Algorithm-Driven Tele-otoscope for Remote Care for Patients With Otitis Media.

OBJECTIVE: The COVID-19 pandemic has spurred a growing demand for telemedicine. Artificial intelligence and image processing systems with wireless transmission functionalities can facilitate remote care for otitis media (OM). Accordingly, this study developed and validated an algorithm-driven tele-otoscope system equipped with Wi-Fi transmission and a cloud-based automatic OM diagnostic algorithm. STUDY DESIGN: Prospective, cross-sectional, diagnostic study. SETTING: Tertiary Academic Medical Center. METHODS: We designed a tele-otoscope (Otiscan, SyncVision Technology Corp) equipped with digital imaging and processing modules, Wi-Fi transmission capabilities, and an automatic OM diagnostic algorithm. A total of 1137 otoscopic images, comprising 987 images of normal cases and 150 images of cases of acute OM and OM with effusion, were used as the dataset for image classification. Two convolutional neural network models, trained using our dataset, were used for raw image segmentation and OM classification. RESULTS: The tele-otoscope delivered images with a resolution of 1280 × 720 pixels. Our tele-otoscope effectively differentiated OM from normal images, achieving a classification accuracy rate of up to 94% (sensitivity, 80%; specificity, 96%). CONCLUSION: Our study demonstrated that the developed tele-otoscope has acceptable accuracy in diagnosing OM. This system can assist health care professionals in early detection and continuous remote monitoring, thus mitigating the consequences of OM.

A transferable in-silico augmented ischemic model for virtual myocardial perfusion imaging and myocardial infarction detection.

This paper proposes an innovative approach to generate a generalized myocardial ischemia database by modeling the virtual electrophysiology of the heart and the 12-lead electrocardiography projected by the in-silico model can serve as a ready-to-use database for automatic myocardial infarction/ischemia (MI) localization and classification. Although the virtual heart can be created by an established technique combining the cell model with personalized heart geometry to observe the spatial propagation of depolarization and repolarization waves, we developed a strategy based on the clinical pathophysiology of MI to generate a heterogeneous database with a generic heart while maintaining clinical relevance and reduced computational complexity. First, the virtual heart is simplified into 11 regions that match the types and locations, which can be diagnosed by 12-lead ECG; the major arteries were divided into 3-5 segments from the upstream to the downstream based on the general anatomy. Second, the stenosis or infarction of the major or minor coronary artery branches can cause different perfusion drops and infarct sizes. We simulated the ischemic sites in different branches of the arteries by meandering the infarction location to elaborate on possible ECG representations, which alters the infraction's size and changes the transmembrane potential (TMP) of the myocytes associated with different levels of perfusion drop. A total of 8190 different case combinations of cardiac potentials with ischemia and MI were simulated, and the corresponding ECGs were generated by forward calculations. Finally, we trained and validated our in-silico database with a sparse representation classification (SRC) and tested the transferability of the model on the real-world Physikalisch Technische Bundesanstalt (PTB) database. The overall accuracies for localizing the MI region on the PTB data achieved 0.86, which is only 2% drop compared to that derived from the simulated database (0.88). In summary, we have shown a proof-of-concept for transferring an in-silico model to real-world database to compensate for insufficient data.

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.

Catheter Ablation With Morphologic Repetitiveness Mapping for Persistent Atrial Fibrillation.

Importance: Catheter ablation for persistent atrial fibrillation (AF) has shown limited success. Objective: To determine whether AF drivers could be accurately identified by periodicity and similarity (PRISM) mapping ablation results for persistent AF when added to pulmonary vein isolation (PVI). Design, Setting, and Participants: This prospective randomized clinical trial was performed between June 1, 2019, and December 31, 2020, and included patients with persistent AF enrolled in 3 centers across Asia. Data were analyzed on October 1, 2022. Intervention: Patients were assigned to the PRISM-guided approach (group 1) or the conventional approach (group 2) at a 1:1 ratio. Main Outcomes and Measures: The primary outcome was freedom from AF or other atrial arrhythmia for longer than 30 seconds at 6 and 12 months. Results: A total of 170 patients (mean [SD] age, 62.0 [12.3] years; 136 men [80.0%]) were enrolled (85 patients in group 1 and 85 patients in group 2). More group 1 patients achieved freedom from AF at 12 months compared with group 2 patients (60 [70.6%] vs 40 [47.1%]). Multivariate analysis indicated that the PRISM-guided approach was associated with freedom from the recurrence of atrial arrhythmia (hazard ratio, 0.53 [95% CI, 0.33-0.85]). Conclusions and Relevance: The waveform similarity and recurrence pattern derived from high-density mapping might provide an improved guiding approach for ablation of persistent AF. Compared with the conventional procedure, this novel specific substrate ablation strategy reduced the frequency of recurrent AF and increased the likelihood of maintenance of sinus rhythm. Trial Registration: ClinicalTrials.gov Identifier: NCT05333952.

Coronavirus disease 2019 and cardiovascular disease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus behind the coronavirus disease 2019 (COVID-19) pandemic, is a type of RNA virus that is nonsegmented. Cardiovascular diseases (CVDs) increase the mortality risk of patients. In this review article, we overview the existing evidence regarding the potential mechanisms of myocardial damage in coronavirus disease 2019 (COVID-19) patients. Having a comprehensive knowledge of the cardiovascular damage caused by SARS-CoV-2 and its underlying mechanisms is essential for providing prompt and efficient treatment, ultimately leading to a reduction in mortality rates. Severe COVID-19 causes acute respiratory distress syndrome and shock in patients. In addition, awareness regarding COVID-19 cardiovascular manifestations has increased, including the adverse impact on prognosis with cardiovascular involvement. Angiotensin-converting enzyme 2 receptor may play a role in acute myocardial injury caused by SARS-CoV-2 infection. COVID-19 patients experiencing heart failure may have their condition exacerbated by various contributing factors and mechanisms. Increased oxygen demand, myocarditis, stress cardiomyopathy, elevated pulmonary pressures, and venous thrombosis are potential health issues. The combination of these factors may lead to COVID-19-related cardiogenic shock, resulting in acute systolic heart failure. Extracorporeal membrane oxygenation (ECMO) and left ventricular assist devices (LVADs) are treatment options when inotropic support fails for effective circulatory support. To ensure effective COVID-19-related cardiovascular disease (CVD) surveillance, it is crucial to closely monitor the future host adaptation, viral evolution, and transmissibility of SARS-CoV-2, given the virus's pandemic potential.

Fractal complexity alternations in paroxysmal atrial fibrillation patients with and without recurrence after pulmonary vein isolation.

BACKGROUND: Pulmonary vein isolation (PVI) is a cornerstone therapy for paroxysmal atrial fibrillation (PAF). The variations in nonlinear heart rate variability (HRV) between patients with and without recurrences remain unclear. We aimed to characterize the nonlinear HRV before and after PVI in patients with and without recurrence. METHODS: Twenty-five drug-refractory PAF patients (56.0 ± 9.1 years old, 20 males) who received PVI were enrolled. Holter electrocardiography were performed before, 1-3, and 6-12 months after PVI. After 8.2 ± 2.5 months of follow-ups after PVI, patients were divided into two groups: the recurrence (n = 8) and non-recurrence (n = 17) groups. Linear and nonlinear HRV variables were analyzed, including the Poincaré Plot analysis and the Detrended Fluctuation Analysis (DFA). RESULTS: The non-recurrence group, but not the recurrence group, had decreased high-frequency component (HF), the root mean square of successive RR interval differences (RMSSD), and the Poincaré Plot index SD1 1-3 months after PVI and increased DFAslope2 6-12 months after PVI. The non-recurrence group's LF/HF ratio and DFAslope1 decreased significantly 1-3 and 6-12 months after PVI, respectively, whereas there was no significant change in the recurrence group after PVI. CONCLUSIONS: Significantly reduced vagal tone 1-3 months after PVI, increased long-term fractal complexity 6-12 months after PVI, and decreased sympathetic tone as well as short-term fractal complexity 1-3 and 6-12 months after PVI led to a better AF-free survival after PVI. These findings suggest that neuromodulation and heart rate dynamics play crucial roles in AF recurrence following PVI.

Cross-Frequency Coupling and Intelligent Neuromodulation.

Cross-frequency coupling (CFC) reflects (nonlinear) interactions between signals of different frequencies. Evidence from both patient and healthy participant studies suggests that CFC plays an essential role in neuronal computation, interregional interaction, and disease pathophysiology. The present review discusses methodological advances and challenges in the computation of CFC with particular emphasis on potential solutions to spurious coupling, inferring intrinsic rhythms in a targeted frequency band, and causal interferences. We specifically focus on the literature exploring CFC in the context of cognition/memory tasks, sleep, and neurological disorders, such as Alzheimer's disease, epilepsy, and Parkinson's disease. Furthermore, we highlight the implication of CFC in the context and for the optimization of invasive and noninvasive neuromodulation and rehabilitation. Mainly, CFC could support advancing the understanding of the neurophysiology of cognition and motor control, serve as a biomarker for disease symptoms, and leverage the optimization of therapeutic interventions, e.g., closed-loop brain stimulation. Despite the evident advantages of CFC as an investigative and translational tool in neuroscience, further methodological improvements are required to facilitate practical and correct use in cyborg and bionic systems in the field.

Daily rhythm of dynamic cerebral autoregulation in patients after stroke.

Dynamic cerebral autoregulation (dCA) in healthy young adults displays a daily variation. Whether the rhythm exists in patients with stroke is unknown. We studied 28 stroke patients (age: 26-83 years, 7 females) within 48 hours after thrombolysis. dCA was assessed 54 times in these patients during supine rest (twice in 26 and once in 2 patients): 9 assessments between 0-9AM, 12 between 9AM-2PM, 20 between 2-7PM, and 13 between 7PM-12AM. To estimate dCA, phase shifts between spontaneous oscillations of cerebral blood flow velocity (CBFV) in the middle cerebral artery and arterial blood pressure (BP) were obtained in four frequency bands: <0.05 Hz, 0.05-0.1 Hz, 0.1-0.2 Hz, and >0.2 Hz. CBFV-BP phase shifts at <0.05 Hz were significantly larger between 2-7PM, suggesting better dCA, than those at other times (p < 0.0001), and the daily rhythm was consistent for stroke and non-stroke sides. No significant rhythms were observed at higher frequencies (all p > 0.2). All results were independent of age, sex, stroke type and severity, and other cardiovascular conditions. dCA after stroke showed a daily rhythm, leading to a better regulation of CBFV at <0.05 Hz during the afternoon. The finding may have implications for daily activity management of stroke patients.

Characterization and identification of atrial fibrillation drivers in patients with nonparoxysmal atrial fibrillation using simultaneous amplitude frequency electrogram transform.

INSTRUCTION: We hypothesized that real-time simultaneous amplitude frequency electrogram transform (SAFE-T) during sinus rhythm (SR) is able to identify and characterize the drivers of atrial fibrillation (AF) in nonparoxysmal (NP) AF. METHODS: Twenty-one NPAF patients (85.71% males, mean age 52 years old) underwent substrate mapping during SR (SAFE-T and voltage) and during AF (complex fractionated atrial electrograms [CFAE] and similarity index [SI]). After pulmonary veins isolation, extensive substrate ablation was performed with the endpoint of procedural termination or elimination of all SI sites (>63% similarities). Sites with procedural termination and non-termination sites were tagged for postablation SR analysis using SAFE-T. RESULTS: In 74 CFAE sites identified (average of 3 ± 2 sites per person), 28 (37.84%) were identified as termination sites demonstrating a high SI compared with the non-termination sites (80.11 ± 9.57% vs. 45.96 ± 13.38%, p < .001) during AF. During SR, these termination sites have high SAFE-T values and harbor a highly resonant, localized, repetitive high frequency components superimposed in the low frequency components compared with non-termination sites (5.70 ± 3.04 vs. 1.49 ± 1.66 Hz·mV, p < .001). In the multivariate analysis, the termination sites have higher SAFE-T and SI value (p < .001). CONCLUSION: AF procedural termination sites harbored signal characteristics of repetitive, high frequency component of individualized electrogram during SR, which can be masked by the low frequency fractionated electrogram and are difficult to see from the bipolar electrogram. Thus, SAFE-T mapping is feasible in identifying and characterizing sites of AF drivers.

Alterations of sympathetic dynamics after atrial fibrillation ablation by analysis sympathetic nerve activity provide prognostic value for recurrence and mechanistic insights into ablation.

Background: Pulmonary vein isolation (PVI) is the cornerstone of atrial fibrillation (AF) ablation. Success is associated with autonomic function modulation; however, the relationship between the changes after ablation is not fully understood. We aimed to investigate the effect of ablation on autonomic modulation by skin sympathetic nerve activity (SKNA) using conventional electrocardiogram (ECG) electrodes and to predict the treatment success. Methods: We enrolled 79 patients. We recorded neuECG for 10 min at 10 kHz before and after ablation. The NeuECG was bandpass-filtered (500-1,000 Hz) and integrated at intervals of 100 ms (iSKNA). iSKNA was averaged over different time windows (1-, 5-,10-s; aSKNAs), and burst analyses were derived from aSKNAs to quantify the dynamics of sympathetic activities. AF recurrence after 3 months was defined as the study endpoint. Results: Sixteen patients experienced AF recurrence after the ablation. For burst analysis of 1-s aSKNA, the recurrence group had a higher bursting frequency than the non-recurrence group (0.074 ± 0.055 vs. 0.109 ± 0.067; p < 0.05) before ablation. The differences between pre- and post-ablation of firing duration longer than 2 s were more in the non-recurrence group (2.75 ± 6.41 vs. -1.41 ± 5.14; p < 0.05), while no significant changes were observed in the percentage of duration longer than 10 s using 5-s aSKNA. In addition, decreases in differences in firing frequency and percentage of both overall firing duration and longer firing duration (> 2 s) between pre- and post-ablation were independently associated with AF recurrence and more area under receiver operating characteristics (ROC) curve in combination with CHADS2 score (0.833). Conclusion: We demonstrated the applicability of neuECG for determining sympathetic modulation during AF ablation. Decreasing sympathetic activity is the key to successful ablation.

Identification of Patients with Potential Atrial Fibrillation during Sinus Rhythm Using Isolated P Wave Characteristics from 12-Lead ECGs.

Atrial fibrillation (AF) is largely underdiagnosed. Previous studies using deep neural networks with large datasets have shown that screening AF with a 12-lead electrocardiogram (ECG) during sinus rhythm (SR) is possible. However, the poor availability of these trained models and the small size of the retrievable datasets limit its reproducibility. This study proposes an approach to generate explainable features for detecting AF during SR with limited data. We collected 94,224 12-lead ECGs from 64,196 patients from Taipei Medical University Hospital. We selected ECGs during SR from 213 patients before AF diagnosis and randomly selected 247 age-matched participants without AF records as the controls. We developed a signal-processing technique, MA-UPEMD, to isolate P waves, and quantified the spatial and temporal features using principal component analysis and inter-lead relationships. By combining these features, the machine learning models yielded AUC of 0.64. We showed that, even with this limited dataset, the P wave, representing atrial electrical activity, is depicted by our proposed approach. The extracted features performed better than the bandpass filter-extracted P waves and deep neural network model. We provided a physiologically explainable and reproducible approach for classifying patients with AF during SR.

Nonlinear Heart Rate Dynamics Before and After Paroxysmal Atrial Fibrillation Events.

Background: Heart rate complexity, derived from nonlinear heart rate variability (HRV), has been shown to help predict the outcomes of various diseases. Changes in heart rate complexity before and after paroxysmal atrial fibrillation (PAF) events are unclear. Objectives: To evaluate changes in heart rate complexity through nonlinear HRV before and after PAF events. Methods: We enrolled 65 patients (72 ± 12.34 years old, 31 females) with 99 PAF events who received 24-hour Holter recording, and analyzed nonlinear HRV variables including Poincaré plot analysis, sample entropy (SampEn), and multiscale entropy (MSE). HRV analyses were applied to a 20-minute window before the onset and after the termination of PAF events. HRV parameters were evaluated and compared based on eight different 5-minute time segments, as we divided each 20-minute window into four segments of 5 minutes each. Results: SampEn and MSE1~5 significantly decreased before the onset of PAF events, whereas SampEn, MSE1~5 and MSE6~20 significantly increased after the termination of PAF events. SD1 and SD2, which are nonlinear HRV parameters calculated via Poincaré plot analysis, did not significantly change before the PAF events, however they both decreased significantly after termination. Conclusions: Heart rate complexity significantly decreased before the initiation and increased after the termination of PAF events, which indicates the crucial role of nonlinear heart rate dynamics in the initiation and termination of PAF.

Preserved Electroencephalogram Power and Global Synchronization Predict Better Neurological Outcome in Sudden Cardiac Arrest Survivors.

Quantitative EEG (qEEG) delineates complex brain activities. Global field synchronization (GFS) is one multichannel EEG analysis that measures global functional connectivity through quantification of synchronization between signals. We hypothesized that preservation of global functional connectivity of brain activity might be a surrogate marker for good outcome in sudden cardiac arrest (SCA) survivors. In addition, we examined the relation of phase coherence and GFS in a mathematical approach. We retrospectively collected EEG data of SCA survivors in one academic medical center. We included 75 comatose patients who were resuscitated following in-hospital or out-of-hospital nontraumatic cardiac arrest between 2013 and 2017 in the intensive care unit (ICU) of National Taiwan University Hospital (NTUH). Twelve patients (16%) were defined as good outcome (GO) (CPC 1-2). The mean age in the GO group was low (51.6 ± 15.7 vs. 68.1 ± 12.9, p < 0.001). We analyzed standard EEG power, computed EEG GFS, and assessed the cerebral performance category (CPC) score 3 months after discharge. The alpha band showed the highest discrimination ability (area under curve [AUC] = 0.78) to predict GO using power. The alpha band of GFS showed the highest AUC value (0.8) to predict GO in GFS. Furthermore, by combining EEG power + GFS, the alpha band showed the best prediction value (AUC 0.86) in predicting GO. The sensitivity of EEG power + GFS was 73%, specificity was 93%, PPV was 0.67%, and NPV was 0.94%. In conclusion, by combining GFS and EEG power analysis, the neurological outcome of the nontraumatic cardiac arrest survivor can be well-predicted. Furthermore, we proved from a mathematical point of view that although both amplitude and phase contribute to obtaining GFS, the interference in phase variation drastically changes the possibility of generating a good GFS score.

Improvement in vocal-cord visualization with Trachway video intubating stylet using direct oxygen flow and effective analysis of the fraction of inspired oxygen: a bench study.

The Trachway video intubating stylet device facilitates the visualization of the airways of patients from the tip of an endotracheal tube (ETT) during intubation. The major limitations of Trachway are the restricted view due to secretions and the risk of a prolonged apnea during intubation. We conducted a bench study to verify the performance of an alternative, easily applicable airway device that allows better visualization of trackways during Trachway-assisted intubation and prevents the detrimental effects of apnea-related hypoxia. We conducted a bench study to thoroughly evaluate the oral-secretion-elimination ability of a newly designed oxygen delivery device (ODD) to improve vocal-cord visualization using the three commonly used ETT sizes (i.e., 7, 7.5, and 8 mm). Moreover, we measured the fraction of inspired oxygen (FiO2) under different, continuous oxygen-flow supplies (1-10 L/min) during intubation. Each condition was analyzed for a 2 min video-stylet-intubation period. The supplemental oxygen flow and FiO2 fraction achieved using our ODD were higher, and smaller ETTs exhibited better secretion elimination. The ODD, which can be easily coupled with Trachway stylets, enabled high-quality visualization during oxygen flows of 6-8 L/min, and higher FiO2 fractions were achieved at higher oxygen flow rates. The use of the ODD improved the visualization of the airways during video stylet-assisted intubations using the additional FiO2 supply. The ODD developed in this study improves the visualization of airways with Trachway stylets and enhances the safety of intubation.

Using QRS loop descriptors to characterize the risk of sudden cardiac death in patients with structurally normal hearts.

The predictive value of non-invasive electrocardiographic examination findings for the risk of sudden cardiac death (SCD) in populations with structurally normal hearts remains unclear. This study aimed to investigate the characteristics of the QRS vectorcardiography of surface electrocardiography in patients with structurally normal hearts who experienced SCD. We consecutively enrolled patients who underwent vectorcardiography between March 2017 and December 2018 in a tertiary referral medical center. These patients didn't have structural heart diseases, histories of congestive heart failure, or reduced ejection fraction, and they were classified into SCD (with aborted SCD history and cerebral performance category score of 1) and control groups (with an intervention for atrioventricular node reentrant tachycardia and without SCD history). A total of 162 patients (mean age, 54.3±18.1 years; men, 75.9%), including 59 in the SCD group and 103 in the control group, underwent propensity analysis. The baseline demographic variables, underlying diseases, QRS loop descriptors (the percentage of the loop area, loop dispersion, and inter-lead QRS dispersion), and other electrocardiographic parameters were compared between the two groups. In the univariate and multivariate analyses, a smaller percentage of the loop area (odds ratio, 0.0003; 95% confidence interval, 0.00-0.02; p<0.001), more significant V4-5 dispersion (odds ratio, 1.04; 95% confidence interval, 1.02-1.07; p = 0.002), and longer QRS duration (odds ratio, 1.05; 95% confidence interval, 1.00-1.10; p = 0.04) were associated with SCD. In conclusion, the QRS loop descriptors of surface electrocardiography could be used as non-invasive markers to identify patients experiencing aborted SCD from a healthy population. A decreased percentage of loop area and elevated V4-5 QRS dispersion values assessed using vectorcardiography were associated with an increased risk of SCD in patients with structurally normal hearts.

Localizing Spectral Interactions in the Resting State Network Using the Hilbert-Huang Transform.

Brain synchronizations are orchestrated from neuronal oscillations through frequency interactions, such as the alpha rhythm during relaxation. Nevertheless, how the intrinsic interaction forges functional integrity across brain segregations remains elusive, thereby motivating recent studies to localize frequency interactions of resting-state fMRI (rs-fMRI). To this point, we aim to unveil the fMRI-based spectral interactions using the time-frequency (TF) analysis; however, Fourier-based TF analyses impose restrictions on revealing frequency interactions given the limited time points in fMRI signals. Instead of using the Fourier-based wavelet analysis to identify the fMRI frequency of interests, we employed the Hilbert-Huang transform (HHT) for probing the specific frequency contribution to the functional integration, called ensemble spectral interaction (ESI). By simulating data with time-variant frequency changes, we demonstrated the Hilbert TF maps with high spectro-temporal resolution and full accessibility in comparison with the wavelet TF maps. By detecting amplitude-to-amplitude frequency couplings (AAC) across brain regions, we elucidated the ESI disparity between the eye-closed (EC) and eye-open (EO) conditions in rs-fMRI. In the visual network, the strength of the spectral interaction within 0.03-0.04 Hz was amplified in EC compared with that in EO condition, whereas a canonical connectivity analysis did not present differences between conditions. Collectively, leveraging from the instantaneous frequency of HHT, we firstly addressed the ESI technique to map the fMRI-based functional connectivity in a brand-new AAC perspective. The ESI possesses potential in elucidating the functional connectivity at specific frequency bins, thereby providing additional diagnostic merits for future clinical neuroscience.

Strong Early Phase Parasympathetic Inhibition Followed by Sympathetic Withdrawal During Propofol Induction: Temporal Response Assessed by Wavelet-Based Spectral Analysis and Photoplethysmography.

Background: Induction of anesthesia with propofol is associated with a disturbance in hemodynamics, in part due to its effects on parasympathetic and sympathetic tone. The impact of propofol on autonomic function is unclear. In this study, we investigated in detail the changes in the cardiac autonomic nervous system (ANS) and peripheral sympathetic outflow that occur during the induction of anesthesia. Methods: Electrocardiography and pulse photoplethysmography (PPG) signals were recorded and analyzed from 30 s before to 120 s after propofol induction. The spectrogram was derived by continuous wavelet transform with the power of instantaneous high-frequency (HFi) and low-frequency (LFi) bands extracted at 1-s intervals. The wavelet-based parameters were then divided into the following segments: (1) baseline (30 s before administration of propofol), (2) early phase (first minute after administration of propofol), and (3) late phase (second minute after administration of propofol) and compared with the same time intervals of the Fourier-based spectrum [high-frequency (HF) and low-frequency (LF) bands]. Time-dependent effects were explored using fractional polynomials and repeated-measures analysis of variance. Results: Administration of propofol resulted in reductions in HFi and LFi and increases in the LFi/HFi ratio and PPG amplitude, which had a significant non-linear relationship. Significant between-group differences were found in the HFi, LFi, and LFi/HFi ratio and Fourier-based HF and LF after dividing the segments into baseline and early/late phases. On post hoc analysis, changes in HFi, LFi, and the LFi/HFi ratio were significant starting from the early phase. The corresponding effect size (partial eta squared) was > 0.3, achieving power over 90%; however, significant decreases in HF and LF were observed only in the late phase. The PPG amplitude was increased significantly in both the early and late phases. Conclusion: Propofol induction results in significant immediate changes in ANS activity that include temporally relative elevation of cardiac sympathovagal balance and reduced sympathetic activity. Clinical Trial Registration: The study was approved by the Institutional Review Board of Taipei Veterans General Hospital (No. 2017-07-009CC) and is registered at ClinicalTrials.gov (https://clinicaltrials.gov/ct2/show/NCT03613961).

Daily Rhythm of Fractal Cardiac Dynamics Links to Weight Loss Resistance: Interaction with CLOCK 3111T/C Genetic Variant.

The effectiveness of weight loss treatment displays dramatic inter-individual variabilities, even with well-controlled energy intake/expenditure. This study aimed to determine the association between daily rhythms of cardiac autonomic control and weight loss efficiency and to explore the potential relevance to weight loss resistance in humans carrying the genetic variant C at CLOCK 3111T/C. A total of 39 overweight/obese Caucasian women (20 CLOCK 3111C carriers and 19 non-carriers) completed a behaviour-dietary obesity treatment of ~20 weeks, during which body weight was assessed weekly. Ambulatory electrocardiographic data were continuously collected for up to 3.5 days and used to quantify the daily rhythm of fractal cardiac dynamics (FCD), a non-linear measure of autonomic function. FCD showed a 24 h rhythm (p < 0.001). Independent of energy intake and physical activity level, faster weight loss was observed in individuals with the phase (peak) of the rhythm between ~2-8 p.m. and with a larger amplitude. Interestingly, the phase effect was significant only in C carriers (p = 0.008), while the amplitude effect was only significant in TT carriers (p < 0.0001). The daily rhythm of FCD and CLOCK 3111T/C genotype is linked to weight loss response interactively, suggesting complex interactions between the genetics of the circadian clock, the daily rhythm of autonomic control, and energy balance control.

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.

Probing penile hemodynamics by using photoplethysmography as objective indicators for male erection quality and sexual function.

Erectile dysfunction (ED) is mostly due to the lack of blood flow into the penis. In the past 20 years, near-infrared spectroscopy (NIRS) was used in measuring the concentrations and temporal dynamics of different hemoglobin types. However, the dynamics of the light absorption (photoplethysmography; PPG) have not been applied to survey penile hemodynamics and erection quality. This paper compared the use of photoplethysmography (PPG) to study vascular ED with standard penile Doppler ultrasonography. Men diagnosed with vascular ED for at least 6 months and nominated for penile ultrasonography were included. PPG signals were collected during the ultrasound examination. All beat-to-beat PPG waveforms were aligned with the peak and averaged to one representative template waveform for feature analysis, including amplitude differences (APD) index, reflection time index (RTI), augmentation index (AI), and perfusion index (PI). An inverse correlation was found between end-erection amplitude and both erection hardness score (EHS) and resistive index (RI). APD index and EHS as well as the international index of erectile function-5 (IIEF) and RI were positively correlated. RTI and AI were inversely correlated to IIEF and RI. PI was positively correlated to RI. PPG may therefore be useful as a noninvasive, convenient, technique for sexual function evaluation.