Neurological prognostication of outcome in patients in coma after cardiac arrest

Long-Term Disabilities of Survivors of Out-of-Hospital Cardiac Arrest: The Hanox Study

BACKGROUND

Long-term outcomes of awakened survivors of out-of-hospital cardiac arrest (OHCA) are poorly known.

RESEARCH QUESTION

What are the month (M) 18 outcomes of survivors of out-of-hospital cardiac arrest (OHCA) who awakened during the first 2 weeks' post-OHCA and their poor-outcome risk factors?

STUDY DESIGN AND METHODS

All OHCA survivors with a Glasgow Coma Scale score ≥12 during the first 2 weeks' post-OHCA were enrolled in six ICUs and followed up at M3, M6, M12, and M18. The primary outcome measure was Glasgow Outcome Scale-Extended (GOS-E) score at M18. Secondary outcome measures included evaluation at M18 of neurologic, behavioral, and cognitive disabilities; health-related quality of life (HR-QOL), anxiety and depression; and poor-outcome risk factors (GOS-E score ≤ 6).

RESULTS

Among the 139 included patients, 98 were assessable for the primary outcome measure. At M18, 64 (65%) had full recovery or minor disabilities (GOS-E score > 6), 18 (18%) had moderate disabilities but were autonomous for daily-life activities (GOS-E score = 6), 12 (12%) had poor autonomy (GOS-E score < 6 but > 1), and four had died. Percentages of patients with GOS-E scores > 6 increased significantly over the 18-month study period. At M18, no patients had major neurologic disabilities, 20% had cognitive disabilities, 32% had anxiety symptoms, 25% had depression symptoms, and their HR-QOL was impaired compared with a sex- and age-matched population. Low-flow time, Sequential Organ Failure Assessment score at admission, coma duration > 3 days after cardiac arrest, and mechanical ventilation on days 3 and 7 were associated with poor functional outcome.

INTERPRETATION

Among patients who awoke (Glasgow Coma Scale score ≥12) in the 14 days following OHCA, 35% had moderate to severe disabilities or had died at M18. Interestingly, patients improved until M18 post-OHCA. Risk factors associated with poor functional outcome were low-flow time, clinical severity at ICU admission, prolonged coma duration, and mechanical ventilation.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov; No.: NCT02292147; URL: www.clinicaltrials.gov.

Prediction of the level of consciousness using pupillometer measurements in patients with impaired consciousness brought to the emergency and critical care center

Aim

We investigated whether the level of consciousness can be predicted using pupillometer measurements in patients with severe disturbance of consciousness.

Methods

Patients with a Glasgow Coma Scale (GCS) of 3–8, except for those after cardiac arrest, were included. Pupillary contraction rate and contraction velocity were each measured using a pupillometer.

Results

Thirty‐five patients were analyzed. At the time of discharge or changing hospitals, 16 patients had a GCS score of 3–13 and 19 patients had a GCS score of 14–15. In the non‐sedative group at about the time of arrival at our hospital, average pupillary contraction rates were 18.36% in the GCS 3–13 group and 19.67% in the GCS 14–15 group (P = 0.739), and average pupillary contraction velocities were 1.02 and 1.48, respectively (P = 0.182). Approximately 48 h after arrival, average pupillary contraction rates were 21.18% and 29.27%, respectively (P = 0.058), and average pupillary contraction velocities were 1.37 and 1.91, respectively (P = 0.172). Among the sedative group, at about the time of arrival, average pupillary contraction rates were 8.75% in the GCS 3–13 group and 19.75% in the GCS 14–15 group (P = 0.032). Average pupillary contraction velocities were 0.34 and 1.48, respectively (P = 0.001). Approximately 48 h after arrival, average pupillary contraction rates were 13.50% and 13.50%, respectively (P = 1.00), and average pupillary contraction velocities were 0.80 and 0.82, respectively (P = 0.93).

Conclusions

Pupillometer measurements could predict level of consciousness of patients with severe consciousness disorder.

EEG reactivity testing for prediction of good outcome in patients after cardiac arrest

Objective

To determine the additional value of EEG reactivity (EEG-R) testing to EEG background pattern for prediction of good outcome in adult patients after cardiac arrest (CA).

Methods

In this post hoc analysis of a prospective cohort study, EEG-R was tested twice a day, using a strict protocol. Good outcome was defined as a Cerebral Performance Category score of 1–2 within 6 months. The additional value of EEG-R per EEG background pattern was evaluated using the diagnostic odds ratio (DOR). Prognostic value (sensitivity and specificity) of EEG-R was investigated in relation to time after CA, sedative medication, different stimuli, and repeated testing.

Results

Between 12 and 24 hours after CA, data of 108 patients were available. Patients with a continuous (n = 64) or discontinuous (n = 19) normal voltage background pattern with reactivity were 3 and 8 times more likely to have a good outcome than without reactivity (continuous: DOR, 3.4; 95% confidence interval [CI], 0.97–12.0; p = 0.06; discontinuous: DOR, 8.0; 95% CI, 1.0–63.97; p = 0.0499). EEG-R was not observed in other background patterns within 24 hours after CA. In 119 patients with a normal voltage EEG background pattern, continuous or discontinuous, any time after CA, prognostic value was highest in sedated patients (sensitivity 81.3%, specificity 59.5%), irrespective of time after CA. EEG-R induced by handclapping and sternal rubbing, especially when combined, had highest prognostic value. Repeated EEG-R testing increased prognostic value.

Conclusion

EEG-R has additional value for prediction of good outcome in patients with discontinuous normal voltage EEG background pattern and possibly with continuous normal voltage. The best stimuli were clapping and sternal rubbing.

Postcardiac arrest neurological prognostication with quantitative regional cerebral densitometry

PURPOSE

To quantitatively assess the severity of anoxic-ischemic brain injury early after cardiac arrest (CA) using a novel automated method applied to head computed tomography (HCT).

METHODS

Adult patients who were comatose and underwent HCT < 24 h after arrest were included in a retrospective analysis. Principal endpoint was unfavorable outcome (UO) defined as Cerebral Performance Category (CPC) of 3-5 at hospital discharge. We developed an automated processing algorithm for HCT images to be registered, atlas-segmented in 181 regions, and region-specific radiologic densities determined in Hounsfield Units. This approach was compared with an established manual method evaluating grey-white matter ratios (GWR). We tested univariable and multivariable prognostic models which integrated clinical and HCT features including densities in lobes and in nodes of cerebral networks linked to CA recovery.

RESULTS

Ninety-one patients were enrolled among whom 66 (73%) had an UO. HCTs were interpreted as normal or without acute abnormality by a neuroradiologist in 77 cases (85%). Compared to the favorable outcome group, UO patients had significantly lower densities in all lobes and in nodes of cerebral networks. A model combining clinical variables with the automated method applied to cerebral network nodes had the highest prognostic performance although not significantly different than the combined clinical-GWR method (AUC [95% CI] 0.94 [0.86-1.00] and 0.92 [0.83-1.00] respectively).

CONCLUSION

In comatose survivors of CA, automated quantitative analysis of HCT revealed very early multifocal changes in brain tissue density which are mostly overlooked on conventional neuroradiologic interpretation and are associated with neurological outcome.

Prognostic value of magnetic resonance imaging performed during the subacute phase in adult patients with hypoxic-ischemic encephalopathy for long-term neurological outcomes

OBJECTIVE

To investigate the value of a model based on brain magnetic resonance imaging (MRI) performed in the subacute phase (between the 1st and 30th day) in predicting long-term neurological outcomes of adult hypoxic-ischemic encephalopathy (HIE) patients.

METHODS

Ninety-six adult HIE patients who underwent conventional MRI and diffusion-weighted imaging (DWI) during the subacute phase were retrospectively analyzed. Favorable (Cerebral Performance Categories (CPC) 1-2) and unfavorable outcome (CPC 3-5) groups were created based on patient neurological status approximately three months after the onset of hypoxic-ischemic events. A multivariate stepwise regression model was applied after univariate analysis of MRI findings, and then the overall MRI score, Alberta Stroke Program Early Computed Tomography Score (ASPECTS), Bilateral ASPECTS (Bi-ASPECTS), modified ASPECTS (mASPECTS) and Bi-ASPECTS combined with posterior circulation ASPECTS (PC-ASPECTS) were calculated based on MRI findings. Receiver operating characteristic (ROC) curves were used to assess prognostic accuracy.

RESULTS

Both univariate and multivariate analyses showed the cerebral cortex and cerebellum, neostriatum, hippocampus, brainstem and postanoxic leukoencephalopathy were independent prognostic factors for unfavorable outcomes. The multivariate regression analysis resulted in an overall classification accuracy of 84.4%, a sensitivity of 84.2% (95% CI, 71.6-92.1%), and a specificity of 92.3% (95% CI, 78.0-98.0%) for unfavorable outcomes. The model had an areas under the ROC curves (AUC) of 0.944 (95% CI, 0.901-0.987); the MRI overall scores were 0.918 (95% CI, 0.866, 0.971), ASPECTS 0.839 (95% CI, 0.755, 0.923), Bi-ASPECTS 0.837 (95% CI, 0.753, 0.922), mASPECTS 0.851(95% CI, 0.771, 0.931) and Bi-ASPECTS+PC-ASPECTS 0.876 (95% CI, 0.806, 0.946).

CONCLUSIONS

The multivariate model based on conventional MRI combined with DWI performed in the subacute phase could help predict the prognosis of adult HIE with high performance.

Qualitative and quantitative analysis of diffusion-weighted brain MR imaging in comatose survivors after cardiac arrest

PURPOSE

The aim of this study is to compare a qualitative and a quantitative assessment of brain diffusion-weighted imaging (DWI) in predicting outcome of comatose patients after cardiac arrest (CA).

METHODS

Two observers used a scoring template to analyze the DWI of 75 patients. A total of 13 regions were scored from 0 to 3 (0 = normal, 1 = probably normal, 2 = probably abnormal, 3 = definitely abnormal). The total cerebral cortex (TCC), the total deep grey nuclei (TDGN), the total brain stem, the total cerebellum, and the total brain score were calculated. Intra- and inter-observer variability were tested. The mean whole brain apparent diffusion coefficient (ADC) values and percentage of voxels below a specific ADC value cut-off were calculated. The data were correlated with clinical outcome (cerebral performance category score after 180 days, dichotomized in a score 1-2 with favorable outcome and score 3-5 with unfavorable outcome) using ROC analysis.

RESULTS

Intra-observer variability was excellent for the TCC score (ICC 0.95 and 0.86) and the TDGN score (ICC 0.89 and 0.75). Inter-observer variability was good to excellent for total cerebral cortex score and total deep grey nuclei score in both the first (ICC 0.78 and 0.69) and third (ICC 0.86 and 0.83) image assessment. TCC and TDGN score show the best correlation with clinical outcome (highest AUC values 0.87 and 0.87). Quantitative parameters did not show good correlation with clinical outcome (AUC values 0.57 and 0.60).

CONCLUSION

A qualitative assessment of brain DWI using a scoring template provides useful data regarding patient outcome while quantitative data appeared less reliable.

MRI-EEG correlation for outcome prediction in postanoxic myoclonus: A multicenter study

OBJECTIVE

To examine the prognostic ability of the combination of EEG and MRI in identifying patients with good outcome in postanoxic myoclonus (PAM) after cardiac arrest (CA).

METHODS

Adults with PAM who had an MRI within 20 days after CA were identified in 4 prospective CA registries. The primary outcome measure was coma recovery to command following by hospital discharge. Clinical examination included brainstem reflexes and motor activity. EEG was assessed for best background continuity, reactivity, presence of epileptiform activity, and burst suppression with identical bursts (BSIB). MRI was examined for presence of diffusion restriction or fluid-attenuated inversion recovery changes consistent with anoxic brain injury. A prediction model was developed using optimal combination of variables.

RESULTS

Among 78 patients, 11 (14.1%) recovered at discharge and 6 (7.7%) had good outcome (Cerebral Performance Category < 3) at 3 months. Patients who followed commands were more likely to have pupillary and corneal reflexes, flexion or better motor response, EEG continuity and reactivity, no BSIB, and no anoxic injury on MRI. The combined EEG/MRI variable of continuous background and no anoxic changes on MRI was associated with coma recovery at hospital discharge with sensitivity 91% (95% confidence interval [CI], 0.59-1.00), specificity 99% (95% CI, 0.92-1.00), positive predictive value 91% (95% CI, 0.59-1.00), and negative predictive value 99% (95% CI, 0.92-1.00).

CONCLUSIONS

EEG and MRI are complementary and identify both good and poor outcome in patients with PAM with high accuracy. An MRI should be considered in patients with myoclonus showing continuous or reactive EEGs.

Brain functional connectivity during the first day of coma reflects long-term outcome

•

Coma patients show different connectivity patterns depending on long-term outcome.

•

Time-variance of functional connectivity is an early prognostic marker for coma patients.

•

Connectivity patterns observed in chronic patients may develop early after coma onset.

Objective

In patients with disorders of consciousness (DOC), properties of functional brain networks at rest are informative of the degree of consciousness impairment and of long-term outcome. Here we investigate whether connectivity differences between patients with favorable and unfavorable outcome are already present within 24 h of coma onset.

Methods

We prospectively recorded 63-channel electroencephalography (EEG) at rest during the first day of coma after cardiac arrest. We analyzed 98 adults, of whom 57 survived beyond unresponsive wakefulness. Functional connectivity was estimated by computing the ‘debiased weighted phase lag index’ over epochs of five seconds duration. We evaluated the network’s topological features, including clustering coefficient, path length, modularity and participation coefficient and computed their variance over time. Finally, we estimated the predictive value of these topological features for patients’ outcomes by splitting the patient sample in training and test datasets.

Results

Group-level analysis revealed lower clustering coefficient, higher modularity and path length variance in patients with favorable compared to those with unfavorable outcomes (p < 0.01). Within all features, the path length variance in the network provided the best positive predictive value (PPV) for favorable outcome and specificity for unfavorable outcome in the test dataset (PPV: 0.83, p < 0.01; specificity: 0.86, p < 0.01) with above-chance negative predictive value and accuracy. Of note, the exclusion of patients with epileptiform activity (20 in total) eliminates all false positive predictions (n = 6) for path length variance.

Interpretation

Topological features of functional connectivity differ as a function of long-term outcome in patients on the first day of coma. These differences are not interpretable in terms of consciousness levels as all patients were in a deep unconscious state. The time variance of path length is informative of comatose patients’ outcome, as patients with favorable outcome exhibit a richer repertoire of path length than those with unfavorable outcomes.

Exploratory Analyses of Cerebral Gray Matter Volumes After Out-of-Hospital Cardiac Arrest in Good Outcome Survivors

Background

Survival rates of cardiac arrest have increased over recent years, however, survivors may still be left with significant morbidity and functional impairment. A primary concern in cardiac arrest survivors is the effect of prolonged hypoxia/ischemia on the brain. The objectives of the present study were threefold: (1) to explore the effect of cardiac arrest on brain gray matter volumes (GMV) in “good outcome” survivors of out-of-hospital cardiac arrest (OHCA), (2) to examine the relationship between GMV, cognitive functioning and arrest factors, and (3) to explore whether OHCA patients differ from a group of patients with myocardial infarction (MI) uncomplicated by cardiac arrest and a group of healthy controls in terms of GMV.

Methods

Medically stable OHCA survivors with preserved neurological function and who were eligible for magnetic resonance imaging scanning (MRI; n = 9), were compared to: (1) patients who had experienced a MI (n = 19) and (2) healthy controls (n = 12). Participants underwent brain MRI on a 3T Siemens Trio MRI scanner and GMV was measured by voxel-based morphometry. A comprehensive neuropsychological assessment was also conducted. Global GMV was compared in the three samples using analyses of variance. The relationships between cognition and GMV were examined within group using correlations.

Results

The OHCA and MI groups showed a similar pattern of differences compared to the healthy control group. Both groups had decreased GMV in the anterior cingulate cortex, bilateral hippocampus, right dorsolateral prefrontal cortex, right putamen, and bilateral cerebellum. There were no significant differences in global or regional GMV between the OHCA and MI groups. Cognitive functioning was correlated with global GMV in the OHCA group; no such correlation was observed in the MI group.

Conclusion

Regional atrophy was observed in OHCA and MI survivors, compared to a healthy control group, suggesting a common mechanism, presumably preexisting cardiovascular disease. Although similar regional volume differences were observed between the MI and OHCA groups, the relationship between GMV and cognition was only observed in OHCA survivors. We suggest the acute hypoxia/ischemia ensuing from the arrest may interact with diminished neural reserve in select brain areas to expose occult cognitive dysfunction.

Independent Functional Outcomes after Prolonged Coma following Cardiac Arrest: A Mechanistic Hypothesis

OBJECTIVE

Survivors of prolonged (>2 weeks) post-cardiac arrest (CA) coma are expected to remain permanently disabled. We aimed to investigate 3 outlier patients who ultimately achieved independent functional outcomes after prolonged post-CA coma to identify electroencephalographic (EEG) markers of their recovery potential. For validation purposes, we also aimed to evaluate these markers in an independent cohort of post-CA patients.

METHODS

We identified 3 patients with late recovery from coma (17-37 days) following CA who recovered to functionally independent behavioral levels. We performed spectral power analyses of available EEGs during prominent burst suppression patterns (BSP) present in all 3 patients. Using identical methods, we also assessed the relationship of intraburst spectral power and outcomes in a prospectively enrolled cohort of post-CA patients. We performed chart reviews of common clinical, imaging, and EEG prognostic variables and clinical outcomes for all patients.

RESULTS

All 3 patients with late recovery from coma lacked evidence of overwhelming cortical injury but demonstrated prominent BSP on EEG. Spectral analyses revealed a prominent theta (~4-7Hz) feature dominating the bursts during BSP in these patients. In the prospective cohort, similar intraburst theta spectral features were evident in patients with favorable outcomes; patients with BSP and unfavorable outcomes showed either no features, transient burst features, or decreasing intraburst frequencies with time.

INTERPRETATION

BSP with theta (~4-7Hz) peak intraburst spectral power after CA may index a recovery potential. We discuss our results in the context of optimizing metabolic substrate availability and stimulating the corticothalamic system during recovery from prolonged post-CA coma. ANN NEUROL 2020;87:618-632.

Resuscitating the Globally Ischemic Brain: TTM and Beyond

Cardiac arrest (CA) afflicts ~ 550,000 people each year in the USA. A small fraction of CA sufferers survive with a majority of these survivors emerging in a comatose state. Many CA survivors suffer devastating global brain injury with some remaining indefinitely in a comatose state. The pathogenesis of global brain injury secondary to CA is complex. Mechanisms of CA-induced brain injury include ischemia, hypoxia, cytotoxicity, inflammation, and ultimately, irreversible neuronal damage. Due to this complexity, it is critical for clinicians to have access as early as possible to quantitative metrics for diagnosing injury severity, accurately predicting outcome, and informing patient care. Current recommendations involve using multiple modalities including clinical exam, electrophysiology, brain imaging, and molecular biomarkers. This multi-faceted approach is designed to improve prognostication to avoid "self-fulfilling" prophecy and early withdrawal of life-sustaining treatments. Incorporation of emerging dynamic monitoring tools such as diffuse optical technologies may provide improved diagnosis and early prognostication to better inform treatment. Currently, targeted temperature management (TTM) is the leading treatment, with the number of patients needed to treat being ~ 6 in order to improve outcome for one patient. Future avenues of treatment, which may potentially be combined with TTM, include pharmacotherapy, perfusion/oxygenation targets, and pre/postconditioning. In this review, we provide a bench to bedside approach to delineate the pathophysiology, prognostication methods, current targeted therapies, and future directions of research surrounding hypoxic-ischemic brain injury (HIBI) secondary to CA.

Prediction of regaining consciousness despite an early epileptiform EEG after cardiac arrest

Objective

After cardiac arrest (CA), epileptiform EEG, occurring in about 1/3 of patients, often but not invariably heralds poor prognosis. We tested the hypothesis that a combination of specific EEG features identifies patients who may regain consciousness despite early epileptiform patterns.

Methods

We retrospectively analyzed a registry of comatose patients post-CA (2 Swiss centers), including those with epileptiform EEG. Background and epileptiform features in EEGs 12–36 hours or 36–72 hours from CA were scored according to the American Clinical Neurophysiology Society nomenclature. Best Cerebral Performance Category (CPC) score within 3 months (CPC 1–3 vs 4–5) was the primary outcome. Significant EEG variables were combined in a score assessed with receiver operating characteristic curves, and independently validated in a US cohort; its correlation with serum neuron-specific enolase (NSE) was also tested.

Results

Of 488 patients, 107 (21.9%) had epileptiform EEG <72 hours; 18 (17%) reached CPC 1–3. EEG 12–36 hours background continuity ≥50%, absence of epileptiform abnormalities (p< 0.00001 each), 12–36 and 36–72 hours reactivity (p< 0.0001 each), 36–72 hours normal background amplitude (p= 0.0004), and stimulus-induced discharges (p= 0.0001) correlated with favorable outcome. The combined 6-point score cutoff ≥2 was 100% sensitive (95% confidence interval [CI], 78%–100%) and 70% specific (95% CI, 59%–80%) for CPC 1–3 (area under the curve [AUC], 0.98; 95% CI, 0.94–1.00). Increasing score correlated with NSE (ρ = −0.46,p= 0.0001). In the validation cohort (41 patients), the score was 100% sensitive (95% CI, 60%–100%) and 88% specific (95% CI, 73%–97%) for CPC 1–3 (AUC, 0.96; 95% CI, 0.91–1.00).

Conclusion

Prognostic value of early epileptiform EEG after CA can be estimated combining timing, continuity, reactivity, and amplitude features in a score that correlates with neuronal damage.

Essential Noninvasive Multimodality Neuromonitoring for the Critically Ill Patient

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2020. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2020. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

Prognostication of neurological outcome after cardiac arrest using wavelet phase coherence analysis of cerebral oxygen

BACKGROUND

The prognosis for cardiac arrest (CA) is associated with the degree of cerebral ischemia. We investigated the relationship between the wavelet coherence of cerebral oxyhemoglobin (HbO₂) among different channels and outcomes after CA. Moreover, we aimed to develop a prognostication method after CA.

METHODS

Eighty-three post-resuscitation patients were included. The HbO₂ data were collected during the post-resuscitation period (median day, 1) using functional near-infrared spectroscopy. The coherence between sections of prefrontal HbO₂ oscillations in five frequency intervals (I, 0.6-2 Hz; II, 0.15-0.6 Hz; III, 0.05-0.15 Hz; IV, 0.02-0.05 Hz; and V, 0.0095-0.02 Hz) were analyzed. We evaluated the outcomes using cerebral performance category (CPC) scores (good outcome, CPC ≤ 2 and poor outcome, CPC ≥ 3) at 3 months after CA. Additionally, the predictive method was developed using the biomarker and coherence value after CA.

RESULTS

Among the included patients, 19 patients (22.9%) had a good outcome. Poor outcome group had significantly lower phase coherence in the myogenic frequency interval III compared to good outcome group (0.36 ± 0.14 vs. 0.54 ± 0.18, P < 0.001). The predictive method using neuron-specific enolase (NSE) and interval III value demonstrated good discrimination (area under the curve 0.919; 95% confidence interval, 0.850-0.989).

CONCLUSIONS

The predictive method using NSE and phase coherence of HbO₂ in the interval III from the vascular smooth muscle cells could be a useful tool for prognosticating after CA. This suggests that evaluating cerebral ischemia using phase coherence of HbO₂ might be a helpful outcome predictor following CA.

Cervical spinal cord injury by a low-impact trauma as an unnoticed cause of cardiorespiratory arrest

Background

Cardiorespiratory arrest (CA) secondary to traumatic cervical spinal cord injury can occur in minor accidents with low-impact trauma and may be overlooked as the cause of CA in patients admitted in the coronary care unit.

Case summary

We present two patients admitted to the coronary care unit because of suspected CA of cardiac origin. Both patients were found in CA with asystole, one after collapsing in a shopping mall and falling down a few steps and the other in the street next to his bicycle. They underwent early pharmacologically induced coma and hypothermia precluding neurological examination. Both patients remained in coma after rewarming, with preserved brainstem reflexes but absent motor response to pain. One patient had post-anoxic myoclonus in the face without limb involvement. In both patients, median nerve somatosensory evoked potentials demonstrated bilateral absence of thalamocortical N19 responses and abnormal cervicomedullary junction potentials (N13 wave). Extensive diagnostic work-up did not find a cardiac cause of the CA, pulmonary thromboembolism, or intracranial haemorrhage. In both patients, cervical spinal cord injury was diagnosed incidentally 5 and 6 days after CA, when a brain magnetic resonance imaging performed to assess post-anoxic brain injuries detected spinal cord hyperintensities with fracture and luxation of the odontoid. Both patients died 11 and 8 days after CA.

Discussion

Low-impact traumatic cervical spinal cord injury should be considered in the diagnostic work-up of patients with CA of unknown cause.

Standardized EEG analysis to reduce the uncertainty of outcome prognostication after cardiac arrest

PURPOSE

Post-resuscitation guidelines recommend a multimodal algorithm for outcome prediction after cardiac arrest (CA). We aimed at evaluating the prevalence of indeterminate prognosis after application of this algorithm and providing a strategy for improving prognostication in this population.

METHODS

We examined a prospective cohort of comatose CA patients (n = 485) in whom the ERC/ESICM algorithm was applied. In patients with an indeterminate outcome, prognostication was investigated using standardized EEG classification (benign, malignant, highly malignant) and serum neuron-specific enolase (NSE). Neurological recovery at 3 months was dichotomized as good (Cerebral Performance Categories [CPC] 1-2) vs. poor (CPC 3-5).

RESULTS

Using the ERC/ESICM algorithm, 155 (32%) patients were prognosticated with poor outcome; all died at 3 months. Among the remaining 330 (68%) patients with an indeterminate outcome, the majority (212/330; 64%) showed good recovery. In this patient subgroup, absence of a highly malignant EEG by day 3 had 99.5 [97.4-99.9] % sensitivity for good recovery, which was superior to NSE < 33 μg/L (84.9 [79.3-89.4] % when used alone; 84.4 [78.8-89] % when combined with EEG, both p < 0.001). Highly malignant EEG had equal specificity (99.5 [97.4-99.9] %) but higher sensitivity than NSE for poor recovery. Further analysis of the discriminative power of outcome predictors revealed limited value of NSE over EEG.

CONCLUSIONS

In the majority of comatose CA patients, the outcome remains indeterminate after application of ERC/ESICM prognostication algorithm. Standardized EEG background analysis enables accurate prediction of both good and poor recovery, thereby greatly reducing uncertainty about coma prognostication in this patient population.

Prognostic role of EEG identical bursts in patients after cardiac arrest: Multimodal correlation

AIMS

EEG burst-suppression (BS) heralds poor outcome after cardiac arrest (CA). Within this pattern, identical bursts (IB) have been suggested to be absolutely specific, in isolation. We assessed IB prevalence and their added predictive value for poor outcome in a multimodal prognostic approach.

METHODS

We retrospectively analyzed a registry of comatose adults with CA (April 2011-February 2019), undergoing EEG at 5-36 h and 36-72 h. SB and IB were visually assessed. Cerebral Performance Categories (CPC) at 3 months were dichotomized as "good" (CPC 1-2), or "poor" (CPC 3-5). Sensitivity, specificity, positive, negative predictive values of BS and IB for poor outcome were calculated. A multimodal prognostic score was created assigning one point each to unreactive and epileptiform EEG, pupillary light reflex and SSEPs absence, NSE > 75 μg/l. In a second score, IB were added; predictive performances were compared using Receiver Operating Characteristic (ROC) curves.

RESULTS

Of 522 patients, 147 (28%) had BS in any EEG (10 [7%] had good outcome and 129 [88%] died). Of them, 53/147 (36%, 10% of total) showed IB, 47/53 (89%) of which within 36 h. IB were 100% specific for poor outcome, and associated with higher serum NSE than BS. However, there was no significant difference between the scores with and without IB for CPC 3-5 (p = 0.116).

CONCLUSION

IB occur in 10% of patients after CA. In our multimodal context, IB, albeit being very specific for poor outcome, seem redundant with other predictors.

Topography of MR lesions correlates with standardized EEG pattern in early comatose survivors after cardiac arrest

AIM

Multimodal prognostication in comatose patients after cardiac arrest (CA) is complicated by the fact that different modalities are usually not independent. Here we set out to systematically correlate early EEG and MRI findings.

METHODS

89 adult patients from a prospective register who underwent at least one EEG and one MRI in the acute phase after CA were included. The EEGs were characterized using pre-existent standardized categories (highly malignant, malignant, benign). For MRIs, the apparent diffusion coefficient (ADC) was computed in pre-defined regions. We then introduced a novel classification based on the topography of ADC reduction (MR-lesion pattern (MLP) 1: no lesion; MLP 2: purely cortical lesions; MLP 3: involvement of the basal ganglia; MLP 4 involvement of other deep grey matter regions).

RESULTS

EEG background reactivity and EEG background continuity were strongly associated with a lower MLP value (p < 0.001 and p = 0.003 respectively). The EEG categories highly malignant, malignant and benign were strongly correlated with the MLP values (rho = 0.46, p < 0.001).

CONCLUSION

The MRI lesions are highly correlated with the EEG pattern. Our results suggest that performing MRI in comatose patients after CA with either highly malignant or with a benign EEG pattern is unlikely to yield additional useful information for prognostication, and should therefore be performed in priority in patients with intermediate EEG patterns ("malignant pattern").

Corneal Reflex Testing in the Evaluation of a Comatose Patient: An Ode to Precise Semiology and Examination Skills

BACKGROUND/OBJECTIVE

The corneal reflex assesses the integrity of the trigeminal and facial cranial nerves. This brainstem reflex is fundamental in neuroprognostication after cardiac arrest and in brain death determination. We sought to investigate corneal reflex testing methods among neurologists and general critical care providers in the context of neuroprognostication following cardiac arrest.

METHODS

This is an international cross-sectional study disseminated to members of the Neurocritical Care Society, Society of Critical Care Medicine, and American Academy of Neurology. We utilized an open Web-based survey (Qualtrics^®, Provo, UT, USA) to disseminate 26 questions regarding neuroprognostication practices following cardiac arrest, in which 3 questions pertained to corneal reflex testing. Descriptive statistical measures were used, and subgroup analyses performed between neurologists and non-neurologists. Questions were not mandatory; therefore, the percentages were relative to the number of respondents for each question.

RESULTS

There were 959 respondents in total. Physicians comprised 85.1% of practitioners (762 out of 895), of which 55% (419) identified themselves as non-neurologists and 45% (343) as neurologists. Among physicians, 85.9% (608 out of 708) deemed corneal reflex relevant for prognostication following cardiac arrest (neurologists 84.4% versus non-neurologists 87.0%). A variety of techniques were employed for corneal reflex testing, the most common being "light cotton touch" (59.2%), followed by "cotton-tipped applicator with pressure" (23.9%), "saline or water squirt" (15.9%), and "puff of air" (1.0%). There were no significant differences in the methods for testing between neurologists and non-neurologists (p = 0.52). The location of stimulus application was variable, and 26.1% of physicians (148/567) apply the stimulus on the temporal conjunctiva rather than on the cornea itself.

CONCLUSIONS

Corneal reflex testing remains a cornerstone of the coma exam and is commonly used in neuroprognostication of unconscious cardiac arrest survivors and in brain death determination. A wide variability of techniques is noted among practitioners, including some that may provide suboptimal stimulation of corneal nerve endings. Imprecise testing in this setting may lead to inaccuracies in critical settings, which carries significant consequences such as guiding decisions of care limitations, misdiagnosis of brain death, and loss of public trust.

Prognostic Abilities of Serial Neuron-Specific Enolase and Lactate and their Combination in Cardiac Arrest Survivors During Targeted Temperature Management

This study aimed to determine the prognostic ability of serial neuron-specific enolase (NSE) and lactate in cardiac arrest survivors treated with targeted temperature management (TTM) and to investigate whether a combination of NSE and lactate could increase prognostic information. This observational, retrospective, cohort study was conducted between January 2013 and December 2018; data were extracted from an out-of-hospital cardiac arrest registry. We collected serial serum NSE and lactate levels during TTM. The primary endpoint was poor neurological outcome at 28 days from cardiac arrest. Of all 160 included patients, 98 (61.3%) had poor neurological outcomes. Areas under the curves (AUCs) for NSE were 0.797, 0.871, and 0.843 at 24, 48, and 72 h, respectively (all p < 0.05). AUCs for lactate were 0.669, 0.578, 0.634, and 0.620 at 0, 24, 48, and 72 h, respectively (all p < 0.05). Although the combination of initial lactate and NSE at 48 h yielded the highest discovered AUC (0.877) it was not statistically different from that for the 48 h NSE alone (p = 0.692). During the TTM, NSE at 48 h from cardiac arrest was the most robust prognostic marker in comatose cardiac arrest survivors. However, a combination of the 48 h NSE with lactate did not increase the prognostic information.

Brainstem dysfunction in critically ill patients

The brainstem conveys sensory and motor inputs between the spinal cord and the brain, and contains nuclei of the cranial nerves. It controls the sleep-wake cycle and vital functions via the ascending reticular activating system and the autonomic nuclei, respectively. Brainstem dysfunction may lead to sensory and motor deficits, cranial nerve palsies, impairment of consciousness, dysautonomia, and respiratory failure. The brainstem is prone to various primary and secondary insults, resulting in acute or chronic dysfunction. Of particular importance for characterizing brainstem dysfunction and identifying the underlying etiology are a detailed clinical examination, MRI, neurophysiologic tests such as brainstem auditory evoked potentials, and an analysis of the cerebrospinal fluid. Detection of brainstem dysfunction is challenging but of utmost importance in comatose and deeply sedated patients both to guide therapy and to support outcome prediction. In the present review, we summarize the neuroanatomy, clinical syndromes, and diagnostic techniques of critical illness-associated brainstem dysfunction for the critical care setting.

Interobserver Variability in the Recognition of Hypoxic-Ischemic Brain Injury on Computed Tomography Soon After Out-of-Hospital Cardiac Arrest

BACKGROUND

Cerebral edema and loss of gray-white matter differentiation on head computed tomography (CT) after cardiac arrest generally portend a poor prognosis. The interobserver variability in physician recognition of hypoxic-ischemic brain injury (HIBI) on early CT after out-of-hospital cardiac arrest has not been studied.

METHODS

In this survey study, participating physicians and a neuroradiologist reviewed 20 randomly selected head CTs obtained within 2 h of out-of-hospital cardiac arrest and decided if HIBI was present. All participants were blinded to clinical details. Interobserver agreement on the presence of HIBI (primary outcome) and pairwise agreement between participants and the neuroradiologist (secondary outcome) were determined using multi- and dual-rater kappa statistics with 95% confidence intervals (CIs).

RESULTS

Agreement among physicians regarding the presence of HIBI on head CT was fair (kappa 0.34; 95% CI 0.19-0.49). Individual physician agreement with the neuroradiologist varied from poor to moderate (kappa 0.0-0.48), with 8 of 10 physicians having no more than fair agreement. Regarding the perceived severity of HIBI on head CT, physician agreement was moderate (ICC = 0.56; 95% CI 0.38-0.77).

CONCLUSION

Physicians, including radiologists, demonstrated substantial interobserver variability when identifying HIBI on head CT soon after out-of-hospital cardiac arrest.

Serum neuron-specific enolase measurement for neuro-prognostication post out-of-hospital cardiac arrest: Determination of the optimum testing strategy in routine clinical use

Background

Measurement of serum neuron-specific enolase (NSE) for neuro-prognostication post out-of-hospital cardiac arrest (OHCA) is recommended by international guidelines. There is, however, a lack of consensus regarding the cut-offs and time points to use. In addition, NSE is particularly susceptible to haemolysis interference. This study aimed to define the optimum NSE testing strategy to support the intensive care unit (ICU).

Methods

Patients admitted to ICU post-OHCA over 16 months had NSE measured. The outcome was survival to ICU discharge. NSE at 0 h, 24 h, 48 h, 72 h and change in NSE (ΔNSE) were assessed for prognostic accuracy using receiver operator characteristic curve analysis. The magnitude of haemolysis interference was quantified by spiking haemolysate into paired serum.

Results

There is a consistent linear increase in NSE with increasing haemolysis, independent of baseline NSE concentration. A haemolysis index acceptance threshold was defined as 20. There were 142 patients, and 82 survived to ICU discharge. The NSE parameter with best predictive performance was ΔNSE at 48 h, which had an area under the receiver operator characteristic curve of 0.91. A cut-off of >0 μg/L at this time point had sensitivity of 80% and specificity of 97% for predicting death on ICU. When patients who died of non-neurological causes were removed, the sensitivity increased to 91%.

Conclusions

Application of a stringent haemolysis interference threshold and measurement of NSE at two time points enabled us to achieve excellent discrimination. Increasing NSE over the first 48 h, suggestive of an ongoing reperfusion injury to the brain, is a strong predictor of poor outcome.

Neurological Pupil index for Early Prognostication After Venoarterial Extracorporeal Membrane Oxygenation

BACKGROUND

Venoarterial extracorporeal membrane oxygenation therapy (VA-ECMO) after refractory cardiogenic shock or cardiac arrest has significant morbidity and mortality. Early outcome prediction is crucial in this setting, but data on neuroprognostication are limited. We examined the prognostic value of clinical neurologic examination, using an automated device for the quantitative measurement of pupillary light reactivity.

METHODS

An observational cohort of sedated, mechanically ventilated VA-ECMO patients was analyzed during the early phase after ECMO insertion (first 72 h). Using the NPi-200 automated infrared pupillometer, pupillary light reactivity was assessed repeatedly (every 12 h) by calculating the Neurological Pupil index (NPi). Trends of NPi over time were correlated to 90-day mortality, and the prognostic performance of the NPi, alone and in combination with the 12-h PREDICT VA-ECMO score, was evaluated.

RESULTS

One hundred consecutive patients were studied (51 with refractory cardiogenic shock and 49 with refractory cardiac arrest; 12-h PREDICT VA-ECMO, 40%; observed 90-day survival, 43%). Nonsurvivors (n = 57) had significantly lower NPi than did survivors at all time points (all P < .01). Abnormal NPi (< 3, at any time from 24 to 72 h) was 100% specific for 90-day mortality, with 0% false positives. Adding the 12-h PREDICT VA-ECMO score to the NPi provided the best prognostic performance (specificity, 100% [95% CI, 92%-100%]; sensitivity, 60% [95% CI, 46%-72%]; area under the receiver operating characteristic curve, 0.82).

CONCLUSIONS

Quantitative NPi alone had excellent ability to predict a poor outcome from day 1 after VA-ECMO insertion, with no false positives. Combining NPi and 12-h PREDICT-VA ECMO score increased the sensitivity of outcome prediction, while maintaining 100% specificity.

Identifying neuronal correlates of dying and resuscitation in a model of reversible brain anoxia

We developed a new rodent model of reversible brain anoxia and performed continuous electrocorticographic (ECoG) and intracellular recordings of neocortical neurons to identify in real-time the cellular and network dynamics that successively emerge throughout the dying-to-recovery process. Along with a global decrease in ECoG amplitude, deprivation of oxygen supply resulted in an early surge of beta-gamma activities, accompanied by rhythmic membrane depolarizations and regular firing in pyramidal neurons. ECoG and intracellular signals were then dominated by low-frequency activities which progressively declined towards isoelectric levels. Cortical neurons during the isoelectric state underwent a massive membrane potential depolarizing shift, captured in the ECoG as a large amplitude triphasic wave known as the "wave-of-death" (WoD). This neuronal anoxic depolarization, associated with a block of action potentials and a loss of cell integrative properties, could however be reversed if brain re-oxygenation was rapidly restored (within 2-3.5 min). The subsequent slow repolarization of neocortical neurons resulted in a second identifiable ECoG wave we termed "wave-of-resuscitation" since it inaugurated the progressive regaining of pre-anoxic synaptic and firing activities. These results demonstrate that the WoD is not a biomarker of an irremediable death and unveil the cellular correlates of a novel ECoG wave that may be predictive of a successful recovery. The identification of real-time biomarkers of onset and termination of cell anoxic insult could benefit research on interventional strategies to optimize resuscitation procedures.

Serum neurofilament light chain as a prognostic marker in postanoxic encephalopathy

Functional outcome in patients with postanoxic encephalopathy after cardiac arrest (CA) often remains unclear, and there is a strong need of new prognostication measures. We aimed at investigating serum neurofilament light (NfL) chain concentration in patients with a postanoxic encephalopathy after CA and its prognostic potential. Serum samples were prospectively collected at different time points after CA in consecutive patients admitted to the intensive care unit (ICU) of Ticino Cardiocentre (Lugano, Switzerland) between June 2017 and March 2018. Serum NfL concentration was measured using a single molecule array (SIMOA) assay. The association of NfL levels with time to return of spontaneous circulation (ROSC), serum neuronal specific enolase (NSE) concentration, time between CA and sample collection, electroencephalogram (EEG) pattern and clinical outcome (death status at one month) were explored. Fourteen patients experiencing 15 CAs were included in the study (median age = 58 (57-68) years, 8 males). Median serum NfL concentration was 1027.0 (25.5-6033.7) pg/ml. There were positive associations between serum NfL and time to ROSC (rho = 0.60, p < 0.0001), NSE concentration (rho = 0.76, p < 0.0001), and severity of brain damage as estimated by EEG, with the highest concentrations measured in patients with suppressed electrical activity (14,954.0 [9006.0-25,364.0] pg/ml). Neurofilament light concentration remained high in samples collected up to 17 days after CA. Median NfL levels were higher among dead than alive patients at one month (6401.7 [3768.5-15,573.3] vs 25.5 [25.2-75.4] pg/ml). High NfL levels performed better than NSE in predicting death status at one month (NfL area under the curve (AUC) = 0.98, 95% confidence interval (CI) = 0.94-1.00; NSE AUC = 0.80, 95% CI = 0.67-0.94). These results support the potential inclusion of serum NfL in the battery of prognostication measures to be used in patients with postanoxic encephalopathy in ICU settings. This article is part of the Special Issue "Proceedings of the 7th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures".

Neurological outcome of postanoxic refractory status epilepticus after aggressive treatment

Refractory status epilepticus (RSE) occurs in up to 30% of patients following resuscitation after cardiac arrest. The impact of aggressive treatment of postanoxic RSE on long-term neurological outcome remains uncertain. We investigated neurological outcome of cardiac arrest patients with RSE treated with a standardized aggressive protocol with antiepileptic drugs and anesthetics, compared with patients with other electroencephalographic (EEG) patterns. A prospective cohort of 166 consecutive patients with cardiac arrest in coma was stratified according to four independent EEG patterns (benign; RSE; generalized periodic discharges (GPDs); malignant nonepileptiform) and multimodal prognostic indicators. Primary outcomes were survival and cerebral performance category (CPC) at 6 months. Refractory status epilepticus occurred in 36 patients (21.7%) and was treated with an aggressive standardized protocol as long as multimodal prognostic indicators were not unfavorable. Refractory status epilepticus started after 3 ± 2.3 days after cardiac arrest and lasted 4.7 ± 4.3 days. A benign electroencephalographic patterns was recorded in 76 patients (45.8%), a periodic pattern (GPDs) in 13 patients (7.8%), and a malignant nonepileptiform EEG pattern in 41 patients (24.7%). The four EEG patterns were highly associated with different prognostic indicators (low flow time, clinical motor seizures, N20 responses, neuron-specific enolase (NSE), neuroimaging). Survival and good neurological outcome (CPC 1 or 2) at 6 months were 72.4% and 71.1% for benign EEG pattern, 54.3% and 44.4% for RSE, 15.4% and 0% for GPDs, and 2.4% and 0% for malignant nonepileptiform EEG pattern, respectively. Aggressive and prolonged treatment of RSE may be justified in cardiac arrest patients with favorable multimodal prognostic indicators. This article is part of the Special Issue "Proceedings of the 7th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures".

Serum Neurofilament Light Chain for Prognosis of Outcome After Cardiac Arrest

Importance

Prognostication of neurologic outcome after cardiac arrest is an important but challenging aspect of patient therapy management in critical care units.

Objective

To determine whether serum neurofilament light chain (NFL) levels can be used for prognostication of neurologic outcome after cardiac arrest.

Design, Setting and Participants

Prospective clinical biobank study of data from the randomized Target Temperature Management After Cardiac Arrest trial, an international, multicenter study with 29 participating sites. Patients were included between November 11, 2010, and January 10, 2013. Serum NFL levels were analyzed between August 1 and August 23, 2017, after trial completion. A total of 782 unconscious patients with out-of-hospital cardiac arrest of presumed cardiac origin were eligible.

Exposures

Serum NFL concentrations analyzed at 24, 48, and 72 hours after cardiac arrest with an ultrasensitive immunoassay.

Main Outcomes and Measures

Poor neurologic outcome at 6-month follow-up, defined according to the Cerebral Performance Category Scale as cerebral performance category 3 (severe cerebral disability), 4 (coma), or 5 (brain death).

Results

Of 782 eligible patients, 65 patients (8.3%) were excluded because of issues with aliquoting, missing sampling, missing outcome, or transport problems of samples. Of the 717 patients included (91.7%), 580 were men (80.9%) and median (interquartile range [IQR]) age was 65 (56-73) years. A total of 360 patients (50.2%) had poor neurologic outcome at 6 months. Median (IQR) serum NFL level was significantly increased in the patients with poor outcome vs good outcome at 24 hours (1426 [299-3577] vs 37 [20-70] pg/mL), 48 hours (3240 [623-8271] vs 46 [26-101] pg/mL), and 72 hours (3344 [845-7838] vs 54 [30-122] pg/mL) (P < .001 at all time points), with high overall performance (area under the curve, 0.94-0.95) and high sensitivities at high specificities (eg, 69% sensitivity with 98% specificity at 24 hours). Serum NFL levels had significantly greater performance than the other biochemical serum markers (ie, tau, neuron-specific enolase, and S100). At comparable specificities, serum NFL levels had greater sensitivity for poor outcome compared with routine electroencephalogram, somatosensory-evoked potentials, head computed tomography, and both pupillary and corneal reflexes (ranging from 29.2% to 49.0% greater for serum NFL level).

Conclusions and Relevance

Findings from this study suggest that the serum NFL level is a highly predictive marker of long-term poor neurologic outcome at 24 hours after cardiac arrest and may be a useful complement to currently available neurologic prognostication methods.

The Influence of Therapeutics on Prognostication After Cardiac Arrest

PURPOSE OF REVIEW

The goal of this review is to highlight the influence of therapeutic maneuvers on neuro-prognostication measures administered to comatose survivors of cardiac arrest. We focus on the effect of sedation regimens in the setting of targeted temperature management (TTM), one of the principle interventions known to improve neurological recovery after cardiac arrest. Further, we discuss the critical need for novel markers, as well as refinement of existing markers, among patients receiving extracorporeal membrane oxygenation (ECMO) in the setting of failed conventional resuscitation, known as extracorporeal cardiopulmonary resuscitation (ECPR).

RECENT FINDINGS

Automated pupillometry may have some advantage over standard pupillary examination for prognostication following TTM, sedation, or the use of ECMO after cardiac arrest. New serum biomarkers such as Neurofilament light chain have shown good predictive abilities and need further validation in these populations. There is a high-level uncertainty in brain death declaration protocols particularly related to apnea testing and appropriate ancillary tests in patients receiving ECMO. Both sedation and TTM alone and in combination have been shown to affect prognostic markers to varying degrees. The optimal approach to analog-sedation is unknown, and requires further study. Moreover, validation of known prognostic markers, as well as brain death declaration processes in patients receiving ECMO is warranted. Data on the effects of TTM, sedation, and ECMO on biomarkers (e.g., neuron-specific enolase) and electrophysiology measures (e.g., somatosensory-evoked potentials) is sparse. The best approach may be one customized to the individual patient, a precision-medicine approach.

A multimodal approach using somatosensory evoked potentials for prognostication in hypoglycemic encephalopathy

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Hypoglycemic encephalopathy may be associated with poor neurological prognosis.

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Little data exists to guide prognostication in hypoglycemic encephalopathy.

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We describe a multimodal approach to prognostication in hypoglycemia.

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MRI, EEG, and SSEPs estimate severity of brain injury in hypoglycemic coma.

Objectives

We present a case of a patient with hypoglycemic encephalopathy with loss of median nerve N20 somatosensory evoked potentials (SSEPs) and describe our multimodal approach to prognostication in hypoglycemic encephalopathy.

Case

The patient was a 67-year-old woman with type 2 diabetes and stage 5 chronic kidney disease hospitalized for hypoglycemic encephalopathy. SSEPs showed bilateral absence of the median nerve N20 response. She ultimately suffered a poor outcome.

Discussion

There are no high-quality evidence-based clinical, neurophysiologic, or imaging studies available to aid in neurologic outcome prediction in hypoglycemic encephalopathy. In our practice we use a multimodal approach to neurologic prognostication, similar to that used in coma after cardiac arrest that includes SSEPs, EEG, and brain MRI, which enables an estimate of the severity of brain injury. As the literature is largely based on small studies or case reports, and is extrapolated from the cardiac arrest literature, we caution against early prognostication and disposition including the withdrawal of care, to avoid a self-fulfilling prophecy.

Nonconvulsive seizures and nonconvulsive status epilepticus in the neuro ICU should or should not be treated aggressively: A debate

This article presents a "debate" about the appropriate level of aggressiveness of treatment for nonconvulsive status epilepticus (NCSE), held at the International Congress of Clinical Neurophysiology in Washington D.C. on 4 May 2018. The proposition for discussion was "Nonconvulsive seizures and status epilepticus in the intensive care unit should be treated aggressively." Dr. Andrea O. Rossetti from Lausanne, Switzerland, spoke in support of the proposition and Dr. Lawrence J. Hirsch from New Haven, Connecticut, discussed reasons for rejecting the proposal. Dr. Frank W. Drislane from Boston, Massachusetts, was asked by the conference organizers to add comments and perspective.

Predictive performance of plasma neutrophil gelatinase-associated lipocalin for neurologic outcomes in out-of-hospital cardiac arrest patients treated with targeted temperature management: A prospective observational study

Few studies have demonstrated the prognostic potential of neutrophil gelatinase-associated lipocalin (NGAL) in post-cardiac arrest patients. This study evaluated the usefulness of plasma NGAL in predicting neurologic outcome and mortality in out-of-hospital cardiac arrest (OHCA) patients treated with targeted temperature management (TTM). A prospective observational study was conducted between October 2013 and April 2016 at a single tertiary hospital. We enrolled 75 patients treated with TTM and collected their demographic data, cardiopulmonary resuscitation-related information, data on plasma NGAL concentration, and prognostic test results. Plasma NGAL was measured at 4 hours after return of spontaneous circulation (ROSC). The primary endpoint was the neurologic outcome at discharge and the secondary outcome was 28-day mortality. Neurologic outcomes were analyzed using a stepwise multivariate logistic regression while 28-day mortality was analyzed using a stepwise Cox regression. The predictive performance of plasma NGAL for neurologic outcome was measured by the area under the receiver operating characteristic curve and the predictability of 28-day mortality was measured using Harrell C-index. We also compared the predictive performance of plasma NGAL to that of other traditional prognostic modalities for outcome variables. Thirty patients (40%) had good neurologic outcomes and 53 (70.7%) survived for more than 28 days. Plasma NGAL in patients with good neurologic outcomes was 122.7 ± 146.7 ng/ml, which was significantly lower than that in the poor neurologic outcome group (307.5 ± 269.6 ng/ml; P < .001). The probability of a poor neurologic outcome was more than 3.3-fold in the NGAL >124.3 ng/ml group (odds ratio, 3.321; 95% confidence interval [CI], 1.265-8.721]). Plasma NGAL in the survived group was significantly lower than that in the non-survived group (172.7 ± 191.6 vs 379.9 ± 297.8 ng/ml; P = .005). Plasma NGAL was significantly correlated with 28-day mortality (hazard ratio 1.003, 95% CI 1.001-1.004; P < .001). The predictive performance of plasma NGAL was not inferior to that of other prognostic modalities except electroencephalography. Plasma NGAL is valuable for predicting the neurologic outcome and 28-day mortality of patients with OHCA at an early stage after ROSC.This study was registered at ClinicalTrials.gov on November 19, 2013 (Identifier: NCT01987466).

EEG-based outcome prediction after cardiac arrest with convolutional neural networks: Performance and visualization of discriminative features

Prognostication for comatose patients after cardiac arrest is a difficult but essential task. Currently, visual interpretation of electroencephalogram (EEG) is one of the main modality used in outcome prediction. There is a growing interest in computer-assisted EEG interpretation, either to overcome the possible subjectivity of visual interpretation, or to identify complex features of the EEG signal. We used a one-dimensional convolutional neural network (CNN) to predict functional outcome based on 19-channel-EEG recorded from 267 adult comatose patients during targeted temperature management after CA. The area under the receiver operating characteristic curve (AUC) on the test set was 0.885. Interestingly, model architecture and fine-tuning only played a marginal role in classification performance. We then used gradient-weighted class activation mapping (Grad-CAM) as visualization technique to identify which EEG features were used by the network to classify an EEG epoch as favorable or unfavorable outcome, and also to understand failures of the network. Grad-CAM showed that the network relied on similar features than classical visual analysis for predicting unfavorable outcome (suppressed background, epileptiform transients). This study confirms that CNNs are promising models for EEG-based prognostication in comatose patients, and that Grad-CAM can provide explanation for the models' decision-making, which is of utmost importance for future use of deep learning models in a clinical setting.

Outcome prediction of out-of-hospital cardiac arrest with presumed cardiac aetiology using an advanced machine learning technique

BACKGROUND

Outcome prediction for patients with out-of-hospital cardiac arrest (OHCA) has the possibility to detect patients who could have been potentially saved. Advanced machine learning techniques have recently been developed and employed for clinical studies. In this study, we aimed to establish a prognostication model for OHCA with presumed cardiac aetiology using an advanced machine learning technique.

METHODS AND RESULTS

Cohort data from a prospective multi-centre cohort study for OHCA patients transported by an ambulance in the Kanto area of Japan between January 2012 and March 2013 (SOS-KANTO 2012 study) were analysed in this study. Of 16,452 patients, data for OHCA patients aged ≥18 years with presumed cardiac aetiology were retrieved, and were divided into two groups (training set: n = 5718, between January 1, 2012 and December 12, 2012; test set: n = 1608, between January 1, 2013 and March 31, 2013). Of 421 variables observed during prehospital and emergency department settings, 35 prehospital variables, or 35 prehospital and 18 in-hospital variables, were used for outcome prediction of 1-year survival using a random forest method. In validation using the test set, prognostication models trained with 35 variables, or 53 variables for 1-year survival showed area under the receiver operating characteristics curve (AUC) values of 0.943 (95% CI [0.930, 0.955]) and 0.958 (95% CI [0.948, 0.969]), respectively.

CONCLUSIONS

The advanced machine learning technique showed favourable prediction capability for 1-year survival of OHCA with presumed cardiac aetiology. These models can be useful for detecting patients who could have been potentially saved.

[Postcardiac arrest treatment guide]

BACKGROUND

Treatment after cardiac arrest has become more complex and interdisciplinary over the last few years. Thus, the clinically active intensive and emergency care physician not only has to carry out the immediate care and acute diagnostics, but also has to prognosticate the neurological outcome.

AIM

The different, most important steps are presented by leading experts in the area, taking into account the interdisciplinarity and the currently valid guidelines.

MATERIALS AND METHODS

Attention was paid to a concise, practice-oriented presentation.

RESULTS AND DISCUSSION

The practical guide contains all important steps from the acute care to the neurological prognosis generation that are relevant for the clinically active intensive care physician.

Spectral Content of Electroencephalographic Burst-Suppression Patterns May Reflect Neuronal Recovery in Comatose Post-Cardiac Arrest Patients

PURPOSE

To assess the potential biologic significance of variations in burst-suppression patterns (BSPs) after cardiac arrest in relation to recovery of consciousness. In the context of recent theoretical models of BSP, bursting frequency may be representative of underlying network dynamics; discontinuous activation of membrane potential during impaired cellular energetics may promote neuronal rescue.

METHODS

We reviewed a database of 73 comatose post-cardiac arrest patients who underwent therapeutic hypothermia to assess for the presence of BSP and clinical outcomes. In a subsample of patients with BSP (n = 14), spectral content of burst and suppression periods were quantified using multitaper method.

RESULTS

Burst-suppression pattern was seen in 45/73 (61%) patients. Comparable numbers of patients with (31.1%) and without (35.7%) BSP regained consciousness by the time of hospital discharge. In addition, in two unique cases, BSP initially resolved and then spontaneously reemerged after completion of therapeutic hypothermia and cessation of sedative medications. Both patients recovered consciousness. Spectral analysis of bursts in all patients regaining consciousness (n = 6) showed a prominent theta frequency (5-7 Hz) feature, but not in age-matched patients with induced BSP who did not recover consciousness (n = 8).

CONCLUSIONS

The prognostic implications of BSP after hypoxic brain injury may vary based on the intrinsic properties of the underlying brain state itself. The presence of theta activity within bursts may index potential viability of neuronal networks underlying recovery of consciousness; emergence of spontaneous BSP in some cases may indicate an innate neuroprotective mechanism. This study highlights the need for better characterization of various BSP patterns after cardiac arrest.

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

Electroencephalography-based power spectra allow coma outcome prediction within 24 h of cardiac arrest

BACKGROUND

Outcome prediction in comatose patients following cardiac arrest remains challenging. Here, we assess the predictive performance of electroencephalography-based power spectra within 24 h from coma onset.

METHODS

We acquired electroencephalography (EEG) from comatose patients (n = 138) on the first day of coma in four hospital sites in Switzerland. Outcome was categorised as favourable or unfavourable based on the best state within three months. Data were split in training and test sets. We evaluated the predictive performance of EEG power spectra for long term outcome and its added value to standard clinical tests.

RESULTS

Out of 138 patients, 80 had a favourable outcome. Power spectra comparison between favourable and unfavourable outcome in the training set yielded significant differences at 5.2-13.2 Hz and above 21 Hz. Outcome prediction based on power at 5.2-13.2 Hz was accurate in training and test sets. Overall, power spectra predicted patients' outcome with maximum specificity and positive predictive value: 1.00 (95% with CI: 0.94-1.00 and 0.89-1.00, respectively). The combination of power spectra and reactivity yielded better accuracy and sensitivity (0.81, 95% CI: 0.71-0.89) than prediction based on power spectra alone.

CONCLUSIONS

On the first day of coma following cardiac arrest, low power spectra values around 10 Hz, typically linked to impaired cortico-thalamic structural connections, are highly specific of unfavourable outcome. Peaks in this frequency range can predict long-term outcome.

Update in Neurocritical Care: a summary of the 2018 Paris international conference of the French Society of Intensive Care

The 2018 Paris Intensive Care symposium entitled "Update in Neurocritical Care" was organized in Paris, June 21-22, 2018, under the auspices of the French Intensive Care Society. This 2-day post-graduate educational symposium comprised several chapters, aiming first to provide all-board intensivists with current standards for the clinical assessment of altered consciousness states (including coma and delirium) and peripheral nervous system in critically ill patients, monitoring of brain function (specifically, electro-encephalography) and best practices for sedation-analgesia-delirium management. An update on the treatment of specific severe brain pathologies-including ischaemic/haemorrhagic stroke, cerebral venous thrombosis, hypoxic-ischaemic brain injury, immune-mediated and infectious encephalitis and refractory status epilepticus-was also provided. Finally, we discuss how to approach some difficult decisions, namely the role of decompressive craniectomy and prognostication models in patients with head injury. For each chapter, the scope of the present review was to provide important issues and key messages, provide most recent and relevant literature in the field, and briefly describe new developments in the field.

Risk factors for progression toward brain death after out-of-hospital cardiac arrest

BACKGROUND

Successfully resuscitated out-of-hospital cardiac arrest (OHCA) may lead to brain death (BD) and good-quality transplantable organs. We aimed to determine risk factors for evolution toward BD after OHCA. We analyzed adult patients admitted to an intensive care unit (ICU) who survived at least 24 h after an OHCA between 2005 and 2015. BD was defined according to international guidelines. Multivariate logistic regression was used to identify potential risk factors for BD available 24 h after OHCA.

RESULTS

A total of 214 patients were included (median age 68 years; sex ratio 1.25; non-shockable OHCA: 88%). Among these, 42 (19.6%) developed BD, while 22 (10.3%) were alive at 1 year with a good neurological outcome. Independent risk factors for BD were age (OR per year 0.95; 95% CI [0.92-0.98]), female gender (OR 2.34; 95% CI [1.02-5.35]), neurological cause of OHCA (OR 14.72; 95% CI [3.03-71.37]), duration of the low-flow period > 16 min (OR 2.94, 95% CI [1.21-7.16]) and need of vasoactive drugs at 24 h (OR 6.20, 95% CI [2.41-15.93]).

CONCLUSIONS

The study identified, in a population of OHCA with predominantly non-shockable initial rhythms, five simple risk factors independently associated with progression toward BD.

Death after awakening from post-anoxic coma: the "Best CPC" project

BACKGROUND

In patients who recover consciousness after cardiac arrest (CA), a subsequent death from non-neurological causes may confound the assessment of long-term neurological outcome. We investigated the prevalence and causes of death after awakening (DAA) in a multicenter cohort of CA patients.

METHODS

Observational multicenter cohort study on patients resuscitated from CA in eight European intensive care units (ICUs) from January 2007 to December 2014. DAA during the hospital stay was extracted retrospectively from patient medical records. Demographics, comorbidities, initial CA characteristics, concomitant therapies, prognostic tests (clinical examination, electroencephalography (EEG), somatosensory evoked potentials (SSEPs)), and cause of death were identified.

RESULTS

From a total 4646 CA patients, 2478 (53%) died in-hospital, of whom 196 (4.2%; ranges 0.6-13.0%) had DAA. DAA was less frequent among out-of-hospital than in-hospital CA (82/2997 [2.7%] vs. 114/1649 [6.9%]; p < 0.001). Median times from CA to awakening and from awakening to death were 2 [1-5] and 9 [3-18] days, respectively. The main causes of DAA were multiple organ failure (n = 61), cardiogenic shock (n = 61), and re-arrest (n = 26). At day 3 from admission, results from EEG (n = 56) and SSEPs (n = 60) did not indicate poor outcome.

CONCLUSIONS

In this large multicenter cohort, DAA was observed in 4.2% of non-survivors. Information on DAA is crucial since it may influence epidemiology and the design of future CA studies evaluating neuroprognostication and neuroprotection.

Neuron-specific enolase kinetics: an additional tool for neurological prognostication after cardiac arrest

INTRODUCTION AND OBJECTIVES

To analyze neuron-specific enolase (NSE) kinetics as a prognostic biomarker of neurological outcome in cardiac arrest survivors treated with targeted temperature management.

METHODS

We performed a retrospective analysis of patients resuscitated from in- or out-of-hospital cardiac arrest admitted from September 2006 to May 2018 in a single tertiary care center and cooled to 32°C to 34°C for 24 hours. Blood samples for measurement of NSE values were drawn at hospital admission and at 24, 48, and 72hours after return of spontaneous circulation (ROSC). Neurological outcome was evaluated by means of the Cerebral Performance Category (CPC) score at 3 months and was characterized as good (CPC 1-2) or poor (CPC 3-5).

RESULTS

Of 451 patients, 320 fulfilled the inclusion criteria and were analyzed (80.3% male, mean age 61±14.1 years). Among these, 174 patients (54.4%) survived with good neurological status. Poor outcome patients had higher median NSE values at hospital admission and at 24, 48 and 72 hours after ROSC. At 48 and 72 hours after ROSC, NSE predicted poor neurological outcome with areas under the receiver-operating characteristic curves of 0.85 (95%CI, 0.81-0.90) and 0.88 (95%CI, 0.83-0.93), respectively. In addition, delta NSE values between 72hours after ROSC and hospital admission predicted poor neurological outcome with an area under the receiver-operating characteristic curve of 0.90 (95%CI, 0.85-0.95) and was an independent predictor of unfavorable outcome on multivariate analysis (P <.001).

CONCLUSIONS

In cardiac arrest survivors treated with targeted temperature management, delta NSE values between 72 hours after ROSC and hospital admission strongly predicted poor neurological outcome.