to gain an impression of an individual’s HRV and, thus, the dynamic adaptation of an organism’s behavior in response to the ever-changing demands of daily life. The sound selection and interpretation of frequency-domain variables requires considerably more consideration of physiological and mathematical principles. For those who prefer using frequency-domain variables, the paper provides detailed guidance and recommendations for the definition of appropriate frequency bands in compliance with their specific recording conditions and study populations.

Premature Atrial and Ventricular Contraction Detection using Photoplethysmographic Data from a Smartwatch

We developed an algorithm to detect premature atrial contraction (PAC) and premature ventricular contraction (PVC) using photoplethysmographic (PPG) data acquired from a smartwatch. Our PAC/PVC detection algorithm is composed of a sequence of algorithms that are combined to discriminate various arrhythmias. A novel vector resemblance method is used to enhance the PAC/PVC detection results of the Poincaré plot method. The new PAC/PVC detection algorithm with our automated motion and noise artifact detection approach yielded a sensitivity of 86% for atrial fibrillation (AF) subjects while the overall sensitivity was 67% when normal sinus rhythm (NSR) subjects were also included. The specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy values for the combined data consisting of both NSR and AF subjects were 97%, 81%, 94% and 92%, respectively, for PAC/PVC detection combined with our automated motion and noise artifact detection approach. Moreover, when AF detection was compared with and without PAC/PVC, the sensitivity and specificity increased from 94.55% to 98.18% and from 95.75% to 97.90%, respectively. For additional independent testing data, we used two datasets: a smartwatch PPG dataset that was collected in our ongoing clinical study, and a pulse oximetry PPG dataset from the Medical Information Mart for Intensive Care III database. The PAC/PVC classification results of the independent testing on these two other datasets are all above 92% for sensitivity, specificity, PPV, NPV, and accuracy. The proposed combined approach to detect PAC and PVC can ultimately lead to better accuracy in AF detection. This is one of the first studies involving detection of PAC and PVC using PPG recordings from a smartwatch. The proposed method can potentially be of clinical importance as this enhanced capability can lead to fewer false positive detections of AF, especially for those NSR subjects with frequent episodes of PAC/PVC.

Cardiac surgical outcome prediction by blood pressure variability indices Poincaré plot and coefficient of variation: a retrospective study

Background

Recent literature suggests a significant association between blood pressure variability (BPV) and postoperative outcomes after cardiac surgery. However, its outcome prediction ability remains unclear. Current prediction models use static preoperative patient factors. We explored the ability of Poincaré plots and coefficient of variation (CV) by measuring intraoperative BPV in predicting adverse outcomes.

Methods

In this retrospective, observational, cohort study, 3687 adult patients (> 18 years) undergoing cardiac surgery requiring cardio-pulmonary bypass from 2008 to 2014 were included. Blood pressure variability was computed by Poincare plots and CV. Standard descriptors (SD) SD1, SD2 were measured with Poincare plots by ellipse fitting technique. The outcomes analyzed were the 30-day mortality and postoperative renal failure. Logistic regression models adjusted for preoperative and surgical factors were constructed to evaluate the association between BPV parameters and outcomes. C-statistics were used to analyse the predictive ability.

Results

Analysis found that, 99 (2.7%) patients died within 30 days and 105 (2.8%) patients suffered from in-hospital renal failure. Logistic regression models including BPV parameters (standard descriptors from Poincare plots and CV) performed poorly in predicting postoperative 30-day mortality and renal failure [Concordance(C)-Statistic around 0.5]. They did not add any significant value to the standard STS risk score [C-statistic: STS alone 0.7, STS + BPV parmeters 0.7].

Conclusions

In conclusion, BP variability computed from Poincare plots and CV were not predictive of mortality and renal failure in cardiac surgical patients. Patient comorbid conditions and other preoperative factors are still the gold standard for outcome prediction. Future directions include analysis of dynamic parameters such as complexity of physiological signals in identifying high risk patients and tailoring management accordingly.

Geometry of the Poincaré plot can segregate the two arms of autonomic nervous system - A hypothesis

Autonomic Nervous System (ANS) operates to achieve the optimum physiological functioning and maintains homeostasis in a tonic and continuous manner. Evaluation of ANS profile is crucial in assessing autonomic dysfunction. Conventional ANS evaluation procedures fail to capture minute dynamic alterations of ANS activities. The ANS output pattern is appropriately reflected in the fine alteration of the resting heart rate (HR). HR is a non-stationary variable, results from the dynamic interplay between the multiple physiologic mechanisms. The control of cardiac rate or the chronotropic regulation of heart is considered as a coupled network of oscillators, each representing a specific facet of the cardiovascular reflex. The slower vasomotor oscillation via sympathetic system is combined with rapid respiratory oscillation by parasympathetic system to modulate the intrinsic oscillation pattern of the SA Node. Heart Rate Variability (HRV) is used to understand the autonomic influence on cardiovascular system in health and disease. Fourier decomposition of HRV offers us mainly two different frequency components. High frequency (HF) variation indicates parasympathetic variability due to respiration and Low frequency (LF) mainly implicates tonic sympathetic influence, due to slower vasomotor modulation of heart rate. However, different studies show conflicting results and direct recording of sympathetic nerve activity also failed to correlate with LF power in either healthy subjects or in patients with increased cardiac sympathetic drive. A scatter-plot where each R-R interval is plotted against the preceding R-R interval forms a distributed elliptic point cloud in two dimensional plane. The phase space realization of this plot with dimension two and delay one is referred to as Poincaré plot analysis, an emerging quantitative-visual technique where the shape of the plot is categorized into different functional classes. The plot provides summary as well as detailed beat-to-beat information of the heart. This plot can be extended to three dimensions and with multi-lag, offering more insight and information. A mathematical expression was developed by an interventional study by Toichi et al., using pharmacological blockers during different physiological variables that calculated the lengths of transverse and longitudinal axes of the Poincaré plot to derive two quantitative expressions of sympathetic and vagal influence on HRV: 'cardiac sympathetic index' (CSI)) and 'cardiac vagal index' (CVI). In the present study, we emulate Poincaré plot patterns seen in normal range of sympatho-vagal balances and also in Diabetes Mellitus (DM), known to cause autonomic dysfunction. The emerging pattern of R-R interval time series would provide valuable insight into the altered temporal dynamics and also extract crucial features embedded within. DM is a major public health crisis globally and particularly in Indian population. We hypothesize that, CSI and CVI will effectively segregate the two arms of ANS and can be utilized as an effective evaluation tool to explore the disease status in patients of Diabetes Mellitus. We also propose that, the dynamics of fluctuations in physiological rhythms that exhibit long-term correlation and memory, can also be explored and expressed quantitatively by incorporating various degrees of 'lag' in these recurrence plots.

Hand grip strength variability during serial testing as an entropic biomarker of aging: a Poincaré plot analysis

Background

The Poincaré plot method can be used for both qualitative and quantitative assessment of self-similarity in usually periodic functions, hence the idea of applying it to the study of homeostasis of living organisms. From the analysis of numerous scientific data, it can be concluded that hand functionality can be correlated with the state of the human body as a biological system exposed to various forms of ontogenetic stress.

Methods

We used the Poincaré plot method to analyze the variability of hand grip strength (HGS), as an entropic biomarker of aging, during 60 repetitive tests of the dominant and nondominant hand, in young and older healthy subjects. An observational cross-sectional study was performed on 80 young adults (18–22 years old, mean age 20.01 years) and 80 older people (65–69 years old, mean age 67.13 years), with a sex ratio of 1:1 for both groups. For statistical analysis, we applied univariate descriptive statistics and inferential statistics (Shapiro–Wilk test, Mann–Whitney U-test for independent large samples, with the determination of the effect size coefficient r, and simple linear regression. We calculated the effect of fatigue and the Poincaré indices SD₁, SD₂, SD₁/SD₂ and the area of the fitting ellipse (AFE) for the test values of each subject.

Results

The analysis of the differences between groups revealed statistically significant results for most HGS-derived indices (p ≤ 0.05), and the magnitude of the differences indicated, in most situations, a large effect size (r > 0.5). Our results demonstrate that the proposed repetitive HGS testing indicates relevant differences between young and older healthy subjects. Through the mathematical modeling of data and the application of the concept of entropy, we provide arguments supporting this new design of HGS testing.

Conclusions

Our results indicate that the variability of HGS during serial testing, which reflects complex repetitive biomechanical functions, represents an efficient indicator for differentiation between young and older hand function patterns from an entropic perspective. In practical terms, the variability of HGS, evaluated by the new serial testing design, can be considered an attractive and relatively simple biomarker to use for gerontological studies.

Applicability of a Textile ECG-Belt for Unattended Sleep Apnoea Monitoring in a Home Setting

Sleep monitoring in an unattended home setting provides important information complementing and extending the clinical polysomnography findings. The validity of a wearable textile electrocardiography (ECG)-belt has been proven in a clinical setting. For evaluation in a home setting, ECG signals and features were acquired from 12 patients (10 males and 2 females, showing an interquartile range for age of 48–59 years and for body mass indexes (BMIs) of 28.0–35.5) over 28 nights. The signal quality was assessed by artefacts detection, signal-to-noise ratio, and Poincaré plots. To assess the validity, the data were compared to previously reported data from the clinical setting. It was found that the artefact percentage was slightly reduced for the ECG-belt from 9.7% ± 14.7% in the clinical setting, to 7.5% ± 10.8% in the home setting. The signal-to-noise ratio was improved in the home setting and reached similar values to the gel electrodes in the clinical setting. Finally, it was found that for artefact percentages above 3%, Poincaré plots are instrumental to evaluate the origin of artefacts. In conclusion, the application of the ECG-belt in a home setting did not result in a reduction in signal quality compared to the ECG-belt used in the clinical setting, and thus provides new opportunities for patient pre-screening or follow-up.

Differentiation of Heart Failure Patients by the Ratio of the Scaling Exponents of Cardiac Interbeat Intervals

Heart failure (HF) is one of the most frequent heart diseases. It is usually characterized with structural and functional cardiac abnormalities followed by dysfunction of autonomic cardiac control. Current methods of heartbeat interval analysis are not capable to differentiate HF patients and some new differentiation of HF patients could be useful in the determination of the direction of their treatment. In this study, we examined potential of the ratio of the short-term and long-term scaling exponents (α 1 and α 2) to separate HF patients with similar level of reduced cardiac autonomic nervous system control and with no significant difference in age, left ventricular ejection fraction (LVEF) and NYHA class. Thirty-five healthy control subjects and 46 HF patients underwent 20 min of continuous supine resting ECG recording. The interbeat interval time series were analyzed using standardized power spectrum analysis, detrended fluctuation analysis method and standard Poincaré plot (PP) analysis with measures of asymmetry of the PP. Compared with healthy control group, in HF patients linear measures of autonomic cardiac control were statistically significantly reduced (p < 0.05), heart rate asymmetry was preserved (C up > C down, p < 0.01), and long-term scaling exponent α 2 was significantly higher. Cluster analysis of the ratio of short- and long-term scaling exponents showed capability of this parameter to separate four clusters of HF patients. Clusters were determined by interplay of presence of short-term and long-term correlations in interbeat intervals. Complementary measure, commonly accepted ratio of the PP descriptors, SD2/SD1, showed tendency toward statistical significance to separate HF patients in obtained clusters. Also, heart rate asymmetry was preserved only in two clusters. Finally, a multiple regression analysis showed that the ratio α 1/α 2 could be used as an integrated measure of cardiac dynamic with complex physiological background which, besides spectral components as measures of autonomic cardiac control, also involves breathing frequency and mechanical cardiac parameter, left ventricular ejection fraction.

Distinctions among electroconvulsion- and proconvulsant-induced seizure discharges and native motor patterns during flight and grooming: quantitative spike pattern analysis in Drosophila flight muscles

In Drosophila, high-frequency electrical stimulation across the brain triggers a highly stereotypic repertoire of spasms. These electroconvulsive seizures (ECS) manifest as distinctive spiking discharges across the nervous system and can be stably assessed throughout the seizure repertoire in the large indirect flight muscles dorsal longitudinal muscles (DLMs) to characterize modifications in seizure-prone mutants. However, the relationships between ECS-spike patterns and native motor programs, including flight and grooming, are not known and their similarities and distinctions remain to be characterized. We employed quantitative spike pattern analyses for the three motor patterns including: (1) overall firing frequency, (2) spike timing between contralateral fibers, and (3) short-term variability in spike interval regularity (CV₂) and instantaneous firing frequency (ISI^-1). This base-line information from wild-type (WT) flies facilitated quantitative characterization of mutational effects of major neurotransmitter systems: excitatory cholinergic (Cha), inhibitory GABAergic (Rdl) and electrical (ShakB) synaptic transmission. The results provide an initial glimpse on the vulnerability of individual motor patterns to different perturbations. We found marked alterations of ECS discharge spike patterns in terms of either seizure threshold, spike frequency or spiking regularity. In contrast, no gross alterations during grooming and a small but noticeable reduction of firing frequency during Rdl mutant flight were found, suggesting a role for GABAergic modulation of flight motor programs. Picrotoxin (PTX), a known pro-convulsant that inhibits GABA_A receptors, induced DLM spike patterns that displayed some features, e.g. left-right coordination and ISI^-1 range, that could be found in flight or grooming, but distinct from ECS discharges. These quantitative techniques may be employed to reveal overlooked relationships among aberrant motor patterns as well as their links to native motor programs.

The Application of the Extended Poincaré Plot in the Analysis of Physiological Variabilities

The Poincaré plot is a geometrical technique used to visualize and quantify the correlation between two consecutive data points in a time-series. Since the dynamics of fluctuations in physiological rhythms exhibit long-term correlation and memory, this study aimed to extend the Poincaré plot by calculating the correlation between sequential data points in a time-series, rather than between two consecutive points. By incorporating this so-called lag, we hope to integrate a temporal aspect into quantifying the correlation, to depict whether a physiological system holds prolonged association between events separated by time. In doing so, it attempts to instantaneously characterize the intrinsic behavior of a complex system. We tested this hypothesis on three different physiological time-series: heart rate variability in patients with liver cirrhosis, respiratory rhythm in asthma and body temperature fluctuation in patients with cirrhosis, to evaluate the potential application of the extended Poincaré method in clinical practice. When studying the cardiac inter-beat intervals, the extended Poincaré plot revealed a stronger autocorrelation for patients with decompensated liver cirrhosis compared to less severe cases using Pearson's correlation coefficient. In addition, long-term variability (known as SD2 in the extended Poincaré plot) appeared as an independent prognostic variable. This holds significance by acting as a non-invasive tool to evaluate patients with chronic liver disease and potentially facilitate transplant selection as an adjuvant to traditional criteria. For asthmatics, employing the extended Poincaré plot allowed for a non-invasive tool to differentially diagnose various classifications of respiratory disease. In the respiratory inter-breath interval analysis, the receiver operating characteristic (ROC) curve provided evidence that the extension of the Poincaré plot holds a greater advantage in the classification of asthmatic patients, over the traditional Poincaré plot. Lastly, the analysis of body temperature from patients using the extended Poincaré plot helped identify inpatients from outpatients with cirrhosis. Through these analyses, the extended Poincaré plot provided unique and additional information which could potentially make a difference in clinical practice. Conclusively, the potential use of our work lies in its possible application of predicting mortality for the organ allocation procedure in patients with cirrhosis and non-invasively distinguish between atopic and non-atopic asthma.

Effects of vagotomy on cardiovascular and heart rate variability alterations following chronic normobaric hypoxia in adult rabbits

BACKGROUND

chronic hypoxia increases basal ventilation and pulmonary vascular resistance, with variable changes in arterial blood pressure and heart rate, but it's impact on heart rate variability and autonomic regulation have been less well examined. We studied changes in arterial blood pressure, heart rate and heart rate variability (HRV) in rabbits subjected to chronic normobaric hypoxia (CNH; PB ~ 719 mmHg; F_IO₂ ~ 9.2%) for 14 days and assess the effect of autonomic control by acute bilateral vagal denervation.

RESULTS

exposure to CNH stalled animal weight gain and increased the hematocrit, without affecting heart rate or arterial blood pressure. Nevertheless, Poincaré plots of the electrocardiographic R-R intervals showed a reduced distribution parallel to the line of identity, which interpreted as reduced long-term HRV. In the frequency domain, CNH reduced the very-low- (< 0.2 Hz) and high-frequency components (> 0.8 Hz) of the R-R spectrograms and produced a prominent component in the low-frequency component (0.2-0.5 Hz) of the power spectrum. In control and CNH exposed rabbits, bilateral vagotomy had no apparent effect on the short- and long-term HRV in the Poincaré plots. However, bilateral vagotomy differentially affected higher-frequency components (> 0.8 Hz); reducing it in control animals without modifying it in CNH-exposed rabbits.

CONCLUSIONS

These results suggest that CNH exposure shifts the autonomic balance of heart rate towards a sympathetic predominance without modifying resting heart rate or arterial blood pressure.

Area asymmetry of heart rate variability signal

BACKGROUND

Heart rate fluctuates beat-by-beat asymmetrically which is known as heart rate asymmetry (HRA). It is challenging to assess HRA robustly based on short-term heartbeat interval series.

METHOD

An area index (AI) was developed that combines the distance and phase angle information of points in the Poincaré plot. To test its performance, the AI was used to classify subjects with: (i) arrhythmia, and (ii) congestive heart failure, from the corresponding healthy controls. For comparison, the existing Porta's index (PI), Guzik's index (GI), and slope index (SI) were calculated. To test the effect of data length, we performed the analyses separately using long-term heartbeat interval series (derived from >3.6-h ECG) and short-term segments (with length of 500 intervals). A second short-term analysis was further carried out on series extracted from 5-min ECG.

RESULTS

For long-term data, SI showed acceptable performance for both tasks, i.e., for task i p < 0.001, Cohen's d = 0.93, AUC (area under the receiver-operating characteristic curve) = 0.86; for task ii p < 0.001, d = 0.88, AUC = 0.75. AI performed well for task ii (p < 0.001, d = 1.0, AUC = 0.78); for task i, though the difference was statistically significant (p < 0.001, AUC = 0.76), the effect size was small (d = 0.11). PI and GI failed in both tasks (p > 0.05, d < 0.4, AUC < 0.7 for all). However, for short-term segments, AI indicated better distinguishability for both tasks, i.e., for task i, p < 0.001, d = 0.71, AUC = 0.71; for task ii, p < 0.001, d = 0.93, AUC = 0.74. The rest three measures all failed with small effect sizes and AUC values (d < 0.5, AUC < 0.7 for all) although the difference in SI for task i was statistically significant (p < 0.001). Besides, AI displayed smaller variations across different short-term segments, indicating more robust performance. Results from the second short-term analysis were in keeping with those findings.

CONCLUSION

The proposed AI indicated better performance especially for short-term heartbeat interval data, suggesting potential in the ambulatory application of cardiovascular monitoring.

Study of Glycemic Variability Through Time Series Analyses (Detrended Fluctuation Analysis and Poincaré Plot) in Children and Adolescents with Type 1 Diabetes

BACKGROUND

Time series analysis provides information on blood glucose dynamics that is unattainable with conventional glycemic variability (GV) indices. To date, no studies have been published on these parameters in pediatric patients with type 1 diabetes. Our aim is to evaluate the relationship between time series analysis and conventional GV indices, and glycosylated hemoglobin (HbA1c) levels.

METHODS

This is a transversal study of 41 children and adolescents with type 1 diabetes. Glucose monitoring was carried out continuously for 72 h to study the following GV indices: standard deviation (SD) of glucose levels (mg/dL), coefficient of variation (%), interquartile range (IQR; mg/dL), mean amplitude of the largest glycemic excursions (MAGE), and continuous overlapping net glycemic action (CONGA). The time series analysis was conducted by means of detrended fluctuation analysis (DFA) and Poincaré plot.

RESULTS

Time series parameters (DFA alpha coefficient and elements of the ellipse of the Poincaré plot) correlated well with the more conventional GV indices. Patients were grouped according to the terciles of these indices, to the terciles of eccentricity (1: 12.56-16.98, 2: 16.99-21.91, 3: 21.92-41.03), and to the value of the DFA alpha coefficient (> or ≤1.5). No differences were observed in the HbA1c of patients grouped by GV index criteria; however, significant differences were found in patients grouped by alpha coefficient and eccentricity, not only in terms of HbA1c, but also in SD glucose, IQR, and CONGA index.

CONCLUSIONS

The loss of complexity in glycemic homeostasis is accompanied by an increase in variability.

Generalized Poincaré Plots-A New Method for Evaluation of Regimes in Cardiac Neural Control in Atrial Fibrillation and Healthy Subjects

Classical Poincaré plot is a standard way to measure nonlinear regulation of cardiovascular control. In our work we propose a generalized form of Poincaré plot where we track correlation between the duration of j preceding and k next RR intervals. The investigation was done in healthy subjects and patients with atrial fibrillation, by varying j,k ≤ 100. In cases where j = k, in healthy subjects the typical pattern was observed by “paths” that were substituting scatterplots and that were initiated and ended by loops of Poincaré plot points. This was not the case for atrial fibrillation patients where Poincaré plot had a simple scattered form. More, a typical matrix of Pearson's correlation coefficients, r(j,k), showed different positions of local maxima, depending on the subject's health condition. In both groups, local maxima were grouped into four clusters which probably determined specific regulatory mechanisms according to correlations between the duration of symmetric and asymmetric observed RR intervals. We quantified matrices' degrees of asymmetry and found that they were significantly different: distributed around zero in healthy, while being negative in atrial fibrillation. Also, Pearson's coefficients were higher in healthy than in atrial fibrillation or in signals with reshuffled intervals. Our hypothesis is that by this novel method we can observe heart rate regimes typical for baseline conditions and “defense reaction” in healthy subjects. These data indicate that neural control mechanisms of heart rate are operating in healthy subjects in contrast with atrial fibrillation, identifying it as the state of risk for stress-dependent pathologies. Regulatory regimes of heart rate can be further quantified and explored by the proposed novel method.

Heart Rate Variability Density Analysis (Dyx) and Prediction of Long-Term Mortality after Acute Myocardial Infarction

AIMS

The density HRV parameter Dyx is a new heart rate variability (HRV) measure based on multipole analysis of the Poincaré plot obtained from RR interval time series, deriving information from both the time and frequency domain. Preliminary results have suggested that the parameter may provide new predictive information on mortality in survivors of acute myocardial infarction (MI). This study compares the prognostic significance of Dyx to that of traditional linear and nonlinear measures of HRV.

METHODS AND RESULTS

In the Nordic ICD pilot study, patients with an acute MI were screened with 2D echocardiography and 24-hour Holter recordings. The study was designed to assess the power of several HRV measures to predict mortality. Dyx was tested in a subset of 206 consecutive Danish patients with analysable Holter recordings. After a median follow-up of 8.5 years 70 patients had died. Of all traditional and multipole HRV parameters, reduced Dyx was the most powerful predictor of all-cause mortality (HR 2.4; CI 1.5 to 3.8; P < 0.001). After adjustment for known risk markers, such as age, diabetes, ejection fraction, previous MI and hypertension, Dyx remained an independent predictor of mortality (P = 0.02). Reduced Dyx also predicted cardiovascular death (P < 0.01) and sudden cardiovascular death (P = 0.05). In Kaplan-Meier analysis, Dyx significantly predicted mortality in patients both with and without impaired left ventricular systolic function (P < 0.0001).

CONCLUSION

The new nonlinear HRV measure Dyx is a promising independent predictor of mortality in a long-term follow-up study of patients surviving a MI, irrespectively of left ventricular systolic function.

The recursive combination filter approach of pre-processing for the estimation of standard deviation of RR series

Variation in the interval between the R-R peaks of the electrocardiogram represents the modulation of the cardiac oscillations by the autonomic nervous system. This variation is contaminated by anomalous signals called ectopic beats, artefacts or noise which mask the true behaviour of heart rate variability. In this paper, we have proposed a combination filter of recursive impulse rejection filter and recursive 20% filter, with recursive application and preference of replacement over removal of abnormal beats to improve the pre-processing of the inter-beat intervals. We have tested this novel recursive combinational method with median method replacement to estimate the standard deviation of normal to normal (SDNN) beat intervals of congestive heart failure (CHF) and normal sinus rhythm subjects. This work discusses the improvement in pre-processing over single use of impulse rejection filter and removal of abnormal beats for heart rate variability for the estimation of SDNN and Poncaré plot descriptors (SD1, SD2, and SD1/SD2) in detail. We have found the 22 ms value of SDNN and 36 ms value of SD2 descriptor of Poincaré plot as clinical indicators in discriminating the normal cases from CHF cases. The pre-processing is also useful in calculation of Lyapunov exponent which is a nonlinear index as Lyapunov exponents calculated after proposed pre-processing modified in a way that it start following the notion of less complex behaviour of diseased states.

Poincaré plot width, morning urine norepinephrine levels, and autonomic imbalance in children with obstructive sleep apnea

BACKGROUND

Obstructive sleep apnea (OSA) in childhood is accompanied by sympathetic overflow unopposed by the parasympathetic tone. Complex methods like power spectral analysis of heart rate variability have been applied to study this imbalance. In this report, width of Poincaré scattergram of the R-R interval (parasympathetic tone) and morning urine norepinephrine concentration (sympathetic activity) were used to assess autonomic imbalance.

METHODS

Poincaré plot was obtained from the electrocardiographic channel of nocturnal polysomnography and its width was measured, and norepinephrine-to-creatinine concentration ratio was calculated in morning urine specimen.

RESULTS

Twenty children with obstructive sleep apnea and moderate-to-severe nocturnal hypoxemia (oxygen saturation of hemoglobin [SpO(2)] nadir <90%), 24 subjects with mild hypoxemia (SpO(2) nadir ≥90%), and 11 control subjects were recruited. Children with obstructive sleep apnea and moderate-to-severe hypoxemia had significantly narrower Poincaré plot width (318.7 ± 139.3 ms) and higher ln-transformed urine norepinephrine-to-creatinine ratio (4.5 ± 0.6) than control subjects (484.2 ± 104.4 ms and 3.8 ± 0.4, respectively; P < 0.05). Ln-transformed urine norepinephrine levels were inversely related to Poincaré plot width (P = 0.02).

CONCLUSIONS

Subjects with obstructive sleep apnea and moderate-to-severe nocturnal hypoxemia have enhanced sympathetic activity and reduced parasympathetic drive. Poincaré plot width and urine norepinephrine levels are simple measures of autonomic imbalance in pediatric obstructive sleep apnea.