The validation of simplified EEG derived from the bispectral index monitor in post-cardiac arrest patients

EEG in a four-electrode frontotemporal montage reliably predicts outcome after cardiac arrest

AIM

To increase efficiency of continuous EEG monitoring for prognostication of neurological outcome in patients after cardiac arrest, we investigated the reliability of EEG in a four-electrode frontotemporal (4-FT) montage, compared to our standard nine-electrode (9-EL) montage.

METHODS

EEG recorded with Ag/AgCl cup-electrodes at 12 and/or 24h after cardiac arrest of 153 patients was available from a previous study. 220 EEG epochs of 5 minutes were reexamined in a 4-FT montage according to the ACNS criteria. Background classification was compared to the available 9-EL classification using Cohens kappa. Reliability for prognostication was assessed in 151 EEG epochs at 24h after CA using sensitivity and specificity for prediction of poor (cerebral performance categories (CPC) 3-5) and good (CPC 1-2) neurological outcome.

RESULTS

Agreement for EEG background classification between the two montages was substantial with a kappa of 0.85 (95%-CI 0.81-0.90). Specificity for prediction of poor outcome was 100% (95%-CI 95-100) for both montages, sensitivity was 31% (95%-CI 21-43) for the 4-FT montage and 35% (95%-CI 24-47) for the 9-EL montage. Good outcome was predicted with 65% specificity (95%-CI 53-76) and 81% sensitivity (95%-CI 71-89) for the 4-FT montage, similar to the 9-EL montage.

CONCLUSION

In this cohort, EEG background patterns determined in a four-electrode frontotemporal montage predict both poor and good outcome after CA with similar reliability. Our results may contribute to decreasing the workload of EEG monitoring in patients after CA without compromising reliability of outcome prediction. However, validation in a larger cohort is necessary, as is a multimodal approach.

Bispectral index and suppression ratio after cardiac arrest: are they useful as bedside tools for rational treatment escalation plans?

INTRODUCTION AND OBJECTIVES

Myocardial dysfunction contributes to early mortality (24-72 hours) among survivors of a cardiac arrest (CA). The benefits of mechanical support in refractory shock should be balanced against the patient's potential for neurological recovery. To date, these early treatment decisions have been taken based on limited information leading mainly to undertreatment. Therefore, there is a need for early, reliable, accessible, and simple tools that offer information on the possibilities of neurological improvement.

METHODS

We collected data from bispectral index (BIS) and suppression ratio (SR) monitoring of adult comatose survivors of CA managed with targeted temperature management (TTM). Neurological status was assessed according to the Cerebral Performance Category (CPC) scale.

RESULTS

We included 340 patients. At the first full neurological evaluation, 211 patients (62.1%) achieved good outcome or CPC 1-2. Mean BIS values were significantly higher and median SR lower in patients with CPC 1-2. An average BIS> 26 during first 12 hours of TTM predicted good outcome with 89.5% sensitivity and 75.8% specificity (AUC of 0.869), while average SR values> 24 during the first 12 hours of TTM predicted poor outcome (CPC 3-5) with 91.5% sensitivity and 81.8% specificity (AUC, 0.906). Hourly BIS and SR values exhibited good predictive performance (AUC> 0.85), as soon as hour 2 for SR and hour 4 for BIS.

CONCLUSIONS

BIS/SR are associated with patients' potential for neurological recovery after CA. This finding could help to create awareness of the possibility of a better outcome in patients who might otherwise be wrongly considered as nonviable and to establish personalized treatment escalation plans.

Effect of Carbon Dioxide on Bispectral Index of EEG under Intravenous Target-Controlled Anesthesia Based on Intelligent Medical Treatment

Laparoscopic surgery has the advantages of less trauma and quick recovery, and it is more and more favored by surgeons and patients in clinical practice. However, the impact of carbon dioxide pneumoperitoneum on the body during laparoscopic surgery has attracted the attention of many scholars. Pneumoperitoneum can cause increased cerebral blood flow and increased intracranial pressure, cerebral metabolic rate is highly correlated with blood carbon dioxide partial pressure, and cerebral metabolism without cardiopulmonary bypass is linearly correlated with the depth of anesthesia. Electroencephalographic (EEG) bispectral index (BIS) is a signal analysis method, which can directly measure the effect of drugs on the cerebral cortex and reflect the depth of anesthesia. Based on this, this study takes smart medical treatment as the background and uses the improved BP neural network as a tool to explore the effect of carbon dioxide on EEG bispectral index under intravenous target-controlled anesthesia. The main purpose is to observe the correlation between arterial blood carbon dioxide partial pressure and EEG bispectral index under propofol target-controlled anesthesia during retroperitoneal laparoscopic surgery. The experimental results show that the model proposed in this study can efficiently and accurately obtain the size of the influencing factors, which provides a clinical basis for the anesthesia management and anesthesia depth regulation of carbon dioxide pneumoperitoneum laparoscopic surgery.

Processed EEG from depth of anaesthesia monitors and seizures: A scoping review

PURPOSE

Processed electroencephalogram (EEG) is used peri-operatively for monitoring depth of anaesthesia. Because these utilise EEG data, attempts have been made to investigate their use in diagnosing and monitoring seizures. This is important as formal EEG monitoring can be hard to obtain in many critical care environments. We undertook a scoping review of the evidence for using processed EEG (pEEG) from depth of anaesthesia monitors for this indication.

METHODS

Medline, Psych INFO, and Embase were searched for peer-reviewed journals until 20 March 2021. Data and conclusions taken from the study of pEEG in both critical care and peri-operative settings have been included in a qualitative synthesis about the current evidence for the use of pEEG in the detection and monitoring of seizures.

RESULTS

Searches yielded 8 observational studies, 1 randomised trial and 15 case reports in which the use of pEEG in critical care and peri-operative medicine was described. Most concerned the Bispectral Index (BIS) device. The majority of observational studies reported the use of BIS for optimisation of burst suppression in patients with refractory status-epilepticus (RSE), or in the comparison of pEEG data with conventional EEG during epileptic activity. Multiple case reports describe the application of pEEG in the presence of disorders of consciousness as a tool for detection of non-convulsive status-epilepticus, finding variable trends in the pEEG output.

CONCLUSIONS

Processed EEG may be helpful in monitoring pharmacologically induced burst suppression. Despite this, its use in the diagnosing or monitoring seizure activity is controversial and currently not evidenced, with numerous confounding variables that requires systematic assessment in future studies.

Cost-effectiveness analysis of multimodal prognostication in cardiac arrest with EEG monitoring

OBJECTIVE

To determine cost-effectiveness parameters for EEG monitoring in cardiac arrest prognostication.

METHODS

We conducted a cost-effectiveness analysis to estimate the cost per quality-adjusted life-year (QALY) gained by adding continuous EEG monitoring to standard cardiac arrest prognostication using the American Academy of Neurology Practice Parameter (AANPP) decision algorithm: neurologic examination, somatosensory evoked potentials, and neuron-specific enolase. We explored lifetime cost-effectiveness in a closed system that incorporates revenue back into the medical system (return) from payers who survive a cardiac arrest with good outcome and contribute to the health system during the remaining years of life. Good outcome was defined as a Cerebral Performance Category (CPC) score of 1-2 and poor outcome as CPC of 3-5.

RESULTS

An improvement in specificity for poor outcome prediction of 4.2% would be sufficient to make continuous EEG monitoring cost-effective (baseline AANPP specificity = 83.9%). In sensitivity analysis, the effect of increased sensitivity on the cost-effectiveness of EEG depends on the utility (u) assigned to a poor outcome. For patients who regard surviving with a poor outcome (CPC 3-4) worse than death (u = -0.34), an increased sensitivity for poor outcome prediction of 13.8% would make AANPP + EEG monitoring cost-effective (baseline AANPP sensitivity = 76.3%). In the closed system, an improvement in sensitivity of 1.8% together with an improvement in specificity of 3% was sufficient to make AANPP + EEG monitoring cost-effective, assuming lifetime return of 50% (USD $70,687).

CONCLUSION

Incorporating continuous EEG monitoring into cardiac arrest prognostication is cost-effective if relatively small improvements in sensitivity and specificity are achieved.

The Prognostic Value of Simplified EEG in Out-of-Hospital Cardiac Arrest Patients

BACKGROUND

We previously validated simplified electroencephalogram (EEG) tracings obtained by a bispectral index (BIS) device against standard EEG. This retrospective study now investigated whether BIS EEG tracings can predict neurological outcome after cardiac arrest (CA).

METHODS

Bilateral BIS monitoring (BIS VISTA™, Aspect Medical Systems, Inc. Norwood, USA) was started following intensive care unit admission. Six, 12, 18, 24, 36 and 48 h after targeted temperature management (TTM) at 33 °C was started, BIS EEG tracings were extracted and reviewed by two neurophysiologists for the presence of slow diffuse rhythm, burst suppression, cerebral inactivity and epileptic activity (defined as continuous, monomorphic, > 2 Hz generalized sharp activity or continuous, monomorphic, < 2 Hz generalized blunt activity). At 180 days post-CA, neurological outcome was determined using cerebral performance category (CPC) classification (CPC1-2: good and CPC3-5: poor neurological outcome).

RESULTS

Sixty-three out-of-hospital cardiac arrest patients were enrolled for data analysis of whom 32 had a good and 31 a poor neurological outcome. Epileptic activity within 6-12 h predicted CPC3-5 with a positive predictive value (PPV) of 100%. Epileptic activity within time frames 18-24 and 36-48 h showed a PPV for CPC3-5 of 90 and 93%, respectively. Cerebral inactivity within 6-12 h predicted CPC3-5 with a PPV of 57%. In contrast, cerebral inactivity between 36 and 48 h predicted CPC3-5 with a PPV of 100%. The pattern with the worst predictive power at any time point was burst suppression with PPV of 44, 57 and 40% at 6-12 h, at 18-24 h and at 36-48 h, respectively. Slow diffuse rhythms at 6-12 h, at 18-24 h and at 36-48 h predicted CPC1-2 with PPV of 74, 76 and 80%, respectively.

CONCLUSION

Based on simplified BIS EEG, the presence of epileptic activity at any time and cerebral inactivity after the end of TTM may assist poor outcome prognostication in successfully resuscitated CA patients. A slow diffuse rhythm at any time after CA was indicative for a good neurological outcome.