Parametric analysis of an integrated cardio-respiratory model in preterm newborns during apnea.

The analysis of the complex interactions involved in the acute physiological response to apnea-bradycardia events in preterm newborns remains a challenging task. This paper presents a novel integrated model of cardio-respiratory interactions, adapted to preterm newborns. A sensitivity analysis, based Morris' screening method, was applied to study the effects of physiological parameters on heart rate and desaturation, during the simulation of a 15-seconds apnea-bradycardia episode. The most sensitive parameters are associated with fundamental, integrative physiological mechanisms involving: (i) respiratory mechanics (intermediate airways and lung compliance), (ii) fraction of inspired oxygen, (iii) metabolic rates (oxygen consumption rate), (iv) heart rate regulation and (v) chemoreflex (gain). Results highlight the relevant influence of physiological variables, involved in preterm apnea-bradycardia events.

Fracture Resistance of Chairside CAD/CAM Molar Crowns Fabricated with Different Lithium Disilicate Ceramic Materials

PURPOSE: To compare the fracture resistance of five different groups of chairside CAD/CAM molar crowns fabricated from various lithium disilicate ceramic materials (LDC): one conventional precrystallized CAD/CAM LDC, two novel precrystallized LDCs, and one fully crystallized LDC tested both with and without optional sintering. MATERIALS AND METHODS: A total of 60 chairside CAD/CAM lithium disilicate molar crowns (n = 12 per group) with 1.5-mm occlusal thickness and a 1.0-mm chamfer finish were designed and fabricated with a chairside CAD/CAM system (CEREC, Dentsply Sirona). The restorations were divided into five groups: (1) IPS e.max CAD; (2) Amber Mill; (3) Straumann n!ce; (4) Straumann n!ce with optional sintering; and (5) Supreme CAD. Restorations were cemented using conventional resin luting cement and primer system to 3D-printed resin dies. Bonded restorations were loaded for 100,000 cycles with 275-N force, and the load at break (LB) and peak load (PL) until fracture were measured. SEM images of fracture surfaces on the printed dies were obtained. RESULTS: Fracture resistance was significantly different depending on the material. Supreme CAD showed the highest fracture resistance (LB: 1,557.2 N; PL: 1,785.8 N), followed by Amber Mill (LB: 1,393.0 N; PL: 1,604.2 N) and IPS e.max CAD (LB: 1,315.7 N; PL: 1,461.9 N). Straumann n!ce without (LB: 862.4 N; PL: 942.9 N) and with the optional sintering (LB: 490.4 N; PL: 541.0 N) showed significantly lower fracture resistance than the others. CONCLUSION: The fracture resistance of chairside CAD/CAM lithium disilicate molar crowns varied depending on the material, and the novel materials did not perform as well as the conventional equivalents. Fully crystallized lithium disilicate ceramic block materials showed lower fracture resistance than precrystallized counterparts and should be used with caution in the clinic, especially with optional sintering.

Fracture Resistance of Chairside CAD/CAM Molar Crowns Fabricated with Different Lithium Disilicate Ceramic Materials.

PURPOSE: To compare the fracture resistance of five different groups of chairside CAD/CAM molar crowns fabricated from various lithium disilicate ceramic materials (LDC): one conventional precrystallized CAD/CAM LDC, two novel precrystallized LDCs, and one fully crystallized LDC tested both with and without optional sintering. MATERIALS AND METHODS: A total of 60 chairside CAD/CAM lithium disilicate molar crowns (n = 12 per group) with 1.5-mm occlusal thickness and a 1.0-mm chamfer finish were designed and fabricated with a chairside CAD/CAM system (CEREC, Dentsply Sirona). The restorations were divided into five groups: (1) IPS e.max CAD; (2) Amber Mill; (3) Straumann n!ce; (4) Straumann n!ce with optional sintering; and (5) Supreme CAD. Restorations were cemented using conventional resin luting cement and primer system to 3D-printed resin dies. Bonded restorations were loaded for 100,000 cycles with 275-N force, and the load at break (LB) and peak load (PL) until fracture were measured. SEM images of fracture surfaces on the printed dies were obtained. RESULTS: Fracture resistance was significantly different depending on the material. Supreme CAD showed the highest fracture resistance (LB: 1,557.2 N; PL: 1,785.8 N), followed by Amber Mill (LB: 1,393.0 N; PL: 1,604.2 N) and IPS e.max CAD (LB: 1,315.7 N; PL: 1,461.9 N). Straumann n!ce without (LB: 862.4 N; PL: 942.9 N) and with the optional sintering (LB: 490.4 N; PL: 541.0 N) showed significantly lower fracture resistance than the others. CONCLUSION: The fracture resistance of chairside CAD/CAM lithium disilicate molar crowns varied depending on the material, and the novel materials did not perform as well as the conventional equivalents. Fully crystallized lithium disilicate ceramic block materials showed lower fracture resistance than precrystallized counterparts and should be used with caution in the clinic, especially with optional sintering.

Echocardiographic view and feature selection for the estimation of the response to CRT.

Cardiac resynchronization therapy (CRT) is an implant-based therapy applied to patients with a specific heart failure (HF) profile. The identification of patients that may benefit from CRT is a challenging task and the application of current guidelines still induce a non-responder rate of about 30%. Several studies have shown that the assessment of left ventricular (LV) mechanics by speckle tracking echocardiography can provide useful information for CRT patient selection. A comprehensive evaluation of LV mechanics is normally performed using three different echocardioraphic views: 4, 3 or 2-chamber views. The aim of this study is to estimate the relative importance of strain-based features extracted from these three views, for the estimation of CRT response. Several features were extracted from the longitudinal strain curves of 130 patients and different methods of feature selection (out-of-bag random forest, wrapping and filtering) have been applied. Results show that more than 50% of the 20 most important features are calculated from the 4-chamber view. Although features from the 2- and 3-chamber views are less represented in the most important features, some of the former have been identified to provide complementary information. A thorough analysis and interpretation of the most informative features is also provided, as a first step towards the construction of a machine-learning chain for an improved selection of CRT candidates.

Early bradycardia detection and therapeutic interventions in preterm infant monitoring.

In very preterm infants, cardio-respiratory events and associated hypoxemia occurring during early postnatal life have been associated with risks of retinopathy, growth alteration and neurodevelopment impairment. These events are commonly detected by continuous cardio-respiratory monitoring in neonatal intensive care units (NICU), through the associated bradycardia. NICU nurse interventions are mainly triggered by these alarms. In this work, we acquired data from 52 preterm infants during NICU monitoring, in order to propose an early bradycardia detector which is based on a decentralized fusion of three detectors. The main objective is to improve automatic detection under real-life conditions without altering performance with respect to that of a monitor commonly used in NICU. We used heart rate lower than 80 bpm during at least 10 sec to define bradycardia. With this definition we observed a high rate of false alarms (64%) in real-life and that 29% of the relevant alarms were not followed by manual interventions. Concerning the proposed detection method, when compared to current monitors, it provided a significant decrease of the detection delay of 2.9 seconds, without alteration of the sensitivity (97.6% vs 95.2%) and false alarm rate (63.7% vs 64.1%). We expect that such an early detection will improve the response of the newborn to the intervention and allow for the development of new automatic therapeutic strategies which could complement manual intervention and decrease the sepsis risk.

Detection of Apnea Bradycardia from ECG Signals of Preterm Infants Using Layered Hidden Markov Model.

Apnea-bradycardia (AB) is a common complication in prematurely born infants, which is associated with reduced survival and neurodevelopmental outcomes. Thus, early detection or predication of AB episodes is critical for initiating preventive interventions. To develop automatic real-time operating systems for early detection of AB, recent advances in signal processing can be employed. Hidden Markov Models (HMM) are probabilistic models with the ability of learning different dynamics of the real time-series such as clinical recordings. In this study, a hierarchy of HMMs named as layered HMM was presented to detect AB episodes from pre-processed single-channel Electrocardiography (ECG). For training the hierarchical structure, RR interval, and width of QRS complex were extracted from ECG as observations. The recordings of 32 premature infants with median 31.2 (29.7, 31.9) weeks of gestation were used for this study. The performance of the proposed layered HMM was evaluated in detecting AB. The best average accuracy of 97.14 ± 0.31% with detection delay of - 5.05 ± 0.41 s was achieved. The results show that layered structure can improve the performance of the detection system in early detecting of AB episodes. Such system can be incorporated for more robust long-term monitoring of preterm infants.

Apnea bradycardia detection based on new coupled hidden semi Markov model.

In this paper, a method for apnea bradycardia detection in preterm infants is presented based on coupled hidden semi Markov model (CHSMM). CHSMM is a generalization of hidden Markov models (HMM) used for modeling mutual interactions among different observations of a stochastic process through using finite number of hidden states with corresponding resting time. We introduce a new set of equations for CHSMM to be integrated in a detection algorithm. The detection algorithm was evaluated on a simulated data to detect a specific dynamic and on a clinical dataset of electrocardiogram signals collected from preterm infants for early detection of apnea bradycardia episodes. For simulated data, the proposed algorithm was able to detect the desired dynamic with sensitivity of 96.67% and specificity of 98.98%. Furthermore, the method detected the apnea bradycardia episodes with 94.87% sensitivity and 96.52% specificity with mean time delay of 0.73 s. The results show that the algorithm based on CHSMM is a robust tool for monitoring of preterm infants in detecting apnea bradycardia episodes. Graphical Abstract Apnea Bradycardia detection using Coupled hidden semi Markov Model from electrocardiography. In this model, a sequence of hidden states is assigned to each observation based on the effects of previous states of all observations.

Prediction of response to cardiac resynchronization therapy using a multi-feature learning method.

We hypothesized that a multiparametric evaluation, based on the combination of electrocardiographic and echocardiographic parameters, could enhance the appraisal of the likelihood of reverse remodeling and prognosis of favorable clinical evolution to improve the response of cardiac resynchronization therapy (CRT). Three hundred and twenty-three heart failure patients were retrospectively included in this multicenter study. 221 patients (68%) were responders, defined by a decrease in left ventricle end-systolic volume ≥15% at the 6-month follow-up. In addition, strain data coming from echocardiography were analyzed with custom-made signal processing methods. Integrals of regional longitudinal strain signals from the beginning of the cardiac cycle to strain peak and to the instant of aortic valve closure were analyzed. QRS duration, septal flash and different other features manually extracted were also included in the analysis. The random forest (RF) method was applied to analyze the relative feature importance, to select the most significant features and to build an ensemble classifier with the objective of predicting response to CRT. The set of most significant features was composed of Septal Flash, E, E/A, E/EA, QRS, left ventricular end-diastolic volume and eight features extracted from strain curves. A Monte Carlo cross-validation method with 100 runs was applied, using, in each run, different random sets of 80% of patients for training and 20% for testing. Results show a mean area under the curve (AUC) of 0.809 with a standard deviation of 0.05. A multiparametric approach using a combination of echo-based parameters of left ventricular dyssynchrony and QRS duration helped to improve the prediction of the response to cardiac resynchronization therapy.

Model-based estimation of left ventricular pressure and myocardial work in aortic stenosis.

This paper proposes a model-based estimation of left ventricular (LV) pressure for the evaluation of constructive and wasted myocardial work of patients with aortic stenosis (AS). A model of the cardiovascular system is proposed, including descriptions of i) cardiac electrical activity, ii) elastance-based cardiac cavities, iii) systemic and pulmonary circulations and iv) heart valves. After a sensitivity analysis of model parameters, an identification strategy was implemented using a Monte-Carlo cross-validation approach. Parameter identification procedure consists in two steps for the estimation of LV pressures: step 1) from invasive, intraventricular measurements and step 2) from non-invasive data. The proposed approach was validated on data obtained from 12 patients with AS. The total relative errors between estimated and measured pressures were on average 11.9% and 12.27% and mean R2 were equal to 0.96 and 0.91, respectively for steps 1 and 2 of parameter identification strategy. Using LV pressures obtained from non-invasive measurements (step 2) and patient-specific simulations, Global Constructive (GCW), Wasted (GWW) myocardial Work and Global Work Efficiency (GWE) parameters were calculated. Correlations between measures and model-based estimations were 0.88, 0.80, 0.91 respectively for GCW, GWW and GWE. The main contributions concern the proposal of the parameter identification procedure, applied on an integrated cardiovascular model, able to reproduce LV pressure specifically to each AS patient, by non-invasive procedures, as well as a new method for the non-invasive estimation of constructive, wasted myocardial work and work efficiency in AS.

Dynamic changes in ventricular depolarization during exercise in patients with Brugada syndrome.

Brugada syndrome (BS) is a genetic pathological condition associated with a high risk for sudden cardiac death (SCD). Ventricular depolarization disorders have been suggested as a potential electrophysiological mechanism associated with high SCD risk on patients with BS. This paper aims to characterize the dynamic changes of ventricular depolarization observed during physical exercise in symptomatic and asymptomatic BS patients. To this end, cardiac ventricular depolarization features were automatically extracted from 12-lead ECG recordings acquired during standardized exercise stress test in 110 BS patients, of whom 25 were symptomatic. Conventional parameters were evaluated, including QRS duration, R and S wave amplitudes ([Formula: see text], [Formula: see text]), as well as QRS morphological features, such as up-stroke and down-stroke slopes of the R and S waves ([Formula: see text], [Formula: see text] and [Formula: see text]). The effects of physical exercise and recovery on the dynamics of these markers were assessed in both BS populations. Features showing significantly different dynamics between the studied groups were used alone and in combination with the clinical characteristics of the patients in a logistic regression analysis. Results show larger changes in the second half of the QRS complex through [Formula: see text] and [Formula: see text] measured in the right precordial leads for asymptomatic patients, especially during recovery, when the vagal tone is more pronounced. Multivariate analysis involving both types of features resulted in a reduced model of three relevant features ([Formula: see text] in lead V2, Sex and heart rate recovery, HRR), which achieved a suitable discrimination performance between groups; sensitivity = 80% and specificity = 75% (AUC = 83%). However, after controlling the model for possible confounding factors, only one feature ([Formula: see text]) remained meaningful. This adjusted model significantly improved the overall discrimination performance by up to: sensitivity = 84% and specificity = 100% (AUC = 94%). The study highlights the importance of physical exercise test to unmask differentiated behaviors between symptomatic and asymptomatic BS patients through depolarization dynamic analysis. This analysis together with the obtained model may help to identify asymptomatic patients at low or high risk of future cardiac events, but it should be confirmed by further prospective studies.

Sensitivity Analysis of a Left Ventricle Model in the Context of Intraventricular Dyssynchrony.

The objective of the current study was to propose a sensitivity analysis of a 3D left ventricle model in order to assess the influence of parameters on myocardial mechanical dispersion. A finite element model of LV electro-mechanical activity was proposed and a screening method was used to evaluate the sensitivity of model parameters on the standard deviation of time to peak strain. Results highlight the importance of propagation parameters associated with septal and lateral segments activation. Simulated curves were compared to myocardial strains, obtained from echocardiography of one healthy subject and one patient diagnosed with intraventricular dyssynchrony and coronary artery disease. Results show a close match between simulation and clinical strains and illustrate the model ability to reproduce myocardial strains in the context of intraventricular dyssynchrony.

Improving methodology in heart rate variability analysis for the premature infants: Impact of the time length.

BACKGROUND: Heart rate variability (HRV) has been emerging in neonatal medicine. It may help for the early diagnosis of pathology and estimation of autonomous maturation. There is a lack of standardization and automation in the selection of the sequences to analyze and some features have not been explored in this specific population. The main objective of this study was to analyze the impact of the time length of the sequences on the estimation of linear and non-linear HRV features, including horizontal visibility graphs (HVG). METHODS: HRV features were repeatedly measured with linear and non-linear methods on 2-, 5-, 10-minute sequences selected from the longest 15-min sequence and recorded on a weekly basis in 39 infants less than 31 weeks at birth. The associations between HRV measurements were analyzed through principal component analysis and k-means clustering. The effects of the time lengths on HRV measurements and post-menstrual age (PMA) were analyzed by linear mixed effect model for repeated measures. RESULTS: The domains of analysis were concordant for their descriptive parameters of short (rMSSD, SD1 and HF) and long-term (SD, SD2 and LF) variability. α1 was correlated with the LF/HF and SD2/SD1. DC and AC were correlated with short-term variability estimates and significantly increased with GA and PMA. Shortening the windows of analysis increased the random measurement error for all the features and increased the bias for all but short term features and HVGs. CONCLUSION: The linear and non-linear measurements of HRV are correlated each other. Shortening the windows of analysis increased the random error for all the features and increased the bias for all but short term features and HVGs. Short-term HRV can be an index for evaluating the maturation in whatever sequence length.

Recursive model identification for the analysis of the autonomic response to exercise testing in Brugada syndrome.

This paper proposes the integration and analysis of a closed-loop model of the baroreflex and cardiovascular systems, focused on a time-varying estimation of the autonomic modulation of heart rate in Brugada syndrome (BS), during exercise and subsequent recovery. Patient-specific models of 44 BS patients at different levels of risk (symptomatic and asymptomatic) were identified through a recursive evolutionary algorithm. After parameter identification, a close match between experimental and simulated signals (mean error = 0.81%) was observed. The model-based estimation of vagal and sympathetic contributions were consistent with physiological knowledge, enabling to observe the expected autonomic changes induced by exercise testing. In particular, symptomatic patients presented a significantly higher parasympathetic activity during exercise, and an autonomic imbalance was observed in these patients at peak effort and during post-exercise recovery. A higher vagal modulation during exercise, as well as an increasing parasympathetic activity at peak effort and a decreasing vagal contribution during post-exercise recovery could be related with symptoms and, thus, with a worse prognosis in BS. This work proposes the first evaluation of the sympathetic and parasympathetic responses to exercise testing in patients suffering from BS, through the recursive identification of computational models; highlighting important trends of clinical relevance that provide new insights into the underlying autonomic mechanisms regulating the cardiovascular system in BS. The joint analysis of the extracted autonomic parameters and classic electrophysiological markers could improve BS risk stratification.

Differences in Brugada Syndrome Patients Through Ventricular Repolarization Analysis During Sleep.

Brugada syndrome (BS) is a genetic pathology that might cause sudden cardiac death (SCD) in patients with a structurally normal heart. Repolarization disorders have been postulated as a potential substrate for triggering cardiac arrhythmia in BS, that usually occur at rest or during sleep. In this paper, we have characterized ventricular repolarization markers during sleep on patients suffering from BS. To this end, standard 12-lead ECG recordings were analyzed in a population of 110 BS patients (25 symptomatic). The QT and the T-wave peak to T-wave end intervals (respectively QT and Tpe) were assessed from lead V5. The linear relationship between these markers and the instantaneous heart rate period (RR interval) are determined during each hour and for the whole sleep period. From the models obtained, corrected QT and Tpe measures were then estimated for each patient at 60 beats/min (QT60 and Tpe60) and at the mean heart rate observed during the involved time interval (QTHR and TpeHR). Results show larger values for symptomatic patients in all markers, with significant differences with respect to the asymptomatic group in the case of Tpe (Tpe60: p = 0.0012; TpeHR: p = 0.0014). Moreover, the temporal profiles of these markers reveal major differences among BS subgroups during the last 3 hours of sleep, where symptomatic patients presented increased QT60/HR (p = 0.01) and Tpe60/HR (p <; 0.001), as compared to the initial sleep hours. We conclude that BS patients present different repolarization properties according to their symptomatology, especially during the final stage of sleep.

Quantification of Neural Conduction Block on the Rat Sciatic Nerve based on EMG Response.

Neural conduction block performed by balanced-charge kilohertz frequency alternating currents (KHFAC) has been identified as a potential technique for therapy delivery in different clinical setups. The underlying mechanisms that contribute to this phenomenon have been studied through computational models and animal experiments. However, the optimal stimulation parameters to achieve axonal conduction block are difficult to define, since they depend on the species, the nerve being targeted, as well as the technical and experimental setup. This study proposes an experimental setup along with an original data processing approach for the quantification of the effectiveness of neural conduction block. Experiments were performed on the sciatic nerve of two Sprague-Dawley rats, by evaluating different groups of stimulation parameters with varying amplitudes and frequencies, ranging from 1 to 10 mA and from 2 to 10 kHz, respectively. Results suggest that the effectiveness of axonal conduction block strongly depends on the selection of the stimulation parameters. In this work, more effective blockages were achieved for frequencies around 4 kHz and within an approximate amplitude range of 2 to 8 mA.

PEDOT:PSS electrodes for acute experimental evaluation of vagus nerve stimulation on rodents.

The vagus nerve (VN) is involved in the autonomic regulation of many physiological systems (cardiovascular, respiratory, gastrointestinal, etc.) and its stimulation is already an approved therapy for refractory epilepsy and depression. Other pathologies are thought to be treatable through vagus nerve stimulation (VNS), such as heart failure, cardiac arrhythmia, inflammation or auto-immune diseases. However, the efficacy of the stimulation is not always optimal, partly due to the materials and the architecture of currently available electrodes. Standard electrodes, composed of metallic rings that stimulate the whole diameter of the nerve, are not adapted to experimentations involving spatial selectivity. Efficient and selective charge injection is usually difficult to achieve simultaneously, especially in experimental setups using rodents, due to the thin diameter of their VN. In this paper, we show that we can take advantage of the high charge injection property of conducting polymers to acutely stimulate the vagus nerve in rodents, using individual active electrodes with dimensions $725\,\,\mu \mathrm{m}\times \,450\,\,\mu\mathrm{m}$. A particular PEDOT:PSS architecture integrating 12 active electrodes is developed and applied to the VN of one rat. A closed-loop VNS system developed in our previous works is used to stimulate the VN while analyzing the heart rate response. Results show the feasibility of this kind of electrodes for acute VNS on rodents and open the path towards new experimentations focused on selective stimulation and recording.

Global Sensitivity Analysis of a Cardiovascular Model for the Study of the Autonomic Response to Head-up Tilt Testing.

This paper proposes the integration and analysis of a mathematical model representing the cardiovascular system and its short-term autonomic response to head-up tilt (HUT) testing. A Latin Hypercube Sampling method was applied to design an optimal experimental space, including 19 model parameters coming from the cardiovascular and baroreflex control systems. Then, a global, variance-based sensitivity analysis was applied to quantity the effects of these parameters on heart rate and systolic blood pressure. Results highlight the relevant influence of the intrinsic heart rate and the sympathetic and parasympathetic baroreflex gains on heart rate regulation, as well as the impact of left ventricle diastolic parameters on systolic blood pressure. Moreover, a significant effect of right ventricle dynamics on blood pressure was noted. These results provide valuable information for the application of such an integrated model for the analysis of the autonomic mechanisms regulating the cardiovascular response induced by postural changes. In particular, they suggest a convenient set of parameters to be identified in a subject-specific manner.

Model-based analysis of the autonomic response to head-up tilt testing in Brugada syndrome.

The etiology of Brugada syndrome (BS) is complex and multifactorial, making risk stratification in this population a major challenge. Since changes in the autonomic modulation of these patients are commonly related to arrhythmic events, we analyze in this work whether the response to head-up tilt (HUT) testing on this population may provide useful, complementary information for risk stratification. In order to perform this analysis, a coupled physiological model integrating the cardiac electrical activity, the cardiovascular system and the baroreceptors reflex control of the autonomic function, in response to HUT is proposed. A sensitivity analysis was performed, based on a screening method, evidencing the influence of cardiovascular parameters on blood pressure and of baroreflex regulation on heart rate. The most sensitive parameters have been identified on a set of 20 subjects (8 controls and 12 BS patients), so as to assess subject-specific model parameters. According to the results, controls showed an increased sympathetic modulation after tilting, as well as a reduced left ventricular contractility was observed in symptomatic, with respect to asymptomatic BS patients. These results provide new insights regarding the autonomic mechanisms regulating the cardiovascular system in BS which might be used as a complementary source of information, along with classical electrophysiological parameters, for BS risk stratification.

Multivariate classification of Brugada syndrome patients based on autonomic response to exercise testing.

Ventricular arrhythmias in Brugada syndrome (BS) typically occur at rest and especially during sleep, suggesting that changes in the autonomic modulation may play an important role in arrhythmogenesis. The autonomic response to exercise and subsequent recovery was evaluated on 105 patients diagnosed with BS (twenty-four were symptomatic), by means of a time-frequency heart rate variability (HRV) analysis, so as to propose a novel predictive model capable of distinguishing symptomatic and asymptomatic BS populations. During incremental exercise, symptomatic patients showed higher HFnu values, probably related to an increased parasympathetic modulation, with respect to asymptomatic subjects. In addition, those extracted HRV features best distinguishing between populations were selected using a two-step feature selection approach, so as to build a linear discriminant analysis (LDA) classifier. The final features subset included one third of the total amount of extracted autonomic markers, mostly acquired during incremental exercise and active recovery, thus evidencing the relevance of these test segments in BS patients classification. The derived predictive model showed an improved performance with respect to previous works in the field (AUC = 0.92 ± 0.01; Se = 0.91 ± 0.06; Sp = 0.90 ± 0.05). Therefore, based on these findings, some of the analyzed HRV markers and the proposed model could be useful for risk stratification in Brugada syndrome.

Kinesthetic stimulation for obstructive sleep apnea syndrome: An "on-off" proof of concept trial.

Obstructive sleep apnea (OSA) occurs when the upper airway narrows or collapses due to the loss of upper airway muscle activation at sleep onset. This study investigated the effectiveness of triggered kinesthetic stimulation in patients with OSA. This proof-of-concept, open-label, multicenter prospective study was conducted on 24 patients with severe OSA. During a one night evaluation, kinesthetic stimulation was intermittently delivered in 30 minute periods. The duration of apneas and hypopneas during Stim on and Stim off periods were compared. Five hospital-based university centers in France participated. Sleep studies were evaluated by a single scorer at a core laboratory (CHU Grenoble). Results show that during the Stim on phases, statistically significant decreases in durations of apneas and hypopneas were observed in 56% and 46% of patients, respectively. Overall, 75% of patients showed an improvement in apneas or hypopneas durations. The mean reduction in durations for patients with a significant decrease was 4.86 seconds for apneas and 6.00 seconds for hypopneas. This proof of concept study is the first to identify kinesthetic stimulation as a potentially effective therapy for OSA. These data justify evaluation in a controlled study.