Instantaneous 3D EEG Signal Analysis Based on Empirical Mode Decomposition and the Hilbert–Huang Transform Applied to Depth of Anaesthesia

Depth of anaesthesia (DoA) is an important measure for assessing the degree to which the central nervous system of a patient is depressed by a general anaesthetic agent, depending on the potency and concentration with which anaesthesia is administered during surgery. We can monitor the DoA by observing the patient’s electroencephalography (EEG) signals during the surgical procedure. Typically high frequency EEG signals indicates the patient is conscious, while low frequency signals mean the patient is in a general anaesthetic state. If the anaesthetist is able to observe the instantaneous frequency changes of the patient’s EEG signals during surgery this can help to better regulate and monitor DoA, reducing surgical and post-operative risks. This paper describes an approach towards the development of a 3D real-time visualization application which can show the instantaneous frequency and instantaneous amplitude of EEG simultaneously by using empirical mode decomposition (EMD) and the Hilbert–Huang transform (HHT). HHT uses the EMD method to decompose a signal into so-called intrinsic mode functions (IMFs). The Hilbert spectral analysis method is then used to obtain instantaneous frequency data. The HHT provides a new method of analyzing non-stationary and nonlinear time series data. We investigate this approach by analyzing EEG data collected from patients undergoing surgical procedures. The results show that the EEG differences between three distinct surgical stages computed by using sample entropy (SampEn) are consistent with the expected differences between these stages based on the bispectral index (BIS), which has been shown to be quantifiable measure of the effect of anaesthetics on the central nervous system. Also, the proposed filtering approach is more effective compared to the standard filtering method in filtering out signal noise resulting in more consistent results than those provided by the BIS. The proposed approach is therefore able to distinguish between key operational stages related to DoA, which is consistent with the clinical observations. SampEn can also be viewed as a useful index for evaluating and monitoring the DoA of a patient when used in combination with this approach

Local infusion of bupivacaine combined with intravenous patient-controlled analgesia provides better pain relief than intravenous patient-controlled analgesia alone in patients undergoing minimally invasive cardiac surgery

ObjectiveThis prospective randomized double-blind study examined the effect of local wound infusion of anesthetics on pain control in the thoracotomy wound of patients undergoing minimally invasive cardiac surgery.MethodsPatients who underwent coronary artery bypass grafting or cardiac valvular procedures via a minimally invasive thoracotomy were studied. Patients were enrolled and randomly allocated to two groups with different modalities of postoperative analgesia. The thoracotomy wound infusion group received 0.15% bupivacaine infused continuously at 2 mL/h through a catheter embedded in the wound, as well as intravenous patient-controlled analgesia. The control group had patient-controlled analgesia alone with a sham thoracotomy wound infusion of normal saline. Verbal analog pain scores (0–10 points) and recovery profiles were investigated.ResultsThere were 19 patients in each group for complete data analysis. On the first day after the operation, infusion of local anesthetics significantly reduced the verbal analog pain scores both at rest and during motion (thoracotomy wound infusion vs control). The improved pain relief with thoracotomy wound infusion persisted at day 3 and even at 3 months after the operation. No difference was noted about time to extubation, length of intensive care unit stay, or hospital stay.ConclusionIn this controlled double-blind study, thoracotomy wound infusion and patient-controlled analgesia were superior to patient-controlled analgesia alone in reducing pain at 1, 3, and 90 days after minimally invasive cardiac surgery

Tranexamic acid for intracerebral haemorrhage within 2 hours of onset : protocol of a phase II randomised placebo-controlled double-blind multicentre trial

Rationale Haematoma growth is common early after intracerebral haemorrhage (ICH), and is a key determinant of outcome. Tranexamic acid, a widely available antifibrinolytic agent with an excellent safety profile, may reduce haematoma growth. Methods and design Stopping intracerebral haemorrhage with tranexamic acid for hyperacute onset presentation including mobile stroke units (STOP-MSU) is a phase II double-blind, randomised, placebo-controlled, multicentre, international investigator-led clinical trial, conducted within the estimand statistical framework. Hypothesis In patients with spontaneous ICH, treatment with tranexamic acid within 2 hours of onset will reduce haematoma expansion compared with placebo. Sample size estimates A sample size of 180 patients (90 in each arm) would be required to detect an absolute difference in the primary outcome of 20% (placebo 39% vs treatment 19%) under a two-tailed significance level of 0.05. An adaptive sample size re-estimation based on the outcomes of 144 patients will allow a possible increase to a prespecified maximum of 326 patients. Intervention Participants will receive 1 g intravenous tranexamic acid over 10 min, followed by 1 g intravenous tranexamic acid over 8 hours; or matching placebo. Primary efficacy measure The primary efficacy measure is the proportion of patients with haematoma growth by 24 +/- 6 hours, defined as either >= 33% relative increase or >= 6 mL absolute increase in haematoma volume between baseline and follow-up CT scan. Discussion We describe the rationale and protocol of STOP-MSU, a phase II trial of tranexamic acid in patients with ICH within 2 hours from onset, based in participating mobile stroke units and emergency departments.Peer reviewe

Outcome of intracerebral hemorrhage associated with different oral anticoagulants

Objective: In an international collaborative multicenter pooled analysis, we compared mortality, functional outcome, intracerebral hemorrhage (ICH) volume, and hematoma expansion (HE) between non-vitamin K antagonist oral anticoagulation-related ICH (NOAC-ICH) and vitamin K antagonist-associated ICH (VKA-ICH). Methods: We compared all-cause mortality within 90 days for NOAC-ICH and VKA-ICH using a Cox proportional hazards model adjusted for age; sex; baseline Glasgow Coma Scale score, ICH location, and log volume; intraventricular hemorrhage volume; and intracranial surgery. We addressed heterogeneity using a shared frailty term. Good functional outcome was defined as discharge modified Rankin Scale score 33% or >6 mL from baseline within 72 hours. Results: We included 500 patients (97 NOAC-ICH and 403 VKA-ICH). Median baseline ICH volume was 14.4 mL (interquartile range [IQR] 3.6-38.4) for NOAC-ICH vs 10.6 mL (IQR 4.0-27.9) for VKA-ICH (p = 0.78). We did not find any difference between NOAC-ICH and VKA-ICH for all-cause mortality within 90 days (33% for NOAC-ICH vs 31% for VKA-ICH [p = 0.64]; adjusted Cox hazard ratio (for NOAC-ICH vs VKA-ICH) 0.93 [95% confidence interval (CI) 0.52-1.64] [p = 0.79]), the rate of HE (NOAC-ICH n = 29/48 [40%] vs VKA-ICH n = 93/140 [34%] [p = 0.45]), or functional outcome at hospital discharge (NOAC-ICH vs VKA-ICH odds ratio 0.47; 95% CI 0.18-1.19 [p = 0.11]). Conclusions: In our international collaborative multicenter pooled analysis, baseline ICH volume, hematoma expansion, 90-day mortality, and functional outcome were similar following NOAC-ICH and VKA-ICH.Peer reviewe

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.This research was financially supported by the Center for Dynamical Biomarkers and Translational Medicine, National Central University, Taiwan, which is sponsored by Ministry of Science and Technology (Grant Number: NSC102-2911-I-008-001). Also, it was supported by Chung-Shan Institute of Science and Technology in Taiwan (Grant Numbers: CSIST-095-V301 and CSIST-095-V302) and National Natural Science Foundation of China (Grant Number: 51475342)

Neuroimaging and clinical outcomes of oral anticoagulant-associated intracerebral hemorrhage

Objective Methods Whether intracerebral hemorrhage (ICH) associated with non-vitamin K antagonist oral anticoagulants (NOAC-ICH) has a better outcome compared to ICH associated with vitamin K antagonists (VKA-ICH) is uncertain. We performed a systematic review and individual patient data meta-analysis of cohort studies comparing clinical and radiological outcomes between NOAC-ICH and VKA-ICH patients. The primary outcome measure was 30-day all-cause mortality. All outcomes were assessed in multivariate regression analyses adjusted for age, sex, ICH location, and intraventricular hemorrhage extension. Results Interpretation We included 7 eligible studies comprising 219 NOAC-ICH and 831 VKA-ICH patients (mean age = 77 years, 52.5% females). The 30-day mortality was similar between NOAC-ICH and VKA-ICH (24.3% vs 26.5%; hazard ratio = 0.94, 95% confidence interval [CI] = 0.67-1.31). However, in multivariate analyses adjusting for potential confounders, NOAC-ICH was associated with lower admission National Institutes of Health Stroke Scale (NIHSS) score (linear regression coefficient = -2.83, 95% CI = -5.28 to -0.38), lower likelihood of severe stroke (NIHSS > 10 points) on admission (odds ratio [OR] = 0.50, 95% CI = 0.30-0.84), and smaller baseline hematoma volume (linear regression coefficient = -0.24, 95% CI = -0.47 to -0.16). The two groups did not differ in the likelihood of baseline hematoma volume <30cm(3) (OR = 1.14, 95% CI = 0.81-1.62), hematoma expansion (OR = 0.97, 95% CI = 0.63-1.48), in-hospital mortality (OR = 0.73, 95% CI = 0.49-1.11), functional status at discharge (common OR = 0.78, 95% CI = 0.57-1.07), or functional status at 3 months (common OR = 1.03, 95% CI = 0.75-1.43). Although functional outcome at discharge, 1 month, or 3 months was comparable after NOAC-ICH and VKA-ICH, patients with NOAC-ICH had smaller baseline hematoma volumes and less severe acute stroke syndromes. Ann Neurol 2018;84:702-712Peer reviewe

Effect of mannitol on cerebrovascular pressure reactivity in patients with intracranial hypertension

Background/PurposeMannitol is commonly used in patients with increased intracranial pressure (ICP), but its effect on cerebrovascular pressure reactivity (CVPR) is uncertain. We analyzed the changes of pressure reactivity index (PRx) during the course of mannitol treatment.MethodsTwenty-one patients who received mannitol treatment for increased ICP were recruited prospectively. Continuous waveforms of arterial blood pressure (ABP) and ICP were collected simultaneously for 60 minutes (10 minutes at baseline and 50 minutes since mannitol administration) during 37 events of mannitol treatment. The correlation coefficients between the mean ABP and ICP were averaged every 10 minutes and labeled as the PRx. The linear correlation of six time points of PRx in each event was calculated to represent the trend of CVPR changes. The negative slope of correlation was defined as improvement in CVPR under mannitol treatment and vice versa.ResultsAt baseline, the average of ICP was 26.0 ± 9.1 mmHg and the values of PRx were significantly correlated with ICP (p = 0.0044, r = 0.46). After mannitol administration, the average of ICP decreased significantly to 21.2 ± 11.1 mmHg (p = 0.036), and CVPR improved in 59.4 % of all events. Further analysis showed that low baseline cerebral perfusion pressure was the only hemodynamic parameter significant association with the improvement of CVPR after mannitol treatment (p = 0.039).ConclusionDespite lowering ICP, mannitol may have diverse effects on CVPR in patients with intracranial hypertension. Our study suggests that mannitol infusion may have a beneficial effect on CVPR, particularly in those with a low cerebral perfusion pressure at baseline

Application of Multivariate Empirical Mode Decomposition and Sample Entropy in EEG Signals via Artificial Neural Networks for Interpreting Depth of Anesthesia

EEG (Electroencephalography) signals can express the human awareness activities and consequently it can indicate the depth of anesthesia. On the other hand, Bispectral-index (BIS) is often used as an indicator to assess the depth of anesthesia. This study is aimed at using an advanced signal processing method to analyze EEG signals and compare them with existing BIS indexes from a commercial product (i.e., IntelliVue MP60 BIS module). Multivariate empirical mode decomposition (MEMD) algorithm is utilized to filter the EEG signals. A combination of two MEMD components (IMF2 + IMF3) is used to express the raw EEG. Then, sample entropy algorithm is used to calculate the complexity of the patients’ EEG signal. Furthermore, linear regression and artificial neural network (ANN) methods were used to model the sample entropy using BIS index as the gold standard. ANN can produce better target value than linear regression. The correlation coefficient is 0.790 ± 0.069 and MAE is 8.448 ± 1.887. In conclusion, the area under the receiver operating characteristic (ROC) curve (AUC) of sample entropy value using ANN and MEMD is 0.969 ± 0.028 while the AUC of sample entropy value without filter is 0.733 ± 0.123. It means the MEMD method can filter out noise of the brain waves, so that the sample entropy of EEG can be closely related to the depth of anesthesia. Therefore, the resulting index can be adopted as the reference for the physician, in order to reduce the risk of surgery