Trends in management of patients with new-onset refractory status epilepticus (NORSE) from 2016 to 2023: An interim analysis.

In response to the evolving treatment landscape for new-onset refractory status epilepticus (NORSE) and the publication of consensus recommendations in 2022, we conducted a comparative analysis of NORSE management over time. Seventy-seven patients were enrolled by 32 centers, from July 2016 to August 2023, in the NORSE/FIRES biorepository at Yale. Immunotherapy was administered to 88% of patients after a median of 3 days, with 52% receiving second-line immunotherapy after a median of 12 days (anakinra 29%, rituximab 25%, and tocilizumab 19%). There was an increase in the use of second-line immunotherapies (odds ratio [OR] = 1.4, 95% CI = 1.1-1.8) and ketogenic diet (OR = 1.8, 95% CI = 1.3-2.6) over time. Specifically, patients from 2022 to 2023 more frequently received second-line immunotherapy (69% vs 40%; OR = 3.3; 95% CI = 1.3-8.9)-particularly anakinra (50% vs 13%; OR = 6.5; 95% CI = 2.3-21.0), and the ketogenic diet (OR = 6.8; 95% CI = 2.5-20.1)-than those before 2022. Among the 27 patients who received anakinra and/or tocilizumab, earlier administration after status epilepticus onset correlated with a shorter duration of status epilepticus (ρ = .519, p = .005). Our findings indicate an evolution in NORSE management, emphasizing the increasing use of second-line immunotherapies and the ketogenic diet. Future research will clarify the impact of these treatments and their timing on patient outcomes.

Comparative analysis of patients with new onset refractory status epilepticus preceded by fever (febrile infection-related epilepsy syndrome) versus without prior fever: An interim analysis.

Febrile infection-related epilepsy syndrome (FIRES) is a subset of new onset refractory status epilepticus (NORSE) that involves a febrile infection prior to the onset of the refractory status epilepticus. It is unclear whether FIRES and non-FIRES NORSE are distinct conditions. Here, we compare 34 patients with FIRES to 30 patients with non-FIRES NORSE for demographics, clinical features, neuroimaging, and outcomes. Because patients with FIRES were younger than patients with non-FIRES NORSE (median = 28 vs. 48 years old, p = .048) and more likely cryptogenic (odds ratio = 6.89), we next ran a regression analysis using age or etiology as a covariate. Respiratory and gastrointestinal prodromes occurred more frequently in FIRES patients, but no difference was found for non-infection-related prodromes. Status epilepticus subtype, cerebrospinal fluid (CSF) and magnetic resonance imaging findings, and outcomes were similar. However, FIRES cases were more frequently cryptogenic; had higher CSF interleukin 6, CSF macrophage inflammatory protein-1 alpha (MIP-1a), and serum chemokine ligand 2 (CCL2) levels; and received more antiseizure medications and immunotherapy. After controlling for age or etiology, no differences were observed in presenting symptoms and signs or inflammatory biomarkers, suggesting that FIRES and non-FIRES NORSE are very similar conditions.

Combined depth and scalp electroencephalographic monitoring in acute brain injury: Yield and prognostic value.

BACKGROUND AND PURPOSE: Depth electroencephalography (dEEG) is an emerging neuromonitoring technology in acute brain injury (ABI). We aimed to explore the concordances between electrophysiological activities on dEEG and on scalp EEG (scEEG) in ABI patients. METHODS: Consecutive ABI patients who received dEEG monitoring between 2018 and 2022 were included. Background, sporadic epileptiform discharges, rhythmic and periodic patterns (RPPs), electrographic seizures, brief potentially ictal rhythmic discharges, ictal-interictal continuum (IIC) patterns, and hourly RPP burden on dEEG and scEEG were compared. RESULTS: Sixty-one ABI patients with a median dEEG monitoring duration of 114 h were included. dEEG significantly showed less continuous background (75% vs. 90%, p = 0.03), higher background amplitude (p < 0.001), more frequent rhythmic spike-and-waves (16% vs. 3%, p = 0.03), more IIC patterns (39% vs. 21%, p = 0.03), and greater hourly RPP burden (2430 vs. 1090 s/h, p = 0.01), when compared to scEEG. Among five patients with seizures on scEEG, one patient had concomitant seizures on dEEG, one had periodic discharges (not concomitant) on dEEG, and three had no RPPs on dEEG. Features and temporal occurrence of electrophysiological activities observed on dEEG and scEEG are not strongly associated. Patients with seizures and IIC patterns on dEEG seemed to have a higher rate of poor outcomes at discharge than patients without these patterns on dEEG (42% vs. 25%, p = 0.37). CONCLUSIONS: dEEG can detect abnormal electrophysiological activities that may not be seen on scEEG and can be used as a complement in the neuromonitoring of ABI patients.

Sustained effort network for treatment of status epilepticus/European academy of neurology registry on adult refractory status epilepticus (SENSE-II/AROUSE).

BACKGROUND: Status Epilepticus (SE) is a common neurological emergency associated with a high rate of functional decline and mortality. Large randomized trials have addressed the early phases of treatment for convulsive SE. However, evidence regarding third-line anesthetic treatment and the treatment of nonconvulsive status epilepticus (NCSE) is scarce. One trial addressing management of refractory SE with deep general anesthesia was terminated early due to insufficient recruitment. Multicenter prospective registries, including the Sustained Effort Network for treatment of Status Epilepticus (SENSE), have shed some light on these questions, but many answers are still lacking, such as the influence exerted by distinct EEG patterns in NCSE on the outcome. We therefore initiated a new prospective multicenter observational registry to collect clinical and EEG data that combined may further help in clinical decision-making and defining SE. METHODS: Sustained effort network for treatment of status epilepticus/European Academy of Neurology Registry on refractory Status Epilepticus (SENSE-II/AROUSE) is a prospective, multicenter registry for patients treated for SE. The primary objectives are to document patient and SE characteristics, treatment modalities, EEG, neuroimaging data, and outcome of consecutive adults admitted for SE treatment in each of the participating centers and to identify factors associated with outcome and refractoriness. To reach sufficient statistical power for multivariate analysis, a cohort size of 3000 patients is targeted. DISCUSSION: The data collected for the registry will provide both valuable EEG data and information about specific treatment steps in different patient groups with SE. Eventually, the data will support clinical decision-making and may further guide the planning of clinical trials. Finally, it could help to redefine NCSE and its management. TRIAL REGISTRATION: NCT number: NCT05839418.

Severity scores for status epilepticus in the ICU: systemic illness also matters.

BACKGROUND: Current prognostic scores for status epilepticus (SE) may not be adequate for patients in ICU who usually have more severe systemic conditions or more refractory episodes of SE. We aimed to compare the prognostic performance of two SE scores, Status Epilepticus Severity Score (STESS) and Epidemiology-Based Mortality Score in Status Epilepticus (EMSE) score, with four systemic severity scores, Acute Physiology and Chronic Health Evaluation 2 (APACHE-2), Simplified Acute Physiology Score 2 (SAPS-2), Sequential Organ Failure Assessment (SOFA) score, and Inflammation, Nutrition, Consciousness, Neurologic function and Systemic condition (INCNS) score in critically ill patients with SE. METHODS: This retrospective observational study of a prospectively identified SE cohort was conducted in the ICU at a tertiary-care center. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and associations with outcomes of STESS, EMSE, INCNS, APACHE-2, SAPS-2, and SOFA score for the prediction of in-hospital mortality and no return to baseline condition were assessed. RESULTS: Between January 2015 and December 2020, 166 patients with SE in ICU were included in the study. In predicting in-hospital death, APACHE-2 (0.72), SAPS-2 (0.73), and SOFA score (0.71) had higher AUCs than STESS (0.58) and EMSE (0.69). In predicting no return to baseline condition, the AUC of APACHE-2 (0.75) was the highest, and the AUC of INCNS (0.55) was the lowest. When the specificity approached 90%, the sensitivity values of these scores were not quite acceptable (< 40%). Neither SE scores nor systemic severity scores had desirable prognostic power. In the multivariate logistic regression analyses, the best combinations of scores always included at least one or more systemic severity scores. CONCLUSIONS: STESS and EMSE were insufficient in outcome prediction for SE patients in ICU, and EMSE was marginally better than STESS. Systemic illness matters in ICU patients with SE, and SE scores should be modified to achieve better accuracy in this severely ill population. This study mostly refers to severely ill patients in the ICU.

Prognostic scores in status epilepticus: A systematic review and meta-analysis.

The performance of prognostic scores of status epilepticus (SE) has been reported in very heterogeneous cohorts. We aimed to provide a summary of the available evidence on their respective performance. PubMed and EMBASE were searched for relevant articles. Studies were reviewed for eligibility for meta-analysis of the area under the receiver-operating characteristic curve (AUC) and for meta-analysis of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) in predicting in-hospital mortality with scores in which at least two external evaluations had been published. This study was registered with PROSPERO (international prospective register of systematic reviews) (CRD42022325766). Study quality was assessed using Prediction model Risk Of Bias ASsessment Tool (PROBAST). In the meta-analysis of AUC, 21 studies were pooled for STESS (Status Epilepticus Severity Score), five for EMSE-EAC (Epidemiology-based Mortality Score in Status Epilepticus - Etiology, Age, level of Consciousness), five for EMSE-EACE (EMSE - Etiology, Age, level of Consciousness, EEG), and two for ENDIT (Encephalitis, nonconvulsive status epilepticus, Diazepam resistance, Imaging abnormalities, Tracheal intubation). The pooled AUC of STESS, EMSE-EAC, EMSE-EACE, and ENDIT was 0.74 (95% CI: 0.71-0.78), 0.68 (95% CI 0.63-0.72), 0.77 (95% CI: 0.72-0.81), and 0.78 (95% CI: 0.70-0.87), respectively. The pooled sensitivity of STESS-3, STESS-4, EMSE-EACE-64, and ENDIT-4 was 0.83 (95% CI: 0.80-0.86), 0.60 (95% CI: 0.55-0.65), 0.76 (95% CI: 0.67-0.83), and 0.70 (95% CI: 0.55-0.82), respectively. Their pooled specificity was 0.50 (95% CI: 0.48-0.52), 0.74 (95% CI: 0.72-0.76), 0.63 (95% CI: 0.59-0.67), and 0.65 (95% CI: 0.61-0.70), respectively. Their pooled PPV was 0.27 (95% CI: 0.24-0.30), 0.35 (95% CI: 0.29-0.41), 0.33 (95% CI: 0.24-0.43), and 0.20 (95% CI: 0.13-0.27). Their pooled NPV was 0.94 (95% CI: 0.93-0.96), 0.90 (95% CI: 0.89-0.92), 0.89 (95% CI: 0.80-0.98), and 0.95 (95% CI: 0.92-0.98). Variations in performance were observed in patients' subgroups, such as critically ill patients and refractory cases. Investigated scores only have acceptable AUC, sensitivity, and specificity for predicting in-hospital mortality, with the EMSE-EAC having a lower discriminative power. STESS-3 has the highest sensitivity, and STESS-4 the highest specificity, but neither combines acceptable sensitivity and specificity. All these scores had high NPV but very low PPV. Caution should be exercised in their clinical use. Further studies are required to develop more accurate scores.

Stroke Core Volume Weighs More Than Recanalization Time for Predicting Outcome in Large Vessel Occlusion Recanalized Within 6 h of Symptoms Onset.

Introduction: Current guidelines suggest that perfusion imaging should only be performed > 6 h after symptom onset. Pathophysiologically, brain perfusion should matter whatever the elapsed time. We aimed to compare relative contribution of recanalization time and stroke core volume in predicting functional outcome in patients treated by endovascular thrombectomy within 6-h of stroke-onset. Methods: Consecutive patients presenting between January 2015 and June 2021 with (i) an acute ischaemic stroke due to an anterior proximal occlusion, (ii) a successful thrombectomy (TICI >2a) within 6-h of symptom-onset and (iii) CT perfusion imaging were included. Core stroke volume was automatically computed using RAPID software. Two linear regression models were built that included in the null hypothesis the pre-treatment NIHSS score and the hypoperfusion volume (Tmax > 6 s) as confounding variables and 24 h post-recanalization NIHSS and 90 days mRS as outcome variables. Time to recanalization was used as covariate in one model and stroke core volume as covariate in the other. Results: From a total of 377 thrombectomies, 94 matched selection criteria. The Model null hypothesis explained 37% of the variability for 24 h post-recanalization NIHSS and 42% of the variability for 90 days MRS. The core volume as covariate increased outcome variability prediction to 57 and 56%, respectively. Time to recanalization as covariate marginally increased outcome variability prediction from 37 and 34% to 40 and 42.6%, respectively. Conclusion: Core stroke volume better explains outcome variability in comparison to the time to recanalization in anterior large vessel occlusion stroke with successful thrombectomy done within 6 h of symptoms onset. Still, a large part of outcome variability prediction fails to be explained by the usual predictors.

Duration of nonconvulsive seizures in critically ill patients.

INTRODUCTION: Non-convulsive seizures (NCSz) and non-convulsive status epilepticus (NCSE) are frequent in critically ill patients. Specific temporal thresholds to define both are lacking and may be needed to guide appropriate treatment. METHOD: Retrospective review of 995 NCSz captured during continuous EEG monitoring of 111 consecutive critically ill patients. Seizures were classified according to their type and underlying etiology (acute or progressive brain injury, seizure-related disorders and acute medical illness). Median and interquartile ranges [IQR] were calculated. Suggested temporal threshold for NCSE was defined as the 95 percentile of seizure duration. RESULTS: Most (69%) patients had an underlying acute or progressive brain injury. The 95 percentile of seizure duration was 518 s, overall, with variation according to underlying etiology (median 86 [47-137] s for brain injury, 73 [45-115] s for seizure-related disorders, and 92 [58-223] s for acute medical illness, respectively; p = 0.0025; 95 percentile 424, 304, and 1725 s, respectively). Forty-one (37%) patients were comatose and had significantly longer seizures than non-comatose patients (median 99 [49-167] vs. 73 [46-123] s; p < 0.001; 95 percentile: 600 vs 444 s). CONCLUSION: To define NCSE, a temporal threshold of 10 min in critically ill patients with a primary neurological diagnosis can be applied, while a temporal threshold of 30 min might be suitable for patients with an underlying acute medical illness.

Effects of a Psychoeducational Program on Caregivers of Patients with Dementia.

BACKGROUND: The number of demented patients has increased significantly in recent years. The many challenges that dementia causes increase the stress of their caregivers and lead to shortening the time to institutionalization compared to the general population. A psychoeducational program for these accompanying persons was set up in Brussels. This type of program resulted in a 557-day delay in institutionalization in New York City. The objective of our study was to check whether our program also has such an impact, but also to see its potential effect on the psychobehavioral disorders of patients and the burden of caregivers. METHODS: We recruited two groups without randomization: psychoeducated caregivers and caregivers interested in the program and contacted regularly (every 6 months) without having participated. They were all contacted by telephone and responded to the NCPI and Zarit Burden Scale (ZBS) questionnaires. RESULTS: We could not demonstrate any significant impact, either on the institutionalization delay (p = 0.960), on the frequency of psychobehavioral disorders in demented patients (p > 0.05), or on the burden of caregivers (p = 0.403). However, the survival rate among the demented patients with psychoeducated caregivers was significantly higher than that among the demented patients with nonpsychoeducated caregivers (p < 0.001). CONCLUSIONS: Our small-sample, nonrandomized study did not reveal any differences in institutionalization delay, caregiver burden, or perception of psychobehavioral disorders related to our psychoeducational program. A new study should be carried out on the impact of psychoeducation on the survival of demented patients, in view of our preliminary analyses.

Minimal Setting Stroke Unit in a Sub-Saharan African Public Hospital.

Introduction: Sub-Saharan Africa (SSA) has the highest stroke prevalence along with a case fatality that amounts to 40%. We aimed to assess the effect of a minimal setting stroke unit in SSA Public hospital on stroke mortality and main medical complications. Materials and Methods: The study was set in Conakry, Guinea, Ignace Deen public referral hospital. Clinical characteristics, hospital mortality and main medical stroke complications rates (pneumonia, urinary tract infections, sores and venous thromboembolism) of admitted stroke patients after the installation of a minimal stroke unit equipped with heart rate, blood pressure and blood oxygen saturation monitoring and portable oxygen concentrator (POST) were compared to a similar number of stroke patients admitted before the stroke unit creation (PRE). Results: PRE (n = 318) and POST (n = 361) stroke, patients were comparable in term of age (61 ± 14 vs. 60 ± 14.8 years, p = 0.24), sex (56 vs. 50% males, p = 0.09), High blood pressure rate (76.7 vs. 79%, p = 0.44), stroke subtype (ischemic in 72 vs. 78% of cases, p = 0.05) and NIHSS (11 ± 4 vs. 11 ± 4, p = 0.85). Diabetes was more frequent in the PRE group (19 vs. 9%, p < 0.001). Mortality was significantly lower in the POST group (7.2 vs. 22.3%, p < 0.0001) as well as medical complications (4.1 vs. 27.7%, p < 0.001) and lower pneumonia rate (3.3 vs. 14.5%, p < 0.001). Conclusions: Minimally equipped stroke units significantly reduce stroke mortality and main medical complications in SSA.