Novel insights on association and reactivity of Bispectral Index, frontal electromyogram, and autonomic responses in nociception-sedation monitoring of critical care patients.

Background: Assessing nociception and sedation in mechanically ventilated patients in the ICU is challenging, with few reliable methods available for continuous monitoring. Measurable cardiovascular and neurophysiological signals, such as frontal EEG, frontal EMG, heart rate, and blood pressure, have potential in sedation and nociception monitoring. The hypothesis of this explorative study is that derived variables from the aforementioned signals predict the level of sedation, as described by the Richmond Agitation-Sedation score (RASS), and respond to painful stimuli during critical care.

Responsiveness Index versus the RASS-Based Method for Adjusting Sedation in Critically Ill Patients.

Background: Sedation of intensive care patients is needed for patient safety, but deep sedation is associated with adverse outcomes. Frontal electromyogram-based Responsiveness Index (RI) aims to quantify the level of sedation and is scaled 0-100 (low index indicates deep sedation). We compared RI-based sedation to Richmond Agitation-Sedation Scale- (RASS-) based sedation.

Power Spectrum and Cross Power Spectral Density Based EEG Correlates of Intensive Care Delirium.

Full montage EEG recordings of 15 ICU patients (altogether 23 recordings) were analysed to find EEG correlates of delirium. CAM-ICU assessment results were used as the reference. Time period from 7 to 30 minutes at the beginning of the recordings was analysed in 10 sec segments with 5 sec overlap.

Quantitative EEG Parameters for Prediction of Outcome in Severe Traumatic Brain Injury: Development Study.

Monitoring of quantitative EEG (QEEG) parameters in the intensive care unit (ICU) can aid in the treatment of traumatic brain injury (TBI) patients by complementing visual EEG review done by an expert. We performed an explorative study investigating the prognostic value of 59 QEEG parameters in predicting the outcome of patients with severe TBI. Continuous EEG recordings were done on 28 patients with severe TBI in the ICU of Turku University Hospital.

Diagnostic accuracy between readers for identifying electrographic seizures in critically ill adults.

Objective: Electrographic seizures in critically ill patients are often equivocal. In this study, we sought to determine the diagnostic accuracy of electrographic seizure annotation in adult intensive care units (ICUs) and to identify affecting factors.

Methods: To investigate diagnostic accuracy, interreader agreement (IRA) measures were derived from 5,769 unequivocal and 6,263 equivocal seizure annotations by five experienced electroencephalogram (EEG) readers after reviewing 74 days of EEGs from 50 adult ICU patients.

Prediction of outcome in traumatic brain injury patients using long-term qEEG features.

Treatment of patients suffering from severe traumatic brain injury (TBI) commonly involves sedation and mechanical ventilation during prolonged stay in the intensive care unit. Continuous EEG is often monitored in these patients to detect epileptic seizures. It has also been suggested that EEG has prognostic value regarding the outcome of the treatment.

A randomized controlled proof-of-concept trial of early sedation management using Responsiveness Index monitoring in mechanically ventilated critically ill patients.

Introduction: Deep sedation is associated with adverse patient outcomes. We recently described a novel sedation-monitoring technology, the Responsiveness Index (RI), which quantifies patient arousal using processed frontal facial EMG data. We explored the potential effectiveness and safety of continuous RI monitoring during early intensive care unit (ICU) care as a nurse decision-support tool.

Algorithm for Quantifying Frontal EMG Responsiveness for Sedation Monitoring.

Introduction: To study stimulation-related facial electromyographic (FEMG) activity in intensive care unit (ICU) patients, develop an algorithm for quantifying the FEMG activity, and to optimize the algorithm for monitoring the sedation state of ICU patients.

Methods: First, the characteristics of FEMG response patterns related to vocal stimulation of 17 ICU patients were studied. Second, we collected continuous FEMG data from 30 ICU patients.

Frontal electroencephalogram variables are associated with the outcome and stage of hepatic encephalopathy in acute liver failure.

Acute liver failure (ALF) and hepatic encephalopathy (HE) can lead to an elevated intracranial pressure (ICP) and death within days. The impaired liver function increases the risks of invasive ICP monitoring, whereas noninvasive methods remain inadequate. The purpose of our study was to explore reliable noninvasive methods of neuromonitoring for patients with ALF in the intensive care unit (ICU) setting; more specifically, we wanted to track changes in HE and predict the outcomes of ALF patients treated with albumin dialysis.

An evaluation of the validity and potential utility of facial electromyelogram Responsiveness Index for sedation monitoring in critically ill patients.

Purpose: The purpose of this study is to explore the validity of a novel sedation monitoring technology based on facial electromyelography (EMG) in sedated critically ill patients.

Materials And Methods: The Responsiveness Index (RI) integrates the preceding 60 minutes of facial EMG data. An existing data set was used to derive traffic light cut-offs for low (red), intermediate (amber), and higher (green) states of patient arousal.

Application of subhairline EEG montage in intensive care unit: comparison with full montage.

Purpose: Problems with the availability of standard EEG monitoring in the intensive care unit have led to the use of recordings that have limited spatial coverage. We studied the performance of limited coverage EEG compared with more traditional full-montage EEG.

Methods: Continuous EEG recordings were performed on 170 patients using the full-montage 10-20 placement of electrodes as a reference recording and an abbreviated montage of electrodes applied below the hairline (subhairline).

Hypothermia-treated cardiac arrest patients with good neurological outcome differ early in quantitative variables of EEG suppression and epileptiform activity.

Objective: To evaluate electroencephalogram-derived quantitative variables after out-of-hospital cardiac arrest.

Design: Prospective study.

Setting: University hospital intensive care unit.

Bispectral index, entropy, and quantitative electroencephalogram during single-agent xenon anesthesia.

Background: The aim was to evaluate the performance of anesthesia depth monitors, Bispectral Index (BIS) and Entropy, during single-agent xenon anesthesia in 17 healthy subjects.

Methods: After mask induction with xenon and intubation, anesthesia was continued with xenon only. BIS, State Entropy and Response Entropy, and electroencephalogram were monitored throughout induction, steady-state anesthesia, and emergence.

Quantification of epileptiform electroencephalographic activity during sevoflurane mask induction.

Background: Sevoflurane may induce epileptiform electroencephalographic activity leading to unstable Bispectral Index numbers, underestimating the hypnotic depth of anesthesia. The authors developed a method for the quantification of epileptiform electroencephalographic activity during sevoflurane anesthesia.

Methods: Electroencephalographic data from 60 patients under sevoflurane mask induction were used in the analysis.

Prediction of poor outcome using detector of epileptiform EEG in ICU patients resuscitated after cardiac arrest.

Assessing the brain status of patients admitted to intensive care unit (ICU) after out-of-hospital cardiac arrest is challenging. We had earlier found wavelet subband entropy (WSE) to be a useful tool for quantifying the epileptiform content of EEG during anesthesia. In this paper, WSE was applied for EEG of ICU patients to study its prognostic value.

Method for the automatic detection of epileptiform waveforms in sevoflurane-induced anesthesia EEG.

Sevoflurane is a volatile anesthetic which is reported to cause epileptiform EEG changes together with undesired symptoms such as convulsions. In this paper, an algorithm for the automatic detection of these EEG changes is presented which could enable safer induction of anesthesia with sevoflurane by informing the clinicians about the epileptiform EEG. EEG was recorded from 60 healthy female patients during sevoflurane anesthesia.

An assessment of the validity of spectral entropy as a measure of sedation state in mechanically ventilated critically ill patients.

Objective: To assess whether the Entropy Module (GE Healthcare, Helsinki, Finland), a device to measure hypnosis in anesthesia, is a valid measure of sedation state in critically ill patients by comparing clinically assessed sedation state with Spectral Entropy

Design: Prospective observational study.

Setting: Teaching hospital general ICU.

Patients And Participants: 30 intubated, mechanically ventilated patients without primary neurological diagnoses or drug overdose receiving continuous sedation.

A rapid increase in the inspired concentration of desflurane is not associated with epileptiform encephalogram.

Unlabelled: The large inspired concentration of sevoflurane (S) during mask induction of anesthesia can induce epileptiform electroencephalogram (EEG) associated with tachycardia. Tachycardia is also seen when the concentration of desflurane (D) is abruptly increased. It is not known whether this is associated with epileptiform EEG similar to S.

Automatic analysis and monitoring of burst suppression in anesthesia.

Objective: We studied the spectral characteristics of the EEG burst suppression patterns (BSP) of two intravenous anesthetics, propofol and thiopental. Based on the obtained results, we developed a method for automatic segmentation, classification and compact presentation of burst suppression patterns.

Methods: The spectral analysis was performed with the short time Fourier transform and with autoregressive modeling to provide information of frequency contents of bursts.