Frontotemporal EEG to guide sedation in COVID-19 related acute respiratory distress syndrome

Neuromonitoring in the ICU - what, how and why?

PURPOSE OF REVIEW

We selectively review emerging noninvasive neuromonitoring techniques and the evidence that supports their use in the ICU setting. The focus is on neuromonitoring research in patients with acute brain injury.

RECENT FINDINGS

Noninvasive intracranial pressure evaluation with optic nerve sheath diameter measurements, transcranial Doppler waveform analysis, or skull mechanical extensometer waveform recordings have potential safety and resource-intensity advantages when compared to standard invasive monitors, however each of these techniques has limitations. Quantitative electroencephalography can be applied for detection of cerebral ischemia and states of covert consciousness. Near-infrared spectroscopy may be leveraged for cerebral oxygenation and autoregulation computation. Automated quantitative pupillometry and heart rate variability analysis have been shown to have diagnostic and/or prognostic significance in selected subtypes of acute brain injury. Finally, artificial intelligence is likely to transform interpretation and deployment of neuromonitoring paradigms individually and when integrated in multimodal paradigms.

SUMMARY

The ability to detect brain dysfunction and injury in critically ill patients is being enriched thanks to remarkable advances in neuromonitoring data acquisition and analysis. Studies are needed to validate the accuracy and reliability of these new approaches, and their feasibility and implementation within existing intensive care workflows.

Alternate Electrode Placements to Facilitate Frontal Electroencephalography Monitoring in Anesthetized and Critically Ill Patients

BACKGROUND

Frontal electroencephalography (EEG) monitoring can be useful in guiding the titration of anesthetics, but it is not always feasible to place electrodes in the standard configuration in some circumstances, including during neurosurgery. This study compares 5 alternate configurations of the Masimo Sedline Sensor.

METHODS

Ten stably sedated patients in the intensive care unit were recruited. Frontal EEG was monitored in the standard configuration (bifrontal upright) and 5 alternate configurations: bifrontal inverse, infraorbital, lateral upright, lateral inverse, and semilateral. Average power spectral densities (PSDs) with 95% CIs in the alternate configurations were compared to PSDs in the standard configuration. Two-one-sided-testing with Wilcoxon signed-rank tests assessed equivalence in the spectral edge frequency (SEF-95), EEG power, and relative delta (0.5 to 3.5 Hz), alpha (8 to 12 Hz), and beta (20 to 30 Hz) power between each alternate and standard configurations.

RESULTS

After the removal of unanalyzable tracings, 7 patients were included for analysis in the infraorbital configuration and 9 in all other configurations. In the lateral upright and lateral inverse configurations, PSDs significantly differed from the standard configuration within the 15 to 20 Hz band. The greatest decrease in EEG power was in the lateral inverse configuration (median: -97 dB; IQR: -130, -62 dB). The largest change in frequency distribution of EEG power was in the infraorbital configuration; median SEF-95 change of -1.4 Hz (IQR: -2.8, 0.7 Hz), median relative delta power change of +7.3% (IQR: 1.4%, 7.9%), and median relative alpha power change of -0.6% (IQR: -5.7%, 0.0%).

CONCLUSIONS

These 5 alternate Sedline electrode configurations are suitable options for monitoring frontal EEG when the standard configuration is not possible.

Neurological complications of critically ill COVID-19 patients

PURPOSE OF REVIEW

COVID-19 and systemic critical illness are both associated with neurological complications. We provide an update on the diagnosis and critical care management of adult patients with neurological complications of COVID-19.

RECENT FINDINGS

Large prospective multicentre studies conducted in the adult population over the last 18 months improved current knowledge on severe neurological complications of COVID-19. In COVID-19 patients presenting with neurological symptoms, a multimodal diagnostic workup (including CSF analysis, brain MRI, and EEG) may identify different syndromes associated with distinct trajectories and outcomes. Acute encephalopathy, which represents the most common neurological presentation of COVID-19, is associated with hypoxemia, toxic/metabolic derangements, and systemic inflammation. Other less frequent complications include cerebrovascular events, acute inflammatory syndromes, and seizures, which may be linked to more complex pathophysiological processes. Neuroimaging findings include infarction, haemorrhagic stroke, encephalitis, microhaemorrhages and leukoencephalopathy. In the absence of structural brain injury, prolonged unconsciousness is usually fully reversible, warranting a cautious approach for prognostication. Advanced quantitative MRI may provide useful insights into the extent and pathophysiology of the consequences of COVID-19 infection including atrophy and functional imaging changes in the chronic phase.

SUMMARY

Our review highlights the importance of a multimodal approach for the accurate diagnosis and management of complications of COVID-19, both at the acute phase and in the long-term.

Electroencephalography spectral edge frequency and suppression rate-guided sedation in patients with COVID-19: A randomized controlled trial

Background

Sedation in coronavirus disease 2019 (COVID-19) patients has been identified as a major challenge. We aimed to investigate whether the use of a multiparameter electroencephalogram (EEG) protocol to guide sedation in COVID-19 patients would increase the 30-day mechanical ventilation-free days (VFD).

Methods

We conducted a double-blind randomized clinical trial. We included patients with severe pneumonia due to COVID-19 who required mechanical ventilation (MV) and deep sedation. We randomized to the control (n = 25) or multiparameter group (n = 25). Sedation in the intervention group was administered following the standard institutional protocols together with a flow chart designed to reduce the propofol administration dose if the EEG suppression rate was over 2% or the spectral edge frequency 95 (SEF95) was below 10 Hz. We performed an intention-to-treat analysis to evaluate our primary outcome (30-day VFD).

Results

There was no difference in VFD at day 30 (median: 11 [IQR 0–20] days in the control group vs. 0 [IQR 0–21] days in the BIS multiparameter group, p = 0.87). Among secondary outcomes, we documented a 17% reduction in the total adjusted propofol administered during the first 5 days of the protocol [median: 2.3 (IQR 1.9–2.8) mg/k/h in the control group vs. 1.9(IQR 1.5–2.2) mg/k/h in the MP group, p = 0.005]. This was accompanied by a higher average BIS value in the intervention group throughout the treatment period.

Conclusion

A sedation protocol guided by multivariate EEG-derived parameters did not increase the 30-day VFD. However, the intervention led to a reduction in total propofol administration.

Electroencephalogram-Based Evaluation of Impaired Sedation in Patients with Moderate to Severe COVID-19 ARDS

The sedation management of patients with severe COVID-19 is challenging. Processed electroencephalography (pEEG) has already been used for sedation management before COVID-19 in critical care, but its applicability in COVID-19 has not yet been investigated. We performed this prospective observational study to evaluate whether the patient sedation index (PSI) obtained via pEEG may adequately reflect sedation in ventilated COVID-19 patients. Statistical analysis was performed by linear regression analysis with mixed effects. We included data from 49 consecutive patients. None of the patients received neuromuscular blocking agents by the time of the measurement. The mean value of the PSI was 20 (±23). The suppression rate was determined to be 14% (±24%). A deep sedation equivalent to the Richmond Agitation and Sedation Scale of −3 to −4 (correlation expected PSI 25−50) in bedside examination was noted in 79.4% of the recordings. Linear regression analysis revealed a significant correlation between the sedative dosages of propofol, midazolam, clonidine, and sufentanil (p < 0.01) and the sedation index. Our results showed a distinct discrepancy between the RASS and the determined PSI. However, it remains unclear to what extent any discrepancy is due to the electrophysiological effects of neuroinflammation in terms of pEEG alteration, to the misinterpretation of spinal or vegetative reflexes during bedside evaluation, or to other causes.

Monitoring of sedation in mechanically ventilated patients using remote technology

PURPOSE OF REVIEW

Two years of coronavirus disease 2019 (COVID-19) pandemic highlighted that excessive sedation in the ICU leading to coma and other adverse outcomes remains pervasive. There is a need to improve monitoring and management of sedation in mechanically ventilated patients. Remote technologies that are based on automated analysis of electroencephalogram (EEG) could enhance standard care and alert clinicians real-time when severe EEG suppression or other abnormal brain states are detected.

RECENT FINDINGS

High rates of drug-induced coma as well as delirium were found in several large cohorts of mechanically ventilated patients with COVID-19 pneumonia. In patients with acute respiratory distress syndrome, high doses of sedatives comparable to general anesthesia have been commonly administered without defined EEG endpoints. Continuous limited-channel EEG can reveal pathologic brain states such as burst suppression, that cannot be diagnosed by neurological examination alone. Recent studies documented that machine learning-based analysis of continuous EEG signal is feasible and that this approach can identify burst suppression as well as delirium with high specificity.

SUMMARY

Preventing oversedation in the ICU remains a challenge. Continuous monitoring of EEG activity, automated EEG analysis, and generation of alerts to clinicians may reduce drug-induced coma and potentially improve patient outcomes.

Rapid Response EEG: Current State and Future Directions

PURPOSE OF REVIEW

To critically appraise the literature on the application, methods, and advances in emergency electroencephalography (EEG).

RECENT FINDINGS

The development of rapid EEG (rEEG) technologies and other reduced montage approaches, along with advances in machine learning over the past decade, has increased the rate and access to EEG acquisition. These achievements have made EEG in the emergency setting a practical diagnostic technique for detecting seizures, suspected nonconvulsive status epilepticus (NCSE), altered mental status, stroke, and in the setting of sedation. Growing evidence supports using EEG to expedite medical decision-making in the setting of suspected acute neurological injury. This review covers approaches to acquiring EEG in the emergency setting in the adult and pediatric populations. We also cover the clinical impact of this data, the time associated with emergency EEG, and the costs of acquiring EEG in these settings. Finally, we discuss the advances in artificial intelligence for rapid electrophysiological interpretation.