The discriminatory value of cardiorespiratory interactions in distinguishing awake from anaesthetised states: a randomised observational study

Evaluation of the Relationship between Baseline Autonomic Tone and Haemodynamic Effects of Dexmedetomidine

Dexmedetomidine, a central α-2 agonist, is used for procedural sedation and for conscious sedation influences on heart rate and blood pressure. Authors verified whether it is possible to predict bradycardia and hypotension with the use of heart rate variability (HRV) analysis for an autonomic nervous system (ANS) activity assessment. The study included adult patients of both sexes with an ASA score of I or II scheduled for ophthalmic surgery to be performed under sedation. The loading dose of dexmedetomidine was followed by a 15 min infusion of the maintenance dose. The frequency domain heart rate variability parameters from the 5-min Holter electrocardiogram recordings before dexmedetomidine administration were used for the analysis. The statistical analysis also included pre-drug heart rate and blood pressure as well as patient age and sex. The data from 62 patients were analysed. There was no relationship between the decrease in heart rate (42% of cases) and initial HRV parameters, haemodynamic parameters or sex and age of patients. In multivariate analysis, the only risk factor for a decrease in mean arterial pressure (MAP) > 15% from the pre-drug value (39% of cases) was the systolic blood pressure before dexmedetomidine administration as well as for a >15% decrease in MAP sustained at more than one consecutive time point (27% of cases). The initial condition of the ANS did not correlate with the incidence of bradycardia or hypotension; HRV analysis was not helpful in predicting the abovementioned side effects of dexmedetomidine.

Optimizing phase variability threshold for automated synchrogram analysis of cardiorespiratory interactions in amateur cyclists

We propose a procedure suitable for automated synchrogram analysis for setting the threshold below which phase variability between two marker event series is of such a negligible amount that the null hypothesis of phase desynchronization can be rejected. The procedure exploits the principle of maximizing the likelihood of detecting phase synchronization epochs and it is grounded on a surrogate data approach testing the null hypothesis of phase uncoupling. The approach was applied to assess cardiorespiratory phase interactions between heartbeat and inspiratory onset in amateur cyclists before and after 11-week inspiratory muscle training (IMT) at different intensities and compared to a more traditional approach to set phase variability threshold. The proposed procedure was able to detect the decrease in cardiorespiratory phase locking strength during vagal withdrawal induced by the modification of posture from supine to standing. IMT had very limited effects on cardiorespiratory phase synchronization strength and this result held regardless of the training intensity. In amateur athletes training, the inspiratory muscles did not limit the decrease in cardiorespiratory phase synchronization observed in the upright position as a likely consequence of the modest impact of this respiratory exercise, regardless of its intensity, on cardiac vagal control. This article is part of the theme issue 'Advanced computation in cardiovascular physiology: new challenges and opportunities'.

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

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

Physical fitness contributes to cardio-respiratory synchronization

Cardio-respiratory synchronization is a phenomenon of particular interest- especially at a 1:1 ratio- and may give greater insight into the underlying mechanisms of cardio-respiratory communication. Synchronization of this ratio is hypothesised to occur when breathing rate exceeds heart rate, which is the premise of this research. A novel experimental design focused on guiding elevated respiration to induce the entrainment of heart rate, and produce an equivalent rise in value. Application of instantaneous phase for identification and analysis of synchronization allowed for a reliable method of measuring the interaction between these stochastic processes. We have identified 1:1 phase synchronization in all volunteers measured. Longer synchronization episodes were observed reliably in athletic individuals, corroborating previous research for spontaneous breathing. This observation suggests that cardio-respiratory synchronization at all respiration rates is associated with a common underlying communication mechanism. Furthermore, it presents cardio-respiratory synchronization as a potential future measurement of fitness and autonomic health.

Measuring depth of anaesthesia using changes in directional connectivity: a comparison with auditory middle latency response and estimated bispectral index during propofol anaesthesia

General anaesthesia is associated with changes in connectivity between different regions of the brain, the assessment of which has the potential to provide a novel marker of anaesthetic effect. We propose an index that quantifies the strength and direction of information flow in electroencephalographic signals collected across the scalp, assess its performance in discriminating 'wakefulness' from 'anaesthesia', and compare it with estimated bispectral index and the auditory middle latency response. We used a step-wise slow induction of anaesthesia in 10 patients to assess graded changes in electroencephalographic directional connectivity at propofol effect-site concentrations of 2 μg.ml^-1 , 3 μg.ml^-1 and 4 μg.ml^-1 . For each stable effect-site concentration, connectivity was estimated from multichannel electroencephalograms using directed coherence, together with middle latency response and estimated bispectral index. We used a linear support vector machine classifier to compare the performance of the different electroencephalographic features in discriminating wakefulness from anaesthesia. We found a significant reduction in the strength of long-range connectivity (interelectrode distance > 10 cm) (p < 0.008), and a reversal of information flow from markedly postero-frontal to fronto-posterior (p < 0.006) between wakefulness and a propofol effect-site concentration of 2 μg.ml^-1 . This then remained relatively constant as effect-site concentration increased, consistent with a step change in directed coherence with anaesthesia. This contrasted with the gradual change with increasing anaesthetic dose observed for estimated bispectral index and middle latency response. Directed coherence performed best in discriminating wakefulness from anaesthesia with an accuracy of 95%, indicating the potential of this new method (on its own or combined with others) for monitoring adequacy of anaesthesia.

Development of a new analgesic index using nasal photoplethysmography

Although surrogate measures to quantify pain intensity have been commercialised, there is a need to develop a new index with improved accuracy. The aim of this study was to develop a new analgesic index using nasal photoplethysmography data. The specially designed sensor was placed between the columella and the nasal septum to acquire nasal photoplethysmography in surgical patients. Nasal photoplethysmography and Surgical Pleth Index^® (GE Healthcare) data were obtained for 14 min both in the absence (pre-operatively) or presence (postoperatively) of pain in a group of surgical patients, each patient acting as their own control. Various dynamic photoplethysmography variables were extracted to quantify pain intensity; the most accurate index was selected using logistic regression as a classifier. The area under the curve of the receiver-operating characteristic curve was measured to evaluate the accuracy of final model predictions. In total, 12,012 heart beats from 89 patients were used to develop a new Nasal Photoplethysmography Index for analgesic depth quantification. The two-variable model (a combination of diastolic peak point variation and heart beat interval variation) was most accurate in discriminating between the presence and absence of pain (numerical rating scale (NRS) ≥ 3). The accuracy and area under the curve of the receiver-operating characteristic curve for the Nasal Photoplethysmography Index were 75.3% and 0.8018, respectively, and 64.8% and 0.7034, respectively, for the Surgical Pleth Index. The Nasal Photoplethysmography Index clearly distinguished pain (NRS ≥ 3) in awake surgical patients with postoperative pain. The Nasal Photoplethysmography Index performed better than the Surgical Pleth Index. Further validation studies are needed to evaluate its feasibility to quantify pain intensity during general anaesthesia.

On the difference of cardiorespiratory synchronisation and coordination

Cardiorespiratory phase synchronisation (CRS) is a type of cardiorespiratory coupling that manifests through a prediliction for heart beats to occur at specific points relative to the phase of the respiratory cycle. It has been under investigation for nearly 20 years, and while it seems to be mostly occurring in relaxed states such as deep sleep and anesthesia, no clear clinical implications have been established. Cardiorespiratory coordination (CRC) is a recent development in this field where the relationship between the respiratory onset and heart beat is analysed in the time domain and the possible relationship of each heart beat is considered for both the previous and the next respiratory onset. This ostensibly closely related effect must not only show relevant information content but also do so independent of CRS in order to be relevant for future studies. In this paper, we investigate CRC and its relation to CRS mainly using graphical and statistical methods on two exemplary datasets: measurements from a pregnant woman participating in a preeclampsia study and those from a man suffering from sleep apnea. We show fundamental differences between the results of both approaches and are able to show a formerly unknown dependency between the heart activity and respiratory rate, potentially indicating heartbeat-initiated inspiration. Despite their differences, methods developed for the quantification of CRS can be adapted to CRC. Completing the comparison is an investigation into the relationship between CRC and respiratory sinus arrhythmia. Similar to previous results for CRS, the two effects are found to be orthogonal, meaning that they can be observed independently or in conjunction.

EEG artifacts reduction by multivariate empirical mode decomposition and multiscale entropy for monitoring depth of anaesthesia during surgery

Electroencephalography (EEG) has been widely utilized to measure the depth of anaesthesia (DOA) during operation. However, the EEG signals are usually contaminated by artifacts which have a consequence on the measured DOA accuracy. In this study, an effective and useful filtering algorithm based on multivariate empirical mode decomposition and multiscale entropy (MSE) is proposed to measure DOA. Mean entropy of MSE is used as an index to find artifacts-free intrinsic mode functions. The effect of different levels of artifacts on the performances of the proposed filtering is analysed using simulated data. Furthermore, 21 patients' EEG signals are collected and analysed using sample entropy to calculate the complexity for monitoring DOA. The correlation coefficients of entropy and bispectral index (BIS) results show 0.14 ± 0.30 and 0.63 ± 0.09 before and after filtering, respectively. Artificial neural network (ANN) model is used for range mapping in order to correlate the measurements with BIS. The ANN method results show strong correlation coefficient (0.75 ± 0.08). The results in this paper verify that entropy values and BIS have a strong correlation for the purpose of DOA monitoring and the proposed filtering method can effectively filter artifacts from EEG signals. The proposed method performs better than the commonly used wavelet denoising method. This study provides a fully adaptive and automated filter for EEG to measure DOA more accuracy and thus reduce risk related to maintenance of anaesthetic agents.

Alterations in the coupling functions between cortical and cardio-respiratory oscillations due to anaesthesia with propofol and sevoflurane

The precise mechanisms underlying general anaesthesia pose important and still open questions. To address them, we have studied anaesthesia induced by the widely used (intravenous) propofol and (inhalational) sevoflurane anaesthetics, computing cross-frequency coupling functions between neuronal, cardiac and respiratory oscillations in order to determine their mutual interactions. The phase domain coupling function reveals the form of the function defining the mechanism of an interaction, as well as its coupling strength. Using a method based on dynamical Bayesian inference, we have thus identified and analysed the coupling functions for six relationships. By quantitative assessment of the forms and strengths of the couplings, we have revealed how these relationships are altered by anaesthesia, also showing that some of them are differently affected by propofol and sevoflurane. These findings, together with the novel coupling function analysis, offer a new direction in the assessment of general anaesthesia and neurophysiological interactions, in general.

Evaluation of the relationship between baseline autonomic tone and the vagotonic effect of a bolus dose of remifentanil

Remifentanil stimulates the parasympathetic nervous system, and patients with increased parasympathetic tone may be at greater risk of bradycardia after its administration. We aimed to establish if adult patients with increased baseline parasympathetic tone were at higher risk of bradycardia and hypotension when given a bolus dose of remifentanil. Seventy adults (age 20-60 years and ASA physical status 1 or 2) were given remifentanil 1 μg.kg(-1) . A Holter ECG monitor was used to assess heart rate changes. Heart rate variability in the frequency domain during the 5 min after remifentanil administration was analysed. Multivariate analysis demonstrated that baseline heart rate was the only independent predictor of remifentanil-induced bradycardia [odds ratio (95% CI) 0.877 (0.796-0.966)]. The vagotonic action of remifentanil does not appear to be related to baseline autonomic tone in adult patients.