Clinical outcome after a reactive hypothermic EEG following cardiac arrest

EEG for good outcome prediction after cardiac arrest: A multicentre cohort study

AIM

Assess the prognostic ability of a non-highly malignant and reactive EEG to predict good outcome after cardiac arrest (CA).

METHODS

Prospective observational multicentre substudy of the "Targeted Hypothermia versus Targeted Normothermia after Out-of-hospital Cardiac Arrest Trial", also known as the TTM2-trial. Presence or absence of highly malignant EEG patterns and EEG reactivity to external stimuli were prospectively assessed and reported by the trial sites. Highly malignant patterns were defined as burst-suppression or suppression with or without superimposed periodic discharges. Multimodal prognostication was performed 96 h after CA. Good outcome at 6 months was defined as a modified Rankin Scale score of 0-3.

RESULTS

873 comatose patients at 59 sites had an EEG assessment during the hospital stay. Of these, 283 (32%) had good outcome. EEG was recorded at a median of 69 h (IQR 47-91) after CA. Absence of highly malignant EEG patterns was seen in 543 patients of whom 255 (29% of the cohort) had preserved EEG reactivity. A non-highly malignant and reactive EEG had 56% (CI 50-61) sensitivity and 83% (CI 80-86) specificity to predict good outcome. Presence of EEG reactivity contributed (p < 0.001) to the specificity of EEG to predict good outcome compared to only assessing background pattern without taking reactivity into account.

CONCLUSION

Nearly one-third of comatose patients resuscitated after CA had a non-highly malignant and reactive EEG that was associated with a good long-term outcome. Reactivity testing should be routinely performed since preserved EEG reactivity contributed to prognostic performance.

Quantitative EEG reactivity induced by electrical stimulation predicts good outcome in comatose patients after cardiac arrest

BACKGROUND

EEG reactivity is a predictor for neurological outcome in comatose patients after cardiac arrest (CA); however, its application is limited by variability in stimulus types and visual assessment. We aimed to evaluate the prognostic value of the quantitative analysis of EEG reactivity induced by standardized electrical stimulation and for early prognostication in this population.

METHODS

This prospective observational study recruited post-CA comatose patients in Xuanwu Hospital, Capital Medical University (Beijing, China) between January 2016 and June 2023. EEG reactivity to electrical or traditional pain stimulation was randomly performed via visual and quantitative analysis. Neurological outcome within 6 months was dichotomized as good (Cerebral Performance Categories, CPC 1-2) or poor (CPC 3-5).

RESULTS

Fifty-eight post-CA comatose patients were admitted, and 52 patients were included in the final analysis, of which 19 (36.5%) had good outcomes. EEG reactivity induced with the electrical stimulation had superior performance to the traditional pain stimulation for good outcome prediction (quantitative analysis: AUC 0.932 vs. 0.849, p = 0.048). When using the electrical stimulation, the AUC of EEG reactivity to predict good outcome by visual analysis was 0.838, increasing to 0.932 by quantitative analysis (p = 0.039). Comparing to the traditional pain stimulation by visual analysis, the AUC of EEG reactivity for good prognostication by the electrical stimulation with quantitative analysis was significantly improved (0.932 vs. 0.770, p = 0.004).

CONCLUSIONS

EEG reactivity induced by the standardized electrical stimulation in combination with quantitative analysis is a promising formula for post-CA comatose patients, with increased predictive accuracy.

Methods of Evaluating EEG Reactivity in Adult Intensive Care Units: A Review

PURPOSE

EEG reactivity (EEG-R) has become widely used in intensive care units for diagnosing and prognosticating patients with disorders of consciousness. Despite efforts toward standardization, including the establishment of terminology for critical care EEG in 2012, the processes of testing and interpreting EEG-R remain inconsistent.

METHODS

A review was conducted on PubMed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Inclusion criteria consisted of articles published between January 2012, and November 2022, testing EEG-R on adult intensive care unit patients. Exclusion criteria included articles focused on highly specialized stimulation equipment or animal, basic science, or small case report studies. The Quality In Prognostic Studies tool was used to assess risk of bias.

RESULTS

One hundred and five articles were identified, with 26 variables collected for each. EEG-R testing varied greatly, including the number of stimuli (range: 1-8; 26 total described), stimulus length (range: 2-30 seconds), length between stimuli (range: 10 seconds-5 minutes), frequency of stimulus application (range: 1-9), frequency of EEG-R testing (range: 1-3 times daily), EEG electrodes (range: 4-64), personnel testing EEG-R (range: neurophysiologists to nonexperts), and sedation protocols (range: discontinuing all sedation to no attempt). EEG-R interpretation widely varied, including EEG-R definitions and grading scales, personnel interpreting EEG-R (range: EEG specialists to nonneurologists), use of quantitative methods, EEG filters, and time to detect EEG-R poststimulation (range: 1-30 seconds).

CONCLUSIONS

This study demonstrates the persistent heterogeneity of testing and interpreting EEG-R over the past decade, and contributing components were identified. Further many institutional efforts must be made toward standardization, focusing on the reproducibility and unification of these methods, and detailed documentation in the published literature.

Relationship between serum neuron-specific enolase and EEG after cardiac arrest: A reappraisal

OBJECTIVE

Electroencephalogram (EEG) and serum neuron specific enolase (NSE) are frequently used prognosticators after cardiac arrest (CA). This study explored the association between NSE and EEG, considering the role of EEG timing, its background continuity, reactivity, occurrence of epileptiform discharges, and pre-defined malignancy degree.

METHODS

Retrospective analysis including 445 consecutive adults from a prospective registry, surviving the first 24 hours after CA and undergoing multimodal evaluation. EEG were interpreted blinded to NSE results.

RESULTS

Higher NSE was associated with poor EEG prognosticators, such as increasing malignancy, repetitive epileptiform discharges and lack of background reactivity, independently of EEG timing (including sedation and temperature). When stratified for background continuity, NSE was higher with repetitive epileptiform discharges, except in the case of suppressed EEGs. This relationship showed some variation according to the recording time.

CONCLUSIONS

Neuronal injury after CA, reflected by NSE, correlates with several EEG features: increasing EEG malignancy, lack of background reactivity, and presence of repetitive epileptiform discharges. The correlation between epileptiform discharges and NSE is influenced by underlying EEG background and timing.

SIGNIFICANCE

This study, describing the complex interplay between serum NSE and epileptiform features, suggests that epileptiform discharges reflect neuronal injury particularly in non-suppressed EEG.

Predictive Value and Correlation of Neuron-Specific Enolase for Prognosis in Patients with Coma: A Systematic Review and Meta-Analysis

OBJECTIVE

Coma is the most serious disturbance of consciousness, which affects the life quality of patients and increases the burden of their family. Studies to assess the prognostic value of neuron-specific enolase (NSE) in patients with coma have not led to precise, generally accepted prognostic rules. The study aims to assess the correlation between NSE and prognosis of coma and the predictive value of NSE for clinical prognosis.

METHODS

A search was conducted using PubMed, Web of Science, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI), and WanFang Data from the establishment time of databases to December 2019. This analysis included patients with coma, regardless of how long the coma was. In total, 26 articles were retrieved and included in the review.

RESULTS

The meta-analysis revealed the NSE concentration of patients with coma is significantly higher than that of the control group (standard mean difference = 0.88, 95% confidence interval [CI]: 0.63-1.12, p < 0.05). The pooled sensitivity and specificity of NSE in coma diagnosis was 0.5 (95% CI: 0.39-0.61) and 0.86 (95% CI: 0.71-0.94).

CONCLUSIONS

The NSE concentration of patients with poor coma prognosis is significantly higher than that of the control group. The high NSE concentration is not necessarily a poor prognosis for coma, but low NSE concentration indicates a high probability of a good prognosis for coma.

The Use of Continuous EEG Monitoring in Intensive Care Units in The Netherlands: A National Survey

Background

Currently, continuous electroencephalographic monitoring (cEEG) is the only available diagnostic tool for continuous monitoring of brain function in intensive care unit (ICU) patients. Yet, the exact relevance of routinely applied ICU cEEG remains unclear, and information on the implementation of cEEG, especially in Europe, is scarce. This study explores current practices of cEEG in adult Dutch ICU departments focusing on organizational and operational factors, development over time and factors perceived relevant for abstaining its use.

Methods

A national survey on cEEG in adults among the neurology and adult intensive care departments of all Dutch hospitals (n = 82) was performed.

Results

The overall institutional response rate was 78%. ICU cEEG is increasingly used in the Netherlands (in 37% of all hospitals in 2016 versus in 21% in 2008). Currently in 88% of university, 55% of teaching and 14% of general hospitals use ICU cEEG. Reasons for not performing cEEG are diverse, including perceived non-feasibility and lack of data on the effect of cEEG use on patient outcome. Mostly, ICU cEEG is used for non-convulsive seizures or status epilepticus and prognostication. However, cEEG is never or rarely used for monitoring cerebral ischemia and raised intracranial pressure in traumatic brain injury. Review and reporting practices differ considerably between hospitals. Nearly all hospitals perform non-continuous review of cEEG traces. Methods for moving toward continuous review of cEEG traces are available but infrequently used in practice.

Conclusions

cEEG is increasingly used in Dutch ICUs. However, cEEG practices vastly differ between hospitals. Future research should focus on uniform cEEG practices including unambiguous EEG interpretation to facilitate collaborative research on cEEG, aiming to provide improved standard patient care and robust data on the impact of cEEG use on patient outcome.

Electroencephalographic reactivity as predictor of neurological outcome in postanoxic coma: A multicenter prospective cohort study

Objective

Outcome prediction in patients after cardiac arrest (CA) is challenging. Electroencephalographic reactivity (EEG‐R) might be a reliable predictor. We aimed to determine the prognostic value of EEG‐R using a standardized assessment.

Methods

In a prospective cohort study, a strictly defined EEG‐R assessment protocol was executed twice per day in adult patients after CA. EEG‐R was classified as present or absent by 3 EEG readers, blinded to patient characteristics. Uncertain reactivity was classified as present. Primary outcome was best Cerebral Performance Category score (CPC) in 6 months after CA, dichotomized as good (CPC = 1–2) or poor (CPC = 3–5). EEG‐R was considered reliable for predicting poor outcome if specificity was ≥95%. For good outcome prediction, a specificity of ≥80% was used. Added value of EEG‐R was the increase in specificity when combined with EEG background, neurological examination, and somatosensory evoked potentials (SSEPs).

Results

Of 160 patients enrolled, 149 were available for analyses. Absence of EEG‐R for poor outcome prediction had a specificity of 82% and a sensitivity of 73%. For good outcome prediction, specificity was 73% and sensitivity 82%. Specificity for poor outcome prediction increased from 98% to 99% when EEG‐R was added to a multimodal model. For good outcome prediction, specificity increased from 70% to 89%.

Interpretation

EEG‐R testing in itself is not sufficiently reliable for outcome prediction in patients after CA. For poor outcome prediction, it has no substantial added value to EEG background, neurological examination, and SSEPs. For prediction of good outcome, EEG‐R seems to have added value. ANN NEUROL 2019

Postanoxic alpha, theta or alpha-theta coma: Clinical setting and neurological outcome

AIM

The aim of this study was to determine the prognosis of 26 consecutive adults with alpha coma (AC), theta coma (TC) or alpha-theta coma (ATC) following CRA and to describe the clinical setting and EEG features of these patients.

METHODS

We retrospective analyzed a prospectively collected cohort of adult patients diagnosed as having AC, TC or ATC after CRA between January 2008 and June 2016. None of patients included in this analysis underwent therapeutic hypothermia (TH). Neurological outcome was expressed as the best score 6 months after CRA using the five-point Glasgow-Pisttsburgh Cerebral Performance Categories (CPC) RESULTS: Twenty-six patients were identified with a diagnosis of postanoxic AC, TC or ATC coma. There were 20 (77%) men and 6 (23%) women. The mean age was 63 ± 16 years. The most frequent EEG pattern was TC (21 patients, 80%), followed by AC (3 patients, 12%) and ATC (2 patients, 8%). The cardiac rhythm as primary origin of the CRA was ventricular fibrillation (VF) in 16 patients (61.5%), asystole in 8 patients (34.6%) and ventricular tachycardia (VT) in one patient (3.8%). The presence of EEG reactivity was present in 8 patients (30%). The mortality rate was 85%. Of the 4 surviving patients, two (3.8%) had moderate disability (CPC 2), one (3.8%) had severe disability (CPC 3) and one (3.8%) reached a good recovery. The age was significantly lower in survivors 46.2 ± 10.8 versus nonsurvivors 63.3 ± 15.5 (p = 0.04). There was increased association of EEG reactivity with survival (p = 0.07).

CONCLUSION

Hypoxic-ischemic AC, TC and ATC are associated with a poor prognosis and a high rate of mortality. In younger patients with AC, TC and ATC and incomplete forms showing reactivity on the EEG, there is a greater probability of clinical recovery.

Care pathways models and clinical outcomes in Disorders of consciousness

OBJECTIVE

Patients with Disorders of consciousness, are persons with extremely low functioning levels and represent a challenge for health care systems due to their high needs of facilitating environmental factors. Despite a common Italian health care pathway for these patients, no studies have analyzed information on how each region have implemented it in its welfare system correlating data with patients' clinical outcomes.

MATERIALS AND METHODS

A multicenter observational pilot study was realized. Clinicians collected data on the care pathways of patients with Disorder of consciousness by asking 90 patients' caregivers to complete an ad hoc questionnaire through a structured phone interview. Questionnaire consisted of three sections: sociodemographic data, description of the care pathway done by the patient, and caregiver evaluation of health services and information received.

RESULTS

Seventy-three patients were analyzed. Length of hospital stay was different across the health care models and it was associated with improvement in clinical diagnosis. In long-term care units, the diagnosis at admission and the number of caregivers available for each patient (median value = 3) showed an indirect relationship with worsening probability in clinical outcome. Caregivers reported that communication with professionals (42%) and the answer to the need of information were the most critical points in the acute phase, whereas presence of Non-Governmental Organizations (25%) and availability of psychologists for caregivers (21%) were often missing during long-term care. The 65% of caregivers reported they did not know the UN Convention on the Rights of Persons with Disabilities.

CONCLUSION

This study highlights relevant differences in analyzed models, despite a recommended national pathway of care. Future public health considerations and actions are needed to guarantee equity and standardization of the care process in all European countries.

Continuous electroencephalographic-monitoring in the ICU: an overview of current strengths and future challenges

PURPOSE OF REVIEW

In ICUs, numerous physiological parameters are continuously monitored and displayed. Yet, functional monitoring of the organ of primary concern, the brain, is not routinely performed. Despite the benefits of ICU use of continuous electroencephalographic (EEG)-monitoring (cEEG) is increasingly recognized, several issues nevertheless seem to hamper its widespread clinical implementation.

RECENT FINDINGS

Utilization of ICU cEEG has significantly improved detection and characterization of cerebral pathology, prognostication and clinical management in specific patient groups. Potential solutions to several remaining challenges are currently being established. Descriptive EEG-terminology is evolving, whereas logistical issues are dealt with using telemedicine and quantitative EEG trends, training of nonexpert personnel and development of specialized detection algorithms. These concerted solutions are advancing cEEG-registration towards cEEG-monitoring. Notwithstanding these advances, obstacles such as ambiguous EEG-interpretation and differences in treatment based on EEG-findings need yet to be overcome.

SUMMARY

In selected critically ill patient groups, ICU cEEG has clear benefits over (repeated) standard EEG or no functional brain monitoring at all and if available, cEEG should be used. However, several issues preventing optimal ICU cEEG usage persist and should be further explored.

Clinical neurophysiology for neurological prognostication of comatose patients after cardiac arrest

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A multimodal prognostic approach is recommended after cardiac arrest.

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EEG (background and, reactivity, repetitive epileptiform features) and SSEP are core assessments.

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Some outlook into long-latency evoked potentials is offered.

Early prognostication of outcome in comatose patients after cardiac arrest represents a daunting task for clinicians, also considering the nowadays commonly used targeted temperature management with sedation in the first 24–48 h. A multimodal approach is currently recommended, in order to minimize the risks of false-positive prediction of poor outcome, including clinical examination off sedation, EEG (background characterization and reactivity, occurrence of repetitive epileptiform features), and early-latency SSEP responses represent the core assessments in this setting; they may be complemented by biochemical markers and neuroimaging.

This paper, which relies on a recent comprehensive review, focuses on an updated review of EEG and SSEP, and also offers some outlook into long-latency evoked potentials, which seem promising in clinical use.

EEG synchronization measures are early outcome predictors in comatose patients after cardiac arrest

OBJECTIVE

Outcome prognostication in comatose patients after cardiac arrest (CA) remains a major challenge. Here we investigated the prognostic value of combinations of linear and non-linear bivariate EEG synchronization measures.

METHODS

94 comatose patients with EEG within 24h after CA were included. Clinical outcome was assessed at 3months using the Cerebral Performance Categories (CPC). EEG synchronization between the left and right parasagittal, and between the frontal and parietal brain regions was assessed with 4 different quantitative measures (delta power asymmetry, cross-correlation, mutual information, and transfer entropy). 2/3 of patients were used to assess the predictive power of all possible combinations of these eight features (4 measures×2 directions) using cross-validation. The predictive power of the best combination was tested on the remaining 1/3 of patients.

RESULTS

The best combination for prognostication consisted of 4 of the 8 features, and contained linear and non-linear measures. Predictive power for poor outcome (CPC 3-5), measured with the area under the ROC curve, was 0.84 during cross-validation, and 0.81 on the test set. At specificity of 1.0 the sensitivity was 0.54, and the accuracy 0.81.

CONCLUSION

Combinations of EEG synchronization measures can contribute to early prognostication after CA. In particular, combining linear and non-linear measures is important for good predictive power.

SIGNIFICANCE

Quantitative methods might increase the prognostic yield of currently used multi-modal approaches.

EEG as an Indicator of Cerebral Functioning in Postanoxic Coma

Postanoxic coma after cardiac arrest is one of the most serious acute cerebral conditions and a frequent cause of admission to critical care units. Given substantial improvement of outcome over the recent years, a reliable and timely assessment of clinical evolution and prognosis is essential in this context, but may be challenging. In addition to the classic neurologic examination, EEG is increasingly emerging as an important tool to assess cerebral functions noninvasively. Although targeted temperature management and related sedation may delay clinical assessment, EEG provides accurate prognostic information in the early phase of coma. Here, the most frequently encountered EEG patterns in postanoxic coma are summarized and their relations with outcome prediction are discussed. This article also addresses the influence of targeted temperature management on brain signals and the implication of the evolution of EEG patterns over time. Finally, the article ends with a view of the future prospects for EEG in postanoxic management and prognostication.

Nonconvulsive status epilepticus in adults - insights into the invisible

Nonconvulsive status epilepticus (NCSE) is a state of continuous or repetitive seizures without convulsions. Owing to the nonspecific symptoms and considerable morbidity and mortality associated with NCSE, clinical research has focused on early diagnosis, risk stratification and seizure termination. The subtle symptoms and the necessity for electroencephalographic confirmation of seizures result in under-diagnosis with deleterious consequences. The introduction of continuous EEG to clinical practice, and the characterization of electrographic criteria have delineated a number of NCSE types that are associated with different prognoses in several clinical settings. Epidemiological studies have uncovered risk factors for NCSE; knowledge of these factors, together with particular clinical characteristics and EEG observations, enables tailored treatment. Despite these advances, NCSE can be refractory to antiepileptic drugs, necessitating further escalation of treatment. The presumptive escalation to anaesthetics, however, has recently been questioned owing to an association with increased mortality. This Review compiles epidemiological, clinical and diagnostic aspects of NCSE, and considers current treatment options and prognosis.

Neurological prognostication of outcome in patients in coma after cardiac arrest

Management of coma after cardiac arrest has improved during the past decade, allowing an increasing proportion of patients to survive, thus prognostication has become an integral part of post-resuscitation care. Neurologists are increasingly confronted with raised expectations of next of kin and the necessity to provide early predictions of long-term prognosis. During the past decade, as technology and clinical evidence have evolved, post-cardiac arrest prognostication has moved towards a multimodal paradigm combining clinical examination with additional methods, consisting of electrophysiology, blood biomarkers, and brain imaging, to optimise prognostic accuracy. Prognostication should never be based on a single indicator; although some variables have very low false positive rates for poor outcome, multimodal assessment provides resassurance about the reliability of a prognostic estimate by offering concordant evidence.

EEG in postanoxic coma: Prognostic and diagnostic value

Evolution of the EEG background pattern is a robust contributor to prediction of poor or good outcome of comatose patients after cardiac arrest. At 24h, persistent isoelectricity, low voltage activity, or burst-suppression with identical bursts predicts a poor outcome without false positives. Rapid recovery toward continuous patterns within 12h is strongly associated with a good neurological outcome. Predictive values are highest in the first 24h, despite the use of mild therapeutic hypothermia and sedative medication. Studies on reactivity or mismatch negativity have not included the EEG background pattern. Therefore, the additional predictive value of reactivity parameters remains unclear. Whether or not treatment of electrographic status epilepticus improves outcome is studied in the randomized multicenter Treatment of Electroencephalographic STatus epilepticus After cardiopulmonary Resuscitation (TELSTAR) trial (NCT02056236).

Predictive value of EEG-awakening for behavioral awakening from coma

BACKGROUND

A reliable predictor for early recovery of consciousness in comatose patients is of great clinical significance. Here we aimed to investigate the potentially prognostic value of electroencephalogram-reactivity (EEG-R) in combination with sleep spindles, termed EEG-awakening, for behavioral awakening in etiologically diverse comatose patients.

METHODS

We performed a prospectively observational study on a sample of patients, all of whom were in coma lasting longer than 3 days. Continuous EEG monitoring was performed for at least 24 h to detect the presence of EEG-R and sleep spindles. We then followed patients for 1 month to determine their subsequent level of consciousness, classifying them as either awakened or non-awakened. Finally, Univariate and multivariate analyses were employed to assess the association of predictors with consciousness recovery.

RESULTS

One hundred and six patients with different etiologies leading to coma were included in the study. Of these, 48 patients (45.3 %) awoke and 58 patients (54.7 %) did not awake in the month after the onset of the study. Of note, 26 patients (24.5 %) had a good neurological outcome, and 31 patients (29.3 %) died. Univariate analysis revealed that the Glasgow Coma Scale (GCS) score, EEG-R, sleep spindles, and EEG-awakening were all associated with one-month awakening. Comparisons of the area under the receiving operator characteristic curve (AUC) showed that EEG-awakening (0.839; 0.757-0.921) was superior to all of the following: EEG-R (0.798; 0.710-0.886), sleep spindles (0.772; 0.680-0.864), and GCS scores (0.720; 0.623-0.818). However, age, gender, etiology, and pupillary light reflex did not correlate significantly with one-month awakening. Further logistic regression analysis showed that only EEG-awakening and GCS scores at study entry were significant independent predictors of awakening and that the prognostic model containing these two variables yielded an outstanding predictive performance with an AUC of 0.903.

CONCLUSIONS

EEG-awakening incorporates both EEG-R and sleep spindles and is an excellent predictor for early behavioral awakening in comatose patients. The prognostic model combining EEG-awakening and GCS scores shows an outstanding discriminative power for awakening.

Electrophysiological Monitoring of Brain Injury and Recovery after Cardiac Arrest

Reliable prognostic methods for cerebral functional outcome of post cardiac-arrest (CA) patients are necessary, especially since therapeutic hypothermia (TH) as a standard treatment. Traditional neurophysiological prognostic indicators, such as clinical examination and chemical biomarkers, may result in indecisive outcome predictions and do not directly reflect neuronal activity, though they have remained the mainstay of clinical prognosis. The most recent advances in electrophysiological methods--electroencephalography (EEG) pattern, evoked potential (EP) and cellular electrophysiological measurement--were developed to complement these deficiencies, and will be examined in this review article. EEG pattern (reactivity and continuity) provides real-time and accurate information for early-stage (particularly in the first 24 h) hypoxic-ischemic (HI) brain injury patients with high sensitivity. However, the signal is easily affected by external stimuli, thus the measurements of EP should be combined with EEG background to validate the predicted neurologic functional result. Cellular electrophysiology, such as multi-unit activity (MUA) and local field potentials (LFP), has strong potential for improving prognostication and therapy by offering additional neurophysiologic information to understand the underlying mechanisms of therapeutic methods. Electrophysiology provides reliable and precise prognostication on both global and cellular levels secondary to cerebral injury in cardiac arrest patients treated with TH.

Continuous Amplitude-Integrated Electroencephalographic Monitoring Is a Useful Prognostic Tool for Hypothermia-Treated Cardiac Arrest Patients

Supplemental Digital Content is available in the text.

Modern treatments have improved the survival rate following cardiac arrest, but prognostication remains a challenge. We examined the prognostic value of continuous electroencephalography according to time by performing amplitude-integrated electroencephalography on patients with cardiac arrest receiving therapeutic hypothermia.

Prognostic values of gray matter to white matter ratios on early brain computed tomography in adult comatose patients after out-of-hospital cardiac arrest of cardiac etiology

AIM OF THE STUDY

Previous studies found that the gray matter to white matter ratio (GWR) on brain computed tomography (CT) could be used to predict poor outcomes in cardiac arrest survivors. However, these studies have included cardiac arrests of both cardiac and non-cardiac etiologies. We sought to evaluate if the GWR on brain CT can help to predict poor outcomes after out-of-hospital cardiac arrest (OHCA) of cardiac etiology.

METHODS

Using a multicenter retrospective registry of adult cardiac arrest survivors treated with therapeutic hypothermia, we identified survivors of OHCA of cardiac etiology who underwent brain CT within 24h after successful resuscitation. Gray and white matter attenuations were measured, and the GWRs were calculated as in previous studies. The prognostic values of the GWRs were analyzed, and a logistic regression analysis was performed to determine the contribution of the GWR in predicting poor outcomes (Cerebral Performance Category 3-5).

RESULTS

of 283 included patients, 140 had good outcomes and 143 had poor outcomes. Although the GWRs could predict poor outcomes with statistical significance, the sensitivities were remarkably low (3.5% to 5.6%) at cutoff values with 100% specificity. No significant difference in predictive performance was found between the primary predictive model, containing independent poor outcome predictors, and the primary predictive model combined with the GWR.

CONCLUSION

In a cohort of comatose adults after OHCA of cardiac etiology, the GWR demonstrated poor predictive performance and was not helpful in predicting poor outcomes.