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Obstructive sleep apnea (OSA) is a highly heterogeneous disorder, with diverse pathways to disease, expression of disease, susceptibility to co‐morbidities and response to therapy, and is ideally suited to precision medicine approaches. Clinically, the content of the information‐rich polysomnogram (PSG) is not currently fully utilized in determining patient management. Novel PSG parameters such as hypoxic burden, pulse transit time, cardiopulmonary coupling and the frequency representations of PSG sensor signals could predict a variety of cardiovascular disease, cancer and neurodegeneration co‐morbidities. The PSG can also be used to identify key pathophysiological parameters such as loop gain, arousal threshold and muscle compensation which can enhance understanding of the causes of OSA in an individual, and thereby guide choices on therapy. Machine learning methods performing their own parameter extraction coupled with large PSG data sets offer an exciting opportunity for discovering new links between the PSG variables and disease outcomes. By exploiting existing and emerging analytical methods, the PSG may offer a pathway to personalized management for OSA. [ABSTRACT FROM AUTHOR]

Objective: To compare fetal heart rate (FHR) signals acquired simultaneously by an external ultrasound probe and a scalp electrode during the second stage of labor. Methods: This was a prospective observational study in a labor ward of a tertiary care university hospital. The population was women in labor with uneventful singleton pregnancies at term. Simultaneous external and internal FHR monitoring was performed in 67 consecutively recruited women during the second stage of labor. Cases were subsequently excluded if the trace length was under 40 min, cesarean birth occurred, or the interval between trace-end and birth exceeded 5 min, leaving a total of 33 traces for analysis. The last 40-60 min of these traces were analyzed by a computer system (Omniview-SisPorto® 3.5; Speculum®, Lisbon, Portugal) to quantify cardiotocographic parameters. Paired sample t-test and Bland-Altman limits of agreement (LoA) were used for statistical analysis, setting significance at 0.05. The main outcome measures were signal loss, FHR baseline, periodic events, and percentage of periodic events coinciding with contractions. Results: A higher signal loss was observed with external monitoring [10% vs. 4%; P<0.001, LoA=(-6, 18)]. No differences were found in mean FHR baseline [129 bpm vs. 130 bpm, P=0.245, LoA=(-15, 12)], but more accelerations [12 vs. 8, P<0.001, LoA=(-5, 13)] and less decelerations [8 vs. 10, P<0.001, LoA=(-8, 4)] were detected with external monitoring. With this method there were also more accelerations (66% vs. 55%, P=0.036) and less decelerations (68% vs. 81%, P=0.017) coinciding with contractions. Conclusions: External FHR monitoring during the second stage of labor results in higher signal loss, increased number of accelerations, and decreased number of decelerations when compared with internal monitoring. [ABSTRACT FROM AUTHOR]

Studies have shown that long-term vagal stimulation is protective against ventricular fibrillation; however, the effects of acute vagal stimulation during ventricular fibrillation in the normal heart have not been investigated. We examined the effects of acute vagal stimulation on ventricular fibrillation in a canine model. In 4 dogs, we induced 30-second periods of ventricular fibrillation by means of intraventricular pacing. During 2 of the 4 periods of fibrillation that we analyzed, vagal stimulation was delivered through electrodes in the caudal ends of the vagus nerves. Noncontact unipolar electrograms were recorded from 3 ventricular regions: the basal septum, apical septum, and lateral free wall. We then computed the most frequent cycle length, mean organization index, and mean electrogram amplitude for each region. During fibrillation, vagal stimulation shortened the most frequent cycle lengths in the basal septum (P=0.02) and apical septum (P=0.0001), but not in the lateral wall (P=0.46). In addition, vagal stimulation significantly reduced the mean organization indices in the apical septum (P <0.001) and lateral wall (P <0.001), but not in the basal septum (P=0.19). Furthermore, vagal stimulation raised the mean electrogram amplitude in the basal septum (P <0.01) but lowered it substantially in the apical septum (P=0.00005) and lateral wall (P=0.00003). We conclude that vagal stimulation acutely affects the characteristics of ventricular fibrillation in canine myocardium in a spatially heterogeneous manner. This nonuniformity of response may have implications with regard to manipulating the autonomic system as a means of modifying the substrate for ventricular dysrhythmias. [ABSTRACT FROM AUTHOR]

Background Respiratory rate is an important measurement in patient care but frequently poorly assessed. We set out to develop a simple non-invasive device to reliably measure respiratory movements and estimate respiratory rate, in clinical circumstances. Methods Respiratory movement was detected with an encapsulated tri-axial accelerometer (Orient speck) and the data transmitted wirelessly to a computer for analysis. We studied subjects after gynaecological surgery who received opioid analgesia, and compared the derived signal with a signal from nasal cannula using directly matched breaths and within the same 5 min epoch. We analysed the signals for 5 min epochs over a 15 h recording period. Results For matched breath analysis, the instantaneous respiratory rates matched within 2 bpm on 86% of occasions. A similar match was found between epoch averages of the respiratory rate. The mean absolute difference between the respiratory rate measured by nasal cannula and Orient speck was 0.6 bpm. The Orient speck generated reliable measures of respiratory rate every 5 min in 95.4% of epochs. Conclusions The Orient speck provides a reliable measure of respiratory rate at frequent intervals in subjects receiving patient-controlled morphine analgesia after surgery. [ABSTRACT FROM AUTHOR]

Purpose: The occurrence of abnormal dynamics in a physiological system can become manifest as a sudden qualitative change in the behavior of characteristic physiologic variables. We assume that this is what happens in the brain with regard to epilepsy. We consider that neuronal networks involved in epilepsy possess multistable dynamics (i.e., they may display several dynamic states). To illustrate this concept, we may assume, for simplicity, that at least two states are possible: an interictal one characterized by a normal, apparently random, steady state of ongoing activity, and another one that is characterized by the paroxysmal occurrence of a synchronous oscillations (seizure). Methods: By using the terminology of the mathematics of nonlinear systems, we can say that such a bistable system has two attractors, to which the trajectories describing the system's output converge, depending on initial conditions and on the system's parameters. In phase-space, the basins of attraction corresponding to the two states are separated by what is called a “separatrix.” We propose, schematically, that the transition between the normal ongoing and the seizure activity can take place according to three basic models: Model I: In certain epileptic brains (e.g., in absence seizures of idiopathic primary generalized epilepsies), the distance between “normal steady state” and “paroxysmal” attractors is very small in contrast to that of a normal brain (possibly due to genetic and/or developmental factors). In the former, discrete random fluctuations of some variables can be sufficient for the occurrence of a transition to the paroxysmal state. In this case, such seizures are not predictable. Model II and model III: In other kinds of epileptic brains (e.g., limbic cortex epilepsies), the distance between “normal steady-state” and “paroxysmal” attractors is, in general, rather large, such that random fluctuations, of themselves, are commonly not capable of triggering a seizure. However, in these brains, neuronal networks have abnormal features characterized by unstable parameters that are very vulnerable to the influence of endogenous (model II) and/or exogenous (model III) factors. In these cases, these critical parameters may gradually change with time, in such a way that the attractor can deform either gradually or suddenly, with the consequence that the distance between the basin of attraction of the normal state and the separatrix tends to zero. This can lead, eventually, to a transition to a seizure. Results: The changes of the system's dynamics preceding a seizure in these models either may be detectable in the EEG and thus the route to the seizure may be predictable, or may be unobservable by using only measurements of the dynamical state. It is thinkable, however, that in some cases, changes in the excitability state of the underlying networks may be uncovered by using appropriate stimuli configurations before changes in the dynamics of the ongoing EEG activity are evident. A typical example of model III that we discuss here is photosensitive epilepsy. Conclusions: We present an overview of these basic models, based on neurophysiologic recordings combined with signal analysis and on simulations performed by using computational models of neuronal networks. We pay special attention to recent model studies and to novel experimental results obtained while analyzing EEG features preceding limbic seizures and during intermittent photic stimulation that precedes the transition to paroxysmal epileptic activity. [ABSTRACT FROM AUTHOR]