Yi-Chung Chang

Outlier-resilient complexity analysis of heartbeat dynamics

Complexity in physiological outputs is believed to be a hallmark of healthy physiological control. How to accurately quantify the degree of complexity in physiological signals with outliers remains a major barrier for translating this novel concept of nonlinear dynamic theory to clinical practice. Here we propose a new approach to estimate the complexity in a signal by analyzing the irregularity of the sign time series of its coarse-grained time series at different time scales. Using surrogate data, we show that the method can reliably assess the complexity in noisy data while being highly resilient to outliers. We further apply this method to the analysis of human heartbeat recordings. Without removing any outliers due to ectopic beats, the method is able to detect a degradation of cardiac control in patients with congestive heart failure and a more degradation in critically ill patients whose life continuation relies on extracorporeal membrane oxygenator (ECMO). Moreover, the derived complexity measures can predict the mortality of ECMO patients. These results indicate that the proposed method may serve as a promising tool for monitoring cardiac function of patients in clinical settings.

Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects

Using 1000 successive points of a pulse wave velocity (PWV) series, we previously distinguished healthy from diabetic subjects with multi-scale entropy (MSE) using a scale factor of 10. One major limitation is the long time for data acquisition (i.e., 20 min). This study aimed at validating the sensitivity of a novel method, short time MSE (sMSE) that utilized a substantially smaller sample size (i.e., 600 consecutive points), in differentiating the complexity of PWV signals both in simulation and in human subjects that were divided into four groups: healthy young (Group 1; n = 24) and middle-aged (Group 2; n = 30) subjects without known cardiovascular disease and middle-aged individuals with well-controlled (Group 3; n = 18) and poorly-controlled (Group 4; n = 22) diabetes mellitus type 2. The results demonstrated that although conventional MSE could differentiate the subjects using 1000 consecutive PWV series points, sensitivity was lost using only 600 points. Simulation study revealed consistent results. By contrast, the novel sMSE method produced significant differences in entropy in both simulation and testing subjects. In conclusion, this study demonstrated that using a novel sMSE approach for PWV analysis, the time for data acquisition can be substantially reduced to that required for 600 cardiac cycles (~10 min) with remarkable preservation of sensitivity in differentiating among healthy, aged, and diabetic populations.

Correlations between the signal complexity of cerebral and cardiac electrical activity: a multiscale entropy analysis.

The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG) and a 19-channel eye-closed routine electroencephalography (EEG). Multiscale entropy (MSE) analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS), and photic stimulation of slow frequencies (slow-PS)) of EEG in the 1–58 Hz frequency range, and three RR interval (RRI) time series (awake-state, sleep and that concomitant with the EEG) for each subject. The low-to-high frequency power (LF/HF) ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a) the summed MSE value on coarse scales of the awake RRI (scales 11–20, RRI-MSE-coarse) were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6–20, EEG-MSE-coarse) at Fp2, C4, T6 and T4; (b) the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c) the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d) the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e) the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f) the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g) fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration.

Applying Harmonic Optical Microscopy for Spatial Alignment of Atrial Collagen Fibers

Background Atrial fibrosis creates a vulnerable tissue for atrial fibrillation (AF), but the spatial disarray of collagen fibers underlying atrial fibrosis is not fully elucidated. Objective This study hypothesizes that harmonics optical microscopy can illuminate the spatial mal-alignment of collagen fibers in AF via a layer-by-layer approach. Patients and Methods Atrial tissues taken from patients who underwent open-heart surgery were examined by harmonics optical microscopy. Using the two-dimensional Fourier transformation method, a spectral-energy description of image texture was constituted and its entropy was used to quantify the mal-alignment of collagen fibers. The amount of collagen fiber was derived from its area ratio to total atrial tissue in each image. Serum C-terminal pro-collagen pro-peptide (CICP), pro-matrix metalloproteinase-1 (pro-MMP-1), and tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) were also evaluated. Results 46 patients were evaluated, including 20 with normal sinus rhythm and 26 with AF. The entropy of spectral-energy distribution of collagen alignment was significantly higher in AF than that in sinus rhythm (3.97±0.33 vs. 2.80±0.18, p<0.005). This difference was more significant in the permanent AF group. The amount of collagen was also significantly higher in AF patients (0.39±0.13 vs. 0.18±0.06, p<0.005) but serum markers of cardiac fibrosis were not significantly different between the two groups. Conclusions Harmonics optical microscopy can quantify the spatial mal-alignment of collagen fibers in AF. The entropy of spectral-energy distribution of collagen alignment is a potential tool for research in atrial remodeling.

Multi-scale symbolic entropy analysis provides prognostic prediction in patients receiving extracorporeal life support

IntroductionExtracorporeal life support (ECLS) can temporarily support cardiopulmonary function, and is occasionally used in resuscitation. Multi-scale entropy (MSE) derived from heart rate variability (HRV) is a powerful tool in outcome prediction of patients with cardiovascular diseases. Multi-scale symbolic entropy analysis (MSsE), a new method derived from MSE, mitigates the effect of arrhythmia on analysis. The objective is to evaluate the prognostic value of MSsE in patients receiving ECLS. The primary outcome is death or urgent transplantation during the index admission.MethodsFifty-seven patients receiving ECLS less than 24 hours and 23 control subjects were enrolled. Digital 24-hour Holter electrocardiograms were recorded and three MSsE parameters (slope 5, Area 6–20, Area 6–40) associated with the multiscale correlation and complexity of heart beat fluctuation were calculated.ResultsPatients receiving ECLS had significantly lower value of slope 5, area 6 to 20, and area 6 to 40 than control subjects. During the follow-up period, 29 patients met primary outcome. Age, slope 5, Area 6 to 20, Area 6 to 40, acute physiology and chronic health evaluation II score, multiple organ dysfunction score (MODS), logistic organ dysfunction score (LODS), and myocardial infarction history were significantly associated with primary outcome. Slope 5 showed the greatest discriminatory power. In a net reclassification improvement model, slope 5 significantly improved the predictive power of LODS; Area 6 to 20 and Area 6 to 40 significantly improved the predictive power in MODS. In an integrated discrimination improvement model, slope 5 added significantly to the prediction power of each clinical parameter. Area 6 to 20 and Area 6 to 40 significantly improved the predictive power in sequential organ failure assessment.ConclusionsMSsE provides additional prognostic information in patients receiving ECLS.

Static craniofacial measurements and dynamic airway collapse patterns associated with severe obstructive sleep apnoea: a sleep MRI study.

Using sleep MRI, we aimed to identify static craniofacial measurements and dynamic upper airway collapse patterns associated with severe obstructive sleep apnoea (OSA) during natural sleep in age and BMI‐matched patients.

Quality of audio-assisted versus video-assisted dispatcher-instructed bystander cardiopulmonary resuscitation: A systematic review and meta-analysis

AIM This study aimed to conduct a systematic review and meta-analysis comparing the effect of video-assistance and audio-assistance on quality of dispatcher-instructed cardiopulmonary resuscitation (DI-CPR) for bystanders. METHODS Five databases were searched, including PubMed, Cochrane library, Embase, Scopus and NIH clinical trial, to find randomized control trials published before June 2017. Qualitative analysis and meta-analysis were undertaken to examine the difference between the quality of video-instructed and audio-instructed dispatcher-instructed bystander CPR. RESULTS The database search yielded 929 records, resulting in the inclusion of 9 relevant articles in this study. Of these, 6 were included in the meta-analysis. Initiation of chest compressions was slower in the video-instructed group than in the audio-instructed group (median delay 31.5 s; 95% CI: 10.94-52.09). The difference in the number of chest compressions per minute between the groups was 19.9 (95% CI: 10.50-29.38) with significantly faster compressions in the video-instructed group than in the audio-instructed group (104.8 vs. 80.6). The odds ratio (OR) for correct hand positioning was 0.8 (95% CI: 0.53-1.30) when comparing the audio-instructed and video-instructed groups. The differences in chest compression depth (mm) and time to first ventilation (seconds) between the video-instructed group and audio-instructed group were 1.6 mm (95% CI: -8.75, 5.55) and 7.5 s (95% CI: -56.84, 71.80), respectively. CONCLUSIONS Video-instructed DI-CPR significantly improved the chest compression rate compared to the audio-instructed method, and a trend for correctness of hand position was also observed. However, this method caused a delay in the commencement of bystander-initiated CPR in the simulation setting.

The use of a novel signal analysis to identify the origin of idiopathic right ventricular outflow tract ventricular tachycardia during sinus rhythm: Simultaneous amplitude frequency electrogram transformation mapping

Introduction The signal characteristics of intracardiac bipolar electrograms at the origin of idiopathic RVOT-VT during sinus rhythm remain unclear. Objective The study sought to develop a novel real-time/online technique, simultaneous amplitude frequency electrogram transformation (SAFE-T), to quantify and localize the diseased ventricular substrate in idiopathic RVOT-VT. Methods We retrospectively investigated the intracardiac bipolar recordings in 70 consecutive patients (26% male, mean age 42±12 years) who underwent successful radiofrequency catheter ablation of idiopathic RVOT-VT. We quantified the extent of the frequency fraction of ventricular potentials during sinus rhythm or ventricular pacing using a novel formula, the product of instantaneous amplitude and frequency, and showed that in a 3D geometry as an online SAFE-T map. Results The characteristics of the HHT spectra of electrograms derived from VT origins demonstrated high frequency components (>70 Hz), which were independent of the rhythm. The density of the abnormal potentials at the VT origins were higher (VT origins, 7.5±2.3 sites/cm2 vs. surrounding myocardium, 1.5±1.3 sites/cm2, p<0.001), and were significantly decreased after ablation (0.7±0.6 sites/cm2, p<0.001). A small region of abnormal potentials were observed in the VT origins (mean area of 1.5±0.8 cm2). The SAFE-T maps predicted the VT origins with 92% sensitivity, 78% specificity with optimal cut-off value of >3.0 Hz·mV. Conclusion The online SAFE-T map was feasible for quantifying the diseased ventricular substrate, irrespective of the rhythm of activation, and can be used to identify the optimal ablation targets for idiopathic RVOT-VT. We found a limited region of abnormal potentials where the RVOT-VT origins were successfully ablated.

Genotoxicity tests of poly(styrene-co-maleic anhydride)-coated silver nanoparticles in vivo and in vitro

Nanosilver is thought to hold potential for use in medical materials. The safety of newly developed poly(styrene-co-maleic anhydride)-coated silver nanoparticles (SMA-AgNPs) requires investigation. In this study, three in vitro and in vivo experiments for investigating genetic toxicity–the Ames test, a micronucleus assay, and a chromosome aberration test–were conducted. Results from the Ames testing showed SMA-AgNPs to have a negative effect, either with or without S9 metabolism. In addition, SMA-AgNPs increased the number of reticulocytes and micronuclei in reticulocytes at 48 and 72 h after treatment. Indeed, SMA-AgNPs induced significant changes in the chromosomal aberration rate in CHO-K1 (Chinese hamster ovary cell clone K1) cells. In conclusion, SMA-AgNPs did cause DNA damage in terms of chromosomal aberration and may have a potential genotoxic effect in certain applications.

Non-invasive Drosophila ECG recording by using eutectic gallium-indium alloy electrode: a feasible tool for future research on the molecular mechanisms involved in cardiac arrhythmia.

Background Drosophila heart tube is a feasible model for cardiac physiological research. However, obtaining Drosophila electrocardiograms (ECGs) is difficult, due to the weak signals and limited contact area to apply electrodes. This paper presents a non-invasive Gallium-Indium (GaIn) based recording system for Drosophila ECG measurement, providing the heart rate and heartbeat features to be observed. This novel, high-signal-quality system prolongs the recording time of insect ECGs, and provides a feasible platform for research on the molecular mechanisms involved in cardiovascular diseases. Methods In this study, two types of electrode, tungsten needle probes and GaIn electrodes, were used respectively to noiselessly conduct invasive and noninvasive ECG recordings of Drosophila. To further analyze electrode properties, circuit models were established and simulated. By using electromagnetic shielded heart signal acquiring system, consisted of analog amplification and digital filtering, the ECG signals of three phenotypes that have different heart functions were recorded without dissection. Results and Discussion The ECG waveforms of different phenotypes of Drosophila recorded invasively and repeatedly with n value (n>5) performed obvious difference in heart rate. In long period ECG recordings, non-invasive method implemented by GaIn electrodes acts relatively stable in both amplitude and period. To analyze GaIn electrode, the correctness of GaIn electrode model established by this paper was validated, presenting accuracy, stability, and reliability. Conclusions Noninvasive ECG recording by GaIn electrodes was presented for recording Drosophila pupae ECG signals within a limited contact area and signal strength. Thus, the observation of ECG changes in normal and SERCA-depleted Drosophila over an extended period is feasible. This method prolongs insect survival time while conserving major ECG features, and provides a platform for electrophysiological signal research on the molecular mechanism involved in cardiac arrhythmia, as well as research related to drug screening and development.