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Background: Electroencephalography (EEG) is essential to assess prognosis in patients after cardiac arrest (CA). Use of continuous EEG (cEEG) is increasing in critically-ill patients, but it is more resource-consuming than routine EEG (rEEG). Observational studies did not show a major impact of cEEG versus rEEG on outcome, but randomized studies are lacking.Methods: We analyzed data of the CERTA trial (NCT03129438), including comatose adults after CA undergoing cEEG (30-48 hours) or two rEEG (20-30 minutes each). We explored correlations between recording EEG type and mortality (primary outcome), or Cerebral Performance Categories (CPC, secondary outcome), assessed blindly at 6 months, using uni- and multivariable analyses (adjusting for other prognostic variables showing some imbalance across groups).Results: We analyzed 112 adults (52 underwent rEEG, 60 cEEG,); 31 (27.7%) were women; 68 (60.7%) patients died. In univariate analysis, mortality (rEEG 59%, cEEG 65%, p = 0.318) and good outcome (CPC 1-2; rEEG 33%, cEEG 27%, p = 0.247) were comparable across EEG groups. This did not change after multiple logistic regressions, adjusting for shockable rhythm, time to return of spontaneous circulation, serum neuron-specific enolase, EEG background reactivity, regarding mortality (cEEG vs rEEG: OR 1.60, 95% CI 0.43-5.83, p = 0.477), and good outcome (OR 0.51, 95% CI 0.14-1.90, p = 0.318).Conclusion: This analysis suggests that cEEG or repeated rEEG are related to comparable outcomes of comatose patients after CA. Pending a prospective, large randomized trial, this finding does not support the routine use of cEEG for prognostication in this setting.Trial Registration: Continuous EEG Randomized Trial in Adults (CERTA); NCT03129438; July 25, 2019. [ABSTRACT FROM AUTHOR]

Aim: Generalized periodic discharge (GPD) is an EEG pattern of poor neurological outcome, frequently observed in comatose patients after cardiac arrest. The aim of our study was to identify the neuronal network generating ≤2.5 Hz GPD using EEG source localization and connectivity analysis.Methods: We analyzed 40 comatose adult patients with anoxic-ischemic encephalopathy, who had 19 channel-EEG recording. We computed electric source analysis based on distributed inverse solution (LAURA) and we estimated cortical activity in 82 atlas-based cortical brain regions. We applied directed connectivity analysis (Partial Directed Coherence) on these sources to estimate the main drivers.Results: Source analysis suggested that the GPD are generated in the cortex of the limbic system in the majority of patients (87.5%). Connectivity analysis revealed main drivers located in thalamus and hippocampus for the large majority of patients (80%), together with important activation also in amygdala (70%).Conclusions: We hypothesize that the anoxic-ischemic dysfunction, leading to hyperactivity of the thalamo-cortical (limbic presumably) circuit, can result in an oscillatory thalamic activity capable of inducing periodic cortical (limbic, mostly medial-temporal and orbitofrontal) discharges, similarly to the case of generalized rhythmic spike-wave discharge in convulsive or non-convulsive status epilepticus. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Introduction: Standardized EEG patterns according to the American Clinical Neurophysiology Society (ACNS) ("highly malignant", "malignant" and "benign") demonstrated good correlation with outcome after cardiac arrest (CA). However, this approach relates to EEGs after target temperature management (TTM), and correlation to other recognized outcome predictors remains unknown.Objectives: To investigate the relationship between categorized EEG and other outcome predictors, during and after TTM, at different temperatures.Methods: In a prospective adult CA registry between 01.2014 and 06.2017, EEG at day one and two after CA were reclassified into pre-defined categories. Correlations between EEG and clinical, biochemical, neurophysiological outcome predictors, and prognosis (CPC at three months; good: 1-2), were assessed.Results: Of 203 CA episodes, 31.5% were managed targeting 33 °C, 60.6% targeting 36 °C, and 7.9% with spontaneous temperature. "Highly malignant" EEG was found in 36.7% of patients at day one (predicting poor prognosis with 91% specificity -95%CI: 83%-97%-, and 63% sensitivity -95% CI: 53%-72%), and 27.1% at day two. "Benign" EEG occurred in 19.2% at day one (sensitivity to good prognosis: 35% -95%CI: 26%-46%-, positive predictive value: 89% -95% CI: 75%-97%), and in 33.2% at day two. Categorized EEG showed robust correlations with all prognostic predictors. Results were similar between EEGs recorded at day one or two, and, especially for poor prognosis, across TTM targets.Discussion: Standardized EEG categorization after CA shows strong correlation with other outcome predictors, without marked variation across EEG recording time or TTM targets, underscoring its prognostic role in a multimodal approach. [ABSTRACT FROM AUTHOR]

Objective To determine whether neurologic consultation influences the use of therapeutic hypothermia. Methods We identified adult patients treated for cardiac arrest from October 2009 through September 2015 at 149 academic medical centers and their affiliate hospitals using discharge diagnosis codes in Vizient database. Neurology consultation was defined as a neurologist participating in patient care at any point during the hospitalization. Use of therapeutic hypothermia was identified using procedure codes. We used multivariable models to evaluate the association between neurologic consultation and therapeutic hypothermia before and after adjustment for patient baseline characteristics and hospital factors including inpatient volume and relative volume of cardiac arrest cases. Results We identified 136,830 hospitalizations for cardiac arrest. The 9,336 (6.8%) encounters involving a neurologist had higher severity of illness, longer hospital stay, and longer intensive care unit stay. There were 5,034 (3.7%) encounters where patients underwent therapeutic hypothermia. Hypothermia use was significantly more common when neurologists were involved during hospitalization (7.9% vs. 3.4%; OR 2.44, 95% CI 2.2-2.6; p < 0.01). After adjustment, neurologic consultation continued to be associated with the use of therapeutic hypothermia (adjusted OR 2.5, 95% CI 2.3–2.8), particularly among hospitals in the highest quartile of total inpatient volume (OR 4.6, 95% CI 4.0–5.3). Lower in-hospital mortality was also associated with neurological consultation after adjusting for therapeutic hypothermia (59.2% vs. 61.3%, p < 0.01). Conclusions The involvement of a neurologist in cardiac arrest patients is associated with increased use of therapeutic hypothermia, though therapeutic hypothermia for cardiac arrest likely remains underutilized. [ABSTRACT FROM AUTHOR]

Aim: The current EEG role for prognostication after cardiac arrest (CA) essentially aims at reliably identifying patients with poor prognosis ("highly malignant" patterns, defined by Westhall et al. in 2014). Conversely, "benign EEGs", defined by the absence of elements of "highly malignant" and "malignant" categories, has limited sensitivity in detecting good prognosis. We postulate that a less stringent "benign EEG" definition would improve sensitivity to detect patients with favorable outcomes.Methods: Retrospectively assessing our registry of unconscious adults after CA (1.2018-8.2021), we scored EEGs within 72 h after CA using a modified "benign EEG" classification (allowing discontinuity, low-voltage, or reversed anterio-posterior amplitude development), versus Westhall's "benign EEG" classification (not allowing the former items). We compared predictive performances towards good outcome (Cerebral Performance Category 1-2 at 3 months), using 2x2 tables (and binomial 95% confidence intervals) and proportions comparisons.Results: Among 381 patients (mean age 61.9 ± 15.4 years, 104 (27.2%) females, 240 (62.9%) having cardiac origin), the modified "benign EEG" definition identified a higher number of patients with potential good outcome (252, 66%, vs 163, 43%). Sensitivity of the modified EEG definition was 0.97 (95% CI: 0.92-0.97) vs 0.71 (95% CI: 0.62-0.78) (p < 0.001). Positive predictive values (PPV) were 0.53 (95% CI: 0.46-0.59) versus 0.59 (95% CI: 0.51-0.67; p = 0.17). Similar statistics were observed at definite recording times, and for survivors.Discussion: The modified "benign EEG" classification demonstrated a markedly higher sensitivity towards favorable outcome, with minor impact on PPV. Adaptation of "benign EEG" criteria may improve efficient identification of patients who may reach a good outcome. [ABSTRACT FROM AUTHOR]