How much refractory is 'refractory status epilepticus'? A retrospective study of treatment strategies and clinical outcomes

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.

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.

Mammalian models of status epilepticus - Their value and limitations

Status epilepticus (SE) is a medical and neurologic emergency that may lead to permanent brain damage, morbidity, or death. Animal models of SE are particularly important to study the pathophysiology of SE and mechanisms of SE resistance to antiseizure medications with the aim to develop new, more effective treatments. In addition to rodents (rats or mice), larger mammalian species such as dogs, pigs, and nonhuman primates are used. This short review describes and discusses the value and limitations of the most frequently used mammalian models of SE. Issues that are discussed include (1) differences between chemical and electrical SE models; (2) the role of genetic background and environment on SE in rodents; (3) the use of rodent models (a) to study the pathophysiology of SE and mechanisms of SE resistance; (b) to study developmental aspects of SE; (c) to study the efficacy of new treatments, including drug combinations, for refractory SE; (d) to study the long-term consequences of SE and identify biomarkers; (e) to develop treatments that prevent or modify epilepsy; (e) to study the pharmacology of spontaneous seizures; (4) the limitations of animal models of induced SE; and (5) the advantages (and limitations) of naturally (spontaneously) occurring SE in epileptic dogs and nonhuman primates. Overall, mammalian models of SE have significantly increased our understanding of the pathophysiology and drug resistance of SE and identified potential targets for new, more effective treatments. This paper was presented at the 9th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures held in April 2024.

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.