Acute symptomatic status epilepticus: Splitting or lumping? A proposal of classification based on real-world data

Development of a nomogram model for early prediction of refractory convulsive status epilepticus

INTRODUCTION

We aim to identify risk factors that predict refractory convulsive status epilepticus (RCSE) and to develop a model for early recognition of patients at high risk for RCSE.

METHODS

This study involved 200 patients diagnosed with convulsive status epilepticus (CSE), of whom 73 were RCSE and 127 were non-RCSE. Variables included demographic information, lifestyle factors, medical history, comorbidities, clinical symptoms, neuroimaging characteristics, laboratory tests, and nutritional scores. A predictive model was developed through multivariable logistic regression analysis. The model's predictive performance and clinical utility were evaluated using various metrics, including the area under the receiver operating characteristic (AUROC) curve, GiViTI calibration belt, and decision curve analysis (DCA). Additionally, we performed internal five-fold cross-validation for this model.

RESULTS

We developed a nomogram model with six predictors: age ≤ 40 years, prior history of epilepsy, presence of epileptic foci, duration of CSE > 30 min, c-reactive protein > 6 mg/L, and nutritional risk screening ≥ 3 points. Our model has a high AUROC (0.838) and good consistency (P = 0.999). In DCA, the curve of our model exhibits a positive net benefit across the entire range of threshold probabilities. Moreover, our model achieved an accuracy of 0.778 and a Kappa value of 0.519 in the five-fold cross-validation.

CONCLUSION

We developed an objective, simple and accessible model to assess the risk of RCSE. This model shows promise as a valuable tool for evaluating the individual risk of RCSE.

Early Polytherapy for Probably Benzodiazepine Refractory Naïve Status Epilepticus (Stage 1 Plus)

Stage 1 Plus is defined here as a naïve, previously untreated, status epilepticus (SE) that is probably refractory to Benzodiazepines (BDZ). These cases include not only prolonged SE as previously proposed by the author (SE lasting > 10 min) but also other cases notoriously associated with BDZ refractoriness such as the absence of prominent motor phenomena and acute etiology (especially primary central nervous system etiology). Interestingly, the absence of prominent motor phenomena as is the case of non convulsive SE might implicitly fall in the category of prolonged SE due to the delay in recognition and treatment. Future studies should help identify other factors associated with BDZ refractoriness, therefore widening the definition of Stage 1 Plus. The appropriate timing for defining prolonged SE may also differ depending on different etiology. Consequently, in future tailored models of SE, the definition of prolonged SE could be enhanced by defining it for a longer duration than Tx, a time point that changes based on different etiologies (x), Tx being much shorter than 10 min in acute etiologies. These cases of naïve probably BDZ refractory SE (Stage 1 Plus) might require a different approach: combined polytherapy from the start. The objective of this review is to provide pathophysiological and pre-clinical evidence, mostly from animal studies, for the different approach of combined polytherapy from the start for those cases of SE falling in the definition of Stage 1 Plus.

Diagnosis and management of status epilepticus: improving the status quo

Status epilepticus is a common neurological emergency that is characterised by prolonged or recurrent seizures without recovery between episodes and associated with substantial morbidity and mortality. Prompt recognition and targeted therapy can reduce the risk of complications and death associated with status epilepticus, thereby improving outcomes. The most recent International League Against Epilepsy definition considers two important timepoints in status epilepticus: first, when the seizure does not self-terminate; and second, when the seizure can have long-term consequences, including neuronal injury. Recent advances in our understanding of the pathophysiology of status epilepticus indicate that changes in neurotransmission as status epilepticus progresses can increase excitatory seizure-facilitating and decrease inhibitory seizure-terminating mechanisms at a cellular level. Effective clinical management requires rapid initiation of supportive measures, assessment of the cause of the seizure, and first-line treatment with benzodiazepines. If status epilepticus continues, management should entail second-line and third-line treatment agents, supportive EEG monitoring, and admission to an intensive care unit. Future research to study early seizure detection, rescue protocols and medications, rapid treatment escalation, and integration of fundamental scientific and clinical evidence into clinical practice could shorten seizure duration and reduce associated complications. Furthermore, improved recognition, education, and treatment in patients who are at risk might help to prevent status epilepticus, particularly for patients living in low-income and middle-income countries.

Prognostic factors and impact of management strategies for status epilepticus: The STEPPER study in the Emilia-Romagna region, Italy

OBJECTIVE

The STEPPER (Status Epilepticus in Emilia-Romagna) study aimed to investigate the clinical characteristics, prognostic factors, and treatment approaches of status epilepticus (SE) in adults of the Emilia-Romagna region (ERR), Northern Italy.

METHODS

STEPPER, an observational, prospective, multicentric cohort study, was conducted across neurology units, emergency departments, and intensive care units of the ERR over 24 months (October 2019-October 2021), encompassing incident cases of SE. Patients were followed up for 30 days.

RESULTS

A total of 578 cases were recruited (56% female, mean age = 70 years, 32% with previous diagnosis of epilepsy, 43% with in-hospital onset, 35% stuporous/comatose, 46% with nonconvulsive SE). Etiology was known in 87% (acute 43%, remote 24%, progressive 17%, definite epileptic syndrome 3%). The mean pre-SE Rankin Scale score was 2, the Status Epilepticus Severity Score was ≥4 in 33%, the Epidemiology-Based Mortality Score in Status Epilepticus score was ≥64 in 61%, and 34% were refractory. The sequence of treatments followed current clinical practice guidelines in 63%. Benzodiazepines (BDZs) were underused as first-line therapy (71%), especially in in-hospital onset cases; 15% were treated with continuous intravenous anesthetic drugs. Mortality was 24%; 63% of survivors had functional worsening. At the two-step multivariable analysis, incorrect versus correct treatment sequence with correct BDZ dose was the strongest predictor of failure to resolve SE in the in-hospital group (odds ratio [OR] = 4.42, 95% confidence interval [CI] = 1.86-10.5), with a similar trend in the out-of-hospital group (OR = 2.22, 95% CI = .98-5.02). In turn, failure to resolve was the strongest predictor of 30-day mortality (OR = 11.3, 95% CI = 4.16-30.9, out-of-hospital SE; OR = 6.42, 95% CI = 2.79-14.8, in-hospital SE) and functional worsening (OR = 5.83, 95% CI = 2.05-16.6, out-of-hospital SE; OR = 9.30, 95% CI 2.22-32.3, in-hospital SE).

SIGNIFICANCE

The STEPPER study offers insights into real-world SE management, highlighting its significant morbidity and functional decline implications. Although nonmodifiable clinical factors contribute to SE severity, modifiable factors such as optimized first-line therapies and adherence to guidelines can potentially influence prognosis.

Progression to refractory status epilepticus: A machine learning analysis by means of classification and regression tree analysis

BACKGROUND AND OBJECTIVES

to identify predictors of progression to refractory status epilepticus (RSE) using a machine learning technique.

METHODS

Consecutive patients aged ≥ 14 years with SE registered in a 9-years period at Modena Academic Hospital were included in the analysis. We evaluated the risk of progression to RSE using logistic regression and a machine learning analysis by means of classification and regression tree analysis (CART) to develop a predictive model of progression to RSE.

RESULTS

705 patients with SE were included in the study; of those, 33 % (233/705) evolved to RSE. The progression to RSE was an independent risk factor for 30-day mortality, with an OR adjusted for previously identified possible univariate confounders of 4.086 (CI 95 % 2.390-6.985; p < 0.001). According to CART the most important variable predicting evolution to RSE was the impaired consciousness before treatment, followed by acute symptomatic hypoxic etiology and periodic EEG patterns. The decision tree identified 14 nodes with a risk of evolution to RSE ranging from 1.5 % to 90.8 %. The overall percentage of success in classifying patients of the decision tree was 79.4 %; the percentage of accurate prediction was high, 94.1 %, for those patients not progressing to RSE and moderate, 49.8 %, for patients evolving to RSE.

CONCLUSIONS

Decision-tree analysis provided a meaningful risk stratification based on few variables that are easily obtained at SE first evaluation: consciousness before treatment, etiology, and severe EEG patterns. CART models must be viewed as potential new method for the stratification RSE at single subject level deserving further exploration and validation.

NCSE-coma in older adults: Clinical data, initial EEG, and hospital outcome

INTRODUCTION

The clinical-EEG profile and prognosis in nonconvulsive status epilepticus (NCSE-coma) - with preceding SE and without preceding SE - have not been fully established yet.

OBJECTIVE

To evaluate the initial EEG, clinical characteristics, and hospital outcome of older adults with NCSE-coma.

METHODOLOGY

Clinical variables, immediate prognosis, initial EEG data, and scores on the Status Epilepticus Severity Score (STESS) and the SACE score were evaluated according to the type of NCSE-coma (with and without preceding seizure/SE) in 51 older adult patients treated in the emergency department.

RESULTS

The mean age of the participants was 72.2 years. In 23 cases, the diagnosis was NCSE-coma with preceding seizure/SE, and in 28 cases the diagnosis was NCSE-coma without preceding seizure/SE. Previous history of seizures/epilepsy occurred in 11 cases (21.5 %), and was more frequent in NCSE-coma with preceding seizure/SE. The most common etiology was acute. Death within 30 days occurred in 21 cases (41.1 %), but there was no difference between types of NCSE-coma. The predominant EEG finding was the presence of epileptiform discharges/rhythmic delta activity showing morphological/spatial/temporal evolution (classified as A2 in the Salzburg Consensus Criteria [SCC]). There was a significant difference in EEG findings according to the type of NCSE-coma. Total SACE scores averaged 0.9 ± 0.8; on the STESS, it was 4.7 ± 0.4. In the SACE score, the highest total score and a more significant occurrence of scores ≥ 3 (indicating a better prognosis) were observed in NCSE-coma with preceding seizure/SE.

CONCLUSION

In older adults, the types of NCSE-coma presented different clinical aspects and patterns on initial EEG. The mortality rates were elevated. The most prevalent EEG findings encompass criteria A2 of the SCC. A history of previous seizures/epilepsy and a more favorable prognosis in the SACE score occurred in NCSE-coma with preceding seizure/SE.

Status epilepticus: Is there a Stage 1 plus?

In status epilepticus (SE), "time is brain." Currently, first-line therapy consists of benzodiazepines (BDZs) and SE is classified by the response to treatment; stage 2 or established SE is defined as "BDZ-resistant SE." Nonetheless, this classification does not always work, especially in the case of prolonged convulsive SE, where many molecular changes occur and γ-aminobutyric acid signaling becomes excitatory. Under these circumstances, BDZ therapy might not be optimal, and might be possibly detrimental, if given alone; as the duration of SE increases, so too does BDZ resistance. Murine models of SE showed how these cases might benefit more from synergistic combined therapy from the start. The definition of Stage 1 plus is suggested, as a stage requiring combined therapy from the start, which includes prolonged SE with seizure activity going on for >10 min, the time that marks the disruption of receptor homeostasis, with increased internalization. This specific stage might require a synergistic approach from the start, with a combination of first- and second-line treatment.

Research progress on the relationship between epilepsy and circRNA

OBJECTIVE

This review aims to provide a comprehensive summary of the latest research progress regarding the relationship between epilepsy and circular RNA (circRNA).

METHODS

Relevant literature from the PubMed database was meticulously searched and reviewed. The selected articles focused on investigating the association between epilepsy and circRNA, including studies on expression patterns, diagnostic markers, therapeutic targets, and functional mechanisms.

RESULTS

Epilepsy, characterized by recurrent seizures, is a neurological disorder. Numerous studies have demonstrated significant alterations in the expression profiles of circRNA in epileptic brain tissues, animal models, and peripheral blood samples. These differential expressions of circRNA are believed to be closely linked with the occurrence and development of epilepsy. Moreover, circRNA has shown promising potential as diagnostic markers for epilepsy, as well as prognostic indicators for predicting disease outcomes. Furthermore, circRNA has emerged as a potential therapeutic target for epilepsy treatment, offering prospects for gene therapy interventions.

CONCLUSION

The dysregulation of circRNA expression in epilepsy suggests its potential involvement in the pathogenesis and progression of this disorder. Identifying specific circRNA molecules associated with epilepsy may pave the way for novel diagnostic approaches and therapeutic strategies. However, further investigations are imperative to elucidate the precise functional mechanisms of circRNA in epilepsy and validate its clinical utility.

Remote seizures and drug-resistant epilepsy after a first status epilepticus in adults

BACKGROUND AND PURPOSE

Long-term consequences after status epilepticus (SE) represent an unsettled issue. We investigated the incidence of remote unprovoked seizures (RS) and drug-resistant epilepsy (DRE) in a cohort of first-ever SE survivors.

METHODS

A retrospective, observational, and monocentric study was conducted on adult patients (age ≥ 14 years) with first SE who were consecutively admitted to the Modena Academic Hospital, Italy (September 2013-March 2022). Kaplan-Meier survival analyses were used to calculate the probability of seizure freedom following the index event, whereas Cox proportional hazard regression models were used to identify outcome predictors.

RESULTS

A total of 279 patients were included, 57 of whom (20.4%) developed RS (mean follow-up = 32.4 months). Cumulative probability of seizure freedom was 85%, 78%, and 68% respectively at 12 months, 2 years, and 5 years. In 45 of 57 patients (81%), the first relapse occurred within 2 years after SE. The risk of RS was higher in the case of structural brain damage (hazard ratio [HR] = 2.1, 95% confidence interval [CI] = 1.06-4.01), progressive symptomatic etiology (HR = 2.7, 95% CI = 1.44-5.16), and occurrence of nonconvulsive evolution in the semiological sequence of SE (HR = 2.9, 95% CI = 1.37-6.37). Eighteen of 57 patients (32%) developed DRE; the risk was higher in the case of super-refractory (p = 0.006) and non-convulsive SE evolution (p = 0.008).

CONCLUSIONS

The overall risk of RS was moderate, temporally confined within 2 years after the index event, and driven by specific etiologies and SE semiology. Treatment super-refractoriness and non-convulsive SE evolution were associated with DRE development.

The risk of unprovoked seizure occurrence after status epilepticus in adults

OBJECTIVE

Status epilepticus (SE) may lead to long-term consequences. This study evaluated the risk and predictors of seizure occurrence after SE, with a focus on SE due to acute symptomatic etiologies.

METHODS

Prospectively collected data about adults surviving a first non-hypoxic SE were reviewed. The outcome was the occurrence of unprovoked seizures during the follow-up. Kaplan-Meier survival curve analysis and log-rank test were used to analyze the time to seizure occurrence and determine the statistical significance between etiological groups. Three subcategories within acute etiology were considered according to the presence of the following: (1) structural lesion (acute-primary); (2) brain involvement during systemic disorders (acute-secondary); and (3) drug or alcohol intoxication/withdrawal (acute-toxic). Cox proportional hazards model was adopted to estimate hazard ratios (HRs) with the 95% confidence intervals (CIs).

RESULTS

Two hundreds fifty-seven individuals were included. Fifty-four subjects (21.0%) developed seizures after a median of 9.9 (interquartile range 4.3-21.7) months after SE. The estimated 1-, 2-, and 5-year rates of seizure occurrence according to acute SE etiologies were 19.4%, 23.4%, and 30.1%, respectively, for acute-primary central nervous system (CNS) pathology; 2.2%, 2.2%, and 8.7%, respectively, for acute-secondary CNS pathology; and 0%, 9.1%, and 9.1%, respectively, for acute-toxic causes. Five-year rates of seizure occurrence for non-acute SE causes were 33.9% for remote, 65.7% for progressive, and 25.9% for unknown etiologies. In multivariate Cox regression model, progressive etiology (adjusted HR [adjHR] 2.27, 95% CI 1.12-4.58), SE with prominent motor phenomena evolving in non-convulsive SE (adjHR 3.17, 95% CI 1.38-7.25), and non-convulsive SE (adjHR 2.38, 95% CI 1.16-4.90) were independently associated with higher hazards of unprovoked seizures. Older people (adjHR .98, 95% CI .96-.99) and people with SE due to acute-secondary CNS pathology (adjHR .18, 95% CI .04-.82) were at decreased risk of seizure occurrence.

SIGNIFICANCE

SE carries a risk of subsequent seizures. Both the underlying cause and epileptogenic effects of SE are likely to contribute.

Risk assessment of long-term epilepsy after de novo status epilepticus with clinical and electroencephalographic biomarkers: The AFTER score

BACKGROUND

The risk of developing epilepsy after de novo status epilepticus (SE) is nonnegligible. The individualized management of patients with high risk of subsequent epilepsy could improve long-term quality of life and cognitive impairment. We aimed to ascertain potential biomarkers of subsequent epilepsy and to construct a scoring system possessing predictive value for the diagnosis of post-SE epilepsy during follow-up.

METHODS

The study data were obtained from a prospective registry of all SE episodes occurring in patients over 16 years attended in our tertiary center from February 2011 to April 2022. Clinical data, electroencephalography findings, treatment, and long-term clinical data were prospectively recorded. We selected SE patients at risk of developing epilepsy (acute symptomatic and cryptogenic etiologies with no previous history of epilepsy) and analyzed the risk of developing subsequent epilepsy.

RESULTS

We included 230 patients. Median age was 65 years ± 16.9 SD and 112/230 (48.7 %) were women. One-hundred ninety-eight patients (86.1 %) had an acute symptomatic SE, whereas 32 patients (13.9 %) presented with a cryptogenic SE. A total of 55 patients (23.9 %) developed an unprovoked remote seizure and were diagnosed with epilepsy. After adjusting for identifiable confounders in a multivariable Cox regression analysis cryptogenic etiology (HR 2.24 [1.13-4.46], p = 0.022), first-line treatment initiation ≥1 h (HR 2.12 [1.03-4.36], p = 0.041], RDA/LPD/GPD EEG patterns (HR 1.88 [1.07-3.32], p = 0.028), and super-refractoriness (HR 2.90 [1.40-5.99], p = 0.004) emerged as independent predictors of post-SE epilepsy. Based on these findings, we constructed the AFTER score (1 point for each item) with a robust capability to predict post-SE epilepsy at 5 years (AUC 74.3 %, 95 %CI 64.3-84.3 %, p < 0.001).

CONCLUSIONS

The AFTER score is a robust predictor of the development of epilepsy after new onset SE using clinical and electroencephalographic biomarkers (such as etiology, time to first-line treatment initiation, EEG pattern and super-refractoriness). Prospective studies are warranted to validate the score in other populations.