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BACKGROUND: Electroencephalography (EEG) findings following cardiovascular collapse in death are uncertain. We aimed to characterize EEG changes immediately preceding and following cardiac death. METHODS: We retrospectively analyzed EEGs of patients who died from cardiac arrest while undergoing standard EEG monitoring in an intensive care unit. Patients with brain death preceding cardiac death were excluded. Three events during fatal cardiovascular failure were investigated: (1) last recorded QRS complex on electrocardiogram (QRS(0)), (2) cessation of cerebral blood flow (CBF(0)) estimated as the time that blood pressure and heart rate dropped below set thresholds, and (3) electrocerebral silence on EEG (EEG(0)). We evaluated EEG spectral power, coherence, and permutation entropy at these time points. RESULTS: Among 19 patients who died while undergoing EEG monitoring, seven (37%) had a comfort-measures-only status and 18 (95%) had a do-not-resuscitate status in place at the time of death. EEG(0) occurred at the time of QRS(0) in five patients and after QRS(0) in two patients (cohort median − 2.0, interquartile range − 8.0 to 0.0), whereas EEG(0) was seen at the time of CBF(0) in six patients and following CBF(0) in 11 patients (cohort median 2.0 min, interquartile range − 1.5 to 6.0). After CBF(0), full-spectrum log power (p < 0.001) and coherence (p < 0.001) decreased on EEG, whereas delta (p = 0.007) and theta (p = 0.007) permutation entropy increased. CONCLUSIONS: Rarely may patients have transient electrocerebral activity following the last recorded QRS (less than 5 min) and estimated cessation of cerebral blood flow. These results may have implications for discussions around cardiopulmonary resuscitation and organ donation.

Status epilepticus (SE) is a neurologic emergency with high morbidity and mortality. The assessment of a patient’s prognosis is crucial in making treatment decisions. In this review, we discuss various markers that have been used to prognosticate SE in terms of recurrence, mortality, and functional outcome. These markers include demographic, clinical, electrophysiological, biochemical, and structural data. The heterogeneity of SE etiology and semiology renders development of prognostic markers challenging. Currently, prognostication in SE is limited to a few clinical scores. Future research should integrate clinical, genetic and epigenetic, metabolic, inflammatory, and structural biomarkers into prognostication models to approach “personalized medicine” in prognostication of outcomes after SE.

Recovery trajectories of clinically unresponsive patients with acute brain injury are largely uncertain. Brain activation in the absence of a behavioural response to spoken motor commands can be detected by EEG, also known as cognitive-motor dissociation. We aimed to explore the role of cognitive-motor dissociation in predicting time to recovery in patients with acute brain injury.In this observational cohort study, we prospectively studied two independent cohorts of clinically unresponsive patients (aged ≥18 years) with acute brain injury. Machine learning was applied to EEG recordings to diagnose cognitive-motor dissociation by detecting brain activation in response to verbal commands. Survival statistics and shift analyses were applied to the data to identify an association between cognitive-motor dissociation and time to and magnitude of recovery. The prediction accuracy of the model that was built using the derivation cohort was assessed using the validation cohort. Functional outcomes of all patients were assessed with the Glasgow Outcome Scale-Extended (GOS-E) at hospital discharge and at 3, 6, and 12 months after injury. Patients who underwent withdrawal of life-sustaining therapies were censored, and death was treated as a competing risk.Between July 1, 2014, and Sept 30, 2021, we screened 598 patients with acute brain injury and included 193 (32%) patients, of whom 100 were in the derivation cohort and 93 were in the validation cohort. At 12 months, 28 (15%) of 193 unresponsive patients had a GOS-E score of 4 or above. Cognitive-motor dissociation was seen in 27 (14%) patients and was an independent predictor of shorter time to good recovery (hazard ratio 5·6 [95% CI 2·5-12·5]), as was underlying traumatic brain injury or subdural haematoma (4·4 [1·4-14·0]), a Glasgow Coma Scale score on admission of greater than or equal to 8 (2·2 [1·0-4·7]), and younger age (1·0 [1·0-1·1]). Among patients discharged home or to a rehabilitation setting, those diagnosed with cognitive-motor dissociation consistently had higher scores on GOS-E indicating better functional recovery compared with those without cognitive-motor dissociation, which was seen as early as 3 months after the injury (odds ratio 4·5 [95% CI 2·0-33·6]).Recovery trajectories of clinically unresponsive patients diagnosed with cognitive-motor dissociation early after brain injury are distinctly different from those without cognitive-motor dissociation. A diagnosis of cognitive-motor dissociation could inform the counselling of families of clinically unresponsive patients, and it could help clinicians to identify patients who will benefit from rehabilitation.US National Institutes of Health.

Disorder of consciousness (DOC) is common in patients with acute brain injury (ABI) and it weighs heavily in goals of care discussion.1 Dopaminergic agents to support recovery have shown encouraging results in chronic DOC following traumatic brain injury (TBI) and are currently the most promising candidates to also support recovery during the acute post injury phase.2 Amantadine is a neurohormonal modulator that increases the concentration of dopamine at the synaptic cleft. Behavioural assessments of consciousness alone are often operator dependent, time consuming to obtain and may miss patients with covert consciousness.3 Our hypothesis is that resting Electroencephalogram (EEG) features follow a predictable course preceding behavioural recovery in patients with acute non-hypoxic-ischaemic brain injury receiving amantadine and may serve as biomarkers for recovery of consciousness. We studied 44 patients with ABI that were not following commands and were on EEG monitoring before and after the start of amantadine. A full description of the methods is available in the online supplementary file. ### Supplementary data [jnnp-2019-322645supp001.pdf] ### Study cohort From a cohort of 44 patients, 30 (68%) recovered consciousness prior to hospital discharge (online supplementary tables S1, S2). ### Baseline predictors of recovery Age, focal versus diffuse brain injury and admission Glasgow Coma Score were not associated with recovery of command following. Presence of sleep structures in the EEG (spindles and K-complexes) prior to starting amantadine was independently associated with recovery of command following (online supplementary table S3). Average spectrogram plots for each EEG recording classified according to the ‘ABCD’ model representing thalamocortical integrity were generated (figure 1A, online supplementary figure).4 The percent of patients that recovered command following did not increase hierarchically with higher ‘ABCD’ levels (figure 1B). Power spectral density analysis …