Delta Entropy of Heart Rate Variability Along with Deepening Anesthesia

Fractal Properties of Heart Rate Dynamics: A New Biomarker for Anesthesia-Biphasic Changes in General Anesthesia and Decrease in Spinal Anesthesia

Processed electroencephalogram (EEG) has been considered a useful tool for measuring the depth of anesthesia (DOA). However, because of its inability to detect the activities of the brain stem and spinal cord responsible for most of the vital signs, a new biomarker for measuring the multidimensional activities of the central nervous system under anesthesia is required. Detrended fluctuation analysis (DFA) is a new technique for detecting the scaling properties of nonstationary heart rate (HR) behavior. This study investigated the changes in fractal properties of heart rate variability (HRV), a nonlinear analysis, under intravenous propofol, inhalational desflurane, and spinal anesthesia. We compared the DFA method with traditional spectral analysis to evaluate its potential as an alternative biomarker under different levels of anesthesia. Eighty patients receiving elective procedures were randomly allocated different anesthesia. HRV was measured with spectral analysis and DFA short-term (4-11 beats) scaling exponent (DFAα1). An increase in DFAα1 followed by a decrease at higher concentrations during propofol or desflurane anesthesia is observed. Spinal anesthesia decreased the DFAα1 and low-/high-frequency ratio (LF/HF ratio). DFAα1 of HRV is a sensitive and specific method for distinguishing changes from baseline to anesthesia state. The DFAα1 provides a potential real-time biomarker to measure HRV as one of the multiple dimensions of the DOA.

Analyzing the Loss and the Recovery of Consciousness: Functional Connectivity Patterns and Changes in Heart Rate Variability During Propofol-Induced Anesthesia

The analysis of the central and the autonomic nervous systems (CNS, ANS) activities during general anesthesia (GA) provides fundamental information for the study of neural processes that support alterations of the consciousness level. In the present pilot study, we analyzed EEG signals and the heart rate (HR) variability (HRV) in a sample of 11 patients undergoing spinal surgery to investigate their CNS and ANS activities during GA obtained with propofol administration. Data were analyzed during different stages of GA: baseline, the first period of anesthetic induction, the period before the loss of consciousness, the first period after propofol discontinuation, and the period before the recovery of consciousness (ROC). In EEG spectral analysis, we found a decrease in posterior alpha and beta power in all cortical areas observed, except the occipital ones, and an increase in delta power, mainly during the induction phase. In EEG connectivity analysis, we found a significant increase of local efficiency index in alpha and delta bands between baseline and loss of consciousness as well as between baseline and ROC in delta band only and a significant reduction of the characteristic path length in alpha band between the baseline and ROC. Moreover, connectivity results showed that in the alpha band there was mainly a progressive increase in the number and in the strength of incoming connections in the frontal region, while in the beta band the parietal region showed mainly a significant increase in the number and in the strength of outcoming connections values. The HRV analysis showed that the induction of anesthesia with propofol was associated with a progressive decrease in complexity and a consequent increase in the regularity indexes and that the anesthetic procedure determined bradycardia which was accompanied by an increase in cardiac sympathetic modulation and a decrease in cardiac parasympathetic modulation during the induction. Overall, the results of this pilot study showed as propofol-induced anesthesia caused modifications on EEG signal, leading to a "rebalance" between long and short-range cortical connections, and had a direct effect on the cardiac system. Our data suggest interesting perspectives for the interactions between the central and autonomic nervous systems for the modulation of the consciousness level.

A Heartbeat Away From Consciousness: Heart Rate Variability Entropy Can Discriminate Disorders of Consciousness and Is Correlated With Resting-State fMRI Brain Connectivity of the Central Autonomic Network

Background: Disorders of consciousness are challenging to diagnose, with inconsistent behavioral responses, motor and cognitive disabilities, leading to approximately 40% misdiagnoses. Heart rate variability (HRV) reflects the complexity of the heart-brain two-way dynamic interactions. HRV entropy analysis quantifies the unpredictability and complexity of the heart rate beats intervals. We here investigate the complexity index (CI), a score of HRV complexity by aggregating the non-linear multi-scale entropies over a range of time scales, and its discriminative power in chronic patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS), and its relation to brain functional connectivity. Methods: We investigated the CI in short (CIs) and long (CIl) time scales in 14 UWS and 16 MCS sedated. CI for MCS and UWS groups were compared using a Mann-Whitney exact test. Spearman's correlation tests were conducted between the Coma Recovery Scale-revised (CRS-R) and both CI. Discriminative power of both CI was assessed with One-R machine learning model. Correlation between CI and brain connectivity (detected with functional magnetic resonance imagery using seed-based and hypothesis-free intrinsic connectivity) was investigated using a linear regression in a subgroup of 10 UWS and 11 MCS patients with sufficient image quality. Results: Higher CIs and CIl values were observed in MCS compared to UWS. Positive correlations were found between CRS-R and both CI. The One-R classifier selected CIl as the best discriminator between UWS and MCS with 90% accuracy, 7% false positive and 13% false negative rates after a 10-fold cross-validation test. Positive correlations were observed between both CI and the recovery of functional connectivity of brain areas belonging to the central autonomic networks (CAN). Conclusion: CI of MCS compared to UWS patients has high discriminative power and low false negative rate at one third of the estimated human assessors' misdiagnosis, providing an easy, inexpensive and non-invasive diagnostic tool. CI reflects functional connectivity changes in the CAN, suggesting that CI can provide an indirect way to screen and monitor connectivity changes in this neural system. Future studies should assess the extent of CI's predictive power in a larger cohort of patients and prognostic power in acute patients.

[Evaluation of heart rate variability for monitoring the depth of anaesthesia in dogs. Investigations based on total intravenous anaesthesia using propofol alone or in combination with dexmedetomidine or remifentanil]

OBJECTIVE

Evaluation of heart-rate variability (HRV) as an indicator for autonomous activity to monitor anaesthesia in dogs during three different total intravenous anaesthetic protocols and three anaesthetic depth levels as well as before and after electrical nociceptive stimulation.

MATERIAL AND METHODS

Seven beagle dogs (14.3±1.7 kg) were used in a randomised experimental trial with a complete cross-over design. Each dog went through all three anaesthetic protocols, which were propofol alone (group P) and propofol combined with dexmedetomidine (3 µg/kg/h, group PD) or remifentanil (18 µg/kg/h, group PR). Propofol was given using target-controlled infusion. Three anaesthetic depth levels (light, medium, deep) were defined by target concentrations for propofol in the blood and were adapted to the individual animal and treatment (mean of 7, 9 and 11 µg/ml, and in combination with dexmedetomidine or remifentanil, a mean of 3, 5 and 7 µg/ml). During each anaesthetic level, a standardised supramaximal nociceptive electric stimulus (50 Hz, 50 V, 10 ms) was applied medially to the right forearm. The bipolar-derived electrocardiogram (ECG) was recorded continuously. For each anaesthetic depth, the RR-intervals recorded 2 minutes before and after each stimulation were included in the statistical analysis. Using an HRV analytical program (Kubios HRV), the frequency domain HRV-parameters low (LF) and high (HF) frequency and the time-domain HRV-parameters RR-intervals, standard deviation of all RR-intervals (SDNN) and the square root of the mean of the sum of the squares of the differences between consecutive RR-intervals (RMSSD) were determined.

RESULTS

Neither the RR-intervals nor the currently available HRV-parameters which were derived from the RR-intervals were able to discriminate between the different anaesthetic depths levels. Nociception could only be represented by the RR-intervals.

CONCLUSION

Overall, the investigated standard HRV parameters offered no additional information for the monitoring of anaesthetic depths at the investigated, clinically used dose rates.

Effects of awareness and nociception on heart rate variability during general anaesthesia

During anaesthesia awareness and nociception are serious complications that may further lead to haemodynamic instability. Specific monitoring of depth of hypnosis and depth of analgesia based on heart rate variability (HRV) analysis is eligible to improve patient safety and reduce efforts in post-operative care. Consequently, in this analysis we assess the applicability of HRV parameters during surgical interventions with standardized intravenous propofol-remifentanil-anaesthesia. Peri-operative electrocardiograms were recorded from cardiovascular stable patients (ASA Score I/II, N = 32, age: 36.4 ± 11.23 a, BMI: 25.2 ± 3.16) scheduled for trauma and dentofacial surgery. HRV time- and frequency-domain parameters, measures of complexity and nonlinear dynamics were compared by analysing longitudinally distributed 300 s intervals preceding/following induction of anaesthesia (BL-I1), intubation (I1-I2) and extubation (E1-E2). Mean value (meanNN) and standard deviation (sdNN) of the heart rate are influenced in BL-I1 (p < 0.001), I1-I2 (p < 0.05) and E1-E2 (p < 0.001). The number of forbidden words of symbolic dynamics changes significantly for BL-I1 (p < 0.001) and not for I1-I2 and E1-E2 (p > 0.05). Probability of low-variability POLVAR10 is significantly altered in all comparisons (BL-I1: Δ = 0.032, p < 0.01, I1-I2: Δ = 0.12, p < 0.05, E1-E2: Δ = 0.169, p < 0.01) but especially during nociception. While standard time-domain parameters lacked selectivity, parameters of symbolic dynamics appear to be specifically influenced by changes in depth of hypnosis and nociception, respectively. However, the lack of steady-state ventilation/breathing in this study needs to be considered in future research. To be used for clinical anaesthesia monitoring our results have to be prospectively validated in clinical studies.