Time delay of the qCON monitor and its performance during state transitions

Substance-dependent EEG during recovery from anesthesia and optimization of monitoring

The electroencephalographic (EEG) activity during anesthesia emergence contains information about the risk for a patient to experience postoperative delirium, but the EEG dynamics during emergence challenge monitoring approaches. Substance-specific emergence characteristics may additionally limit the reliability of commonly used processed EEG indices during emergence. This study aims to analyze the dynamics of different EEG indices during anesthesia emergence that was maintained with different anesthetic regimens. We used the EEG of 45 patients under general anesthesia from the emergence period. Fifteen patients per group received sevoflurane, isoflurane (+ sufentanil) or propofol (+ remifentanil) anesthesia. One channel EEG and the bispectral index (BIS A-1000) were recorded during the study. We replayed the EEG back to the Conox, Entropy Module, and the BIS Vista to evaluate and compare the index behavior. The volatile anesthetics induced significantly higher EEG frequencies, causing higher indices (AUC > 0.7) over most parts of emergence compared to propofol. The median duration of "awake" indices (i.e., > 80) before the return of responsiveness (RoR) was significantly longer for the volatile anesthetics (p < 0.001). The different indices correlated well under volatile anesthesia (rs > 0.6), with SE having the weakest correlation. For propofol, the correlation was lower (rs < 0.6). SE was significantly higher than BIS and, under propofol anesthesia, qCON. Systematic differences of EEG-based indices depend on the drugs and devices used. Thus, to avoid early awareness or anesthesia overdose using an EEG-based index during emergence, the anesthetic regimen, the monitor used, and the raw EEG trace should be considered for interpretation before making clinical decisions.

Assessment of seizure duration and utility of using SedLine® EEG tracing in veterans undergoing electroconvulsive therapy: a retrospective analysis

BACKGROUND

Electroconvulsive therapy (ECT) endures as a definitive treatment for refractory depression and catatonia and is also considered an effective treatment for a number of other severe psychiatric disorders (Lisanby, N Engl J Med 357:1939-1945, 2007)(Weiner and Prudic, Biol Psychiatry 73:105-106, 2013). GA is an essential component of the ECT procedure for various reasons (Lee, Jenkins and Sparkle, Life 11, 2021). Monitoring anesthetic effects on the brain is desirable as anesthetic agents affect seizure duration and recovery (Rasulo, Hopkins, Lobo, et al,  Neurocrit Care 38:296-311, 2023) (Jones , Nittur , Fleming and Applegate,  BMC Anesthesiol 21:105, 2021) (Soehle , Kayser , Ellerkmann and Schlaepfer,  BJA 112:695-702, 2013). Perioperative anesthetic effects on consciousness can be assessed with brain function monitoring using raw electroencephalogram (EEG) traces and processed EEG indices.

OBJECTIVE

We examined the usefulness and utility of the SedLine® anesthetic effect monitor during ECT procedures. We hypothesized that the seizure duration as measured by the EEG tracing of the ECT machine is equivalent to the duration assessed by the SedLine® EEG tracing. A secondary objective was to describe the SedLine® patient state indices (PSI) at different phases of treatment.

METHODS

Following IRB approval, we analyzed the data of the electronic medical records of 45 ECT treatments of 23 patients in an urban VA medical center between July 01, 2021, and March 30, 2022. We compared the seizure duration in minutes and seconds as measured either by the ECT machine EEG tracing or the SedLine® EEG tracing. We then collected SedLine® processed EEG indices at four different stages during the treatment. Appropriate comparative and observational statistical analyses were applied.

RESULTS

There was no significant difference in measured seizure duration between the two methods examined (p < 0.05). We observed a lag of the SedLine PSI value at the time before stimulus delivery and limited PSI utility during the course of ECT.

CONCLUSION

The SedLine® EEG tracing can be an alternative to the machine EEG tracing for the determination of seizure duration. The SedLine® processed EEG indices are not consistently useful before and after ECT delivery. Anesthetic effect monitoring during ECT is feasible.

Separation of responsive and unresponsive patients under clinical conditions: comparison of symbolic transfer entropy and permutation entropy

Electroencephalogram (EEG)-based monitoring during general anesthesia may help prevent harmful effects of high or low doses of general anesthetics. There is currently no convincing evidence in this regard for the proprietary algorithms of commercially available monitors. The purpose of this study was to investigate whether a more mechanism-based parameter of EEG analysis (symbolic transfer entropy, STE) can separate responsive from unresponsive patients better than a strictly probabilistic parameter (permutation entropy, PE) under clinical conditions. In this prospective single-center study, the EEG of 60 surgical ASA I-III patients was recorded perioperatively. During induction of and emergence from anesthesia, patients were asked to squeeze the investigators' hand every 15s. Time of loss of responsiveness (LoR) during induction and return of responsiveness (RoR) during emergence from anesthesia were registered. PE and STE were calculated at -15s and +30s of LoR and RoR and their ability to separate responsive from unresponsive patients was evaluated using accuracy statistics. 56 patients were included in the final analysis. STE and PE values decreased during anesthesia induction and increased during emergence. Intra-individual consistency was higher during induction than during emergence. Accuracy values during LoR and RoR were 0.71 (0.62-0.79) and 0.60 (0.51-0.69), respectively for STE and 0.74 (0.66-0.82) and 0.62 (0.53-0.71), respectively for PE. For the combination of LoR and RoR, values were 0.65 (0.59-0.71) for STE and 0.68 (0.62-0.74) for PE. The ability to differentiate between the clinical status of (un)responsiveness did not significantly differ between STE and PE at any time. Mechanism-based EEG analysis did not improve differentiation of responsive from unresponsive patients compared to the probabilistic PE.Trial registration: German Clinical Trials Register ID: DRKS00030562, November 4, 2022, retrospectively registered.

Performance of the SEDLine Monitor: Age Dependency and Time Delay

BACKGROUND

Devices monitoring the hypnotic component of general anesthesia can help to guide anesthetic management. The main purposes of these devices are the titration of anesthesia dose. While anesthesia at low doses can result in awareness with intraoperative memory formation, excessive administration of anesthetics may be associated with an increased risk of postoperative neurocognitive disorder. We have previously shown for various indices that they are significantly influenced by the patient's age and that the monitors have a significant time delay. Here, we evaluated the influence of patient's age and time delay on the patient state index (PSI) of the SEDLine monitor.

METHODS

To analyze the influence of the patient's age, we replayed 2 minutes of electroencephalography (EEG) of 141 patients (19-88 years, ASA I-IV) undergoing general anesthesia maintained with desflurane, sevoflurane, or propofol to the SEDLine monitor. We extracted the PSI as well as the spectral edge frequency (SEF) and performed a linear regression analysis. For evaluation of the time delay, we replayed 5 minutes of EEG of stable episodes of adequate anesthesia (PSI between 25 and 50) or light sedation/wake (PSI >70) in different orders to the SEDLine to simulate sudden changes between the states. Time delays were defined as the required time span of the monitor to reach the stable target index.

RESULTS

PSI and SEF increased significantly with the patient's age. These findings did not depend on the administered anesthetic. The evaluation of the correlation between SEF and PSI showed a strong correlation with Spearman's correlation coefficient of ρ = 0.86 (0.82; 0.89). The time delays depended on the type of transition. We found a median time delay of 54 (Min: 46; Max: 61) seconds for the important transition between adequate anesthesia and awake and 55 (Min: 50; Max: 67) seconds in the other direction.

CONCLUSIONS

With our analyses, we show that the indices presented on the SEDLine display, the PSI and the SEF, increase with age for patients under general anesthesia. Additionally, a delay of the PSI to react to sudden neurophysiologic changes due to dose of the maintenance anesthetic is of a time course that is clinically significant. These factors should be considered when navigating anesthesia relying on only the proprietary index for the SEDLine monitor.

[Processed EEG for personalized dosing of anesthetics during general anesthesia]

Electroencephalogram (EEG)-guided anesthesia is indispensable in modern operating rooms and has become established as the standard form of monitoring. Many anesthesiologists rely on processed EEG indices in the hope of averting anesthesia-related complications, such as intraoperative awareness, postoperative delirium and other cognitive complications in their patients. This educational review aims to provide information on the five most prevalent monitors used to guide depth of sedation during general anesthesia. This article elucidates the principles underpinning the application of these monitors where known, which are generally based on power in various EEG frequency bands and on the burst suppression pattern. Convinced that EEG-guided anesthesia has the potential of benefitting many surgical patients, it is felt that many basic principles and shortcomings of processed EEG indices need to be better understood in the clinical practice. After discussing the different monitors and clinically relevant data from the literature, the article gives a short practical guidance on how to critically interpret processed EEG information and troubleshooting of confounded indices in the context of clinical situations.

OPIOID FREE GENERAL ANESTHESIA IN CLINICAL PRACTICE - A REVIEW ARTICLE

Currently, enhanced recovery after surgery (ERAS) protocols are multimodal perioperative care pathways with the goal to achieve early patient recovery after surgery with minimal postoperative complications. According to studies, opioid free general anesthesia has many perioperative benefits and should be part of the ERAS protocols in specific surgical and patient indications. Opioid free general anesthesia is a multimodal balanced technique that is based on the concept that opioids are not used preoperatively or intraoperatively until the patient has aroused. The basic concept of opioid free general anesthesia is intravenous administration of several nonopioid drugs that operate at different pharmacological sites blocking surgical stress and sympathetic activation response. Moreover, current studies have shown that opioid free anesthesia is a technique which satisfactorily controls postoperative pain as the fifth vital sign, and has minimal side effects and better patient recovery with the same surgical conditions as general multimodal balanced anesthesia. However, further research is needed.

Comparison of Quantium Consciousness Index and Richmond Agitation Sedation Scale in Mechanically Ventilated Critically Ill Patients: An Observational Study

Background

The quantium consciousness index (qCON), an electroencephalography (EEG)-based modality, has no studies regarding intensive care unit (ICU) sedation, though very few studies describe its use for assessing depth of anesthesia in the operation theater. In this study, we evaluated qCON for assessing sedation compared with Richmond Agitation Sedation Scale (RASS) in patients on a mechanical ventilator in the ICU.

Materials and methods

Eighty-seven mechanically ventilated patients aged between 18 and 60 years were investigated over a 12-hour period. They were given a standardized dosage of sedation comprised of a bolus dose of propofol 0.5 mg/kg and fentanyl 1 µg/kg, and then infusions of propofol 2–5 mg/kg/hour and fentanyl 0.5–2 µg/kg/hour. These drug infusions were adjusted to achieve a RASS score between 0 and −3. Using the qCON monitor, the investigator recorded the qCON values and then assessed the RASS score.

Results

A total of 1,218 readings were obtained. After contrasting each qCON value correspondingly with time to each RASS value, we found their correlation to be statistically significant (ρ = 0.288, p <0.0001). With the help of receiver operating characteristic (ROC) curves, we were able to differentiate appropriate from inappropriate levels of sedation. A qCON value of 80 had a sensitivity of 72.67% and a specificity of 67.42% (AUC 0.738 with SE 0.021).

Conclusion

qCON can be used for assessing sedation levels in mechanically ventilated critically ill patients.

Clinical trial registration

CTRI/2019/07/020064.

How to cite this article

Harsha MS, Bhatia PK, Sharma A, Sethi P. Comparison of Quantium Consciousness Index and Richmond Agitation Sedation Scale in Mechanically Ventilated Critically Ill Patients: An Observational Study. Indian J Crit Care Med 2022;26(4):491–495.

The influence of age on EEG-based anaesthesia indices

STUDY OBJECTIVE

In the upcoming years there will be a growing number of elderly patients requiring general anaesthesia. As age is an independent risk factor for postoperative delirium (POD) the incidence of POD will increase concordantly. One approach to reduce the risk of POD would be to avoid excessively high doses of anaesthetics by using neuromonitoring to guide anaesthesia titration. Therefore, we evaluated the influence of patient's age on various electroencephalogram (EEG)-based anaesthesia indices.

DESIGN AND PATIENTS

We conducted an analysis of previously published data by replaying single electrode EEG episodes of maintenance of general anaesthesia from 180 patients (18-90 years; ASA I-IV) into the five different commercially available monitoring systems and evaluated their indices. We included the State/Response Entropy, Narcotrend, qCON/qNOX, bispectral index (BIS), and Treaton MGA-06. For a non-commercial comparison, we extracted the spectral edge frequency (SEF) from the BIS. To evaluate the influence of the age we generated linear regression models. We also assessed the correlation between the various indices.

MAIN RESULTS

During anaesthetic maintenance the values of the SEF, State/Response Entropy, qCON/qNOX and BIS all significantly increased (0.05 Hz/0.19-0.26 index points per year) with the patient's age (p < 0.001); whereas the Narcotrend did not change significantly with age (0.06 index points per year; p = 0.28). The index values of the Treaton device significantly decreased with age (-0.09 index points per year; p < 0.001). These findings were independent of the administered dose of anaesthetics.

CONCLUSIONS

Almost all current neuromonitoring devices are influenced by age, with the potential to result in inappropriately high dosage of anaesthetics. Therefore, anaesthesiologists should be aware of this phenomenon, and the next generation of monitors should correct for these changes.