Postictal ammonia as a biomarker for electrographic convulsive seizures: A prospective study

Differentiation of epilepsy and psychogenic nonepileptic events based on body fluid characteristics

OBJECTIVE

Differential diagnosis between epileptic seizures and psychogenic nonepileptic events (PNEEs) is a worldwide problem for neurologists. The present study aims to identify important characteristics from body fluid tests and develop diagnostic models based on them.

METHODS

This is a register-based observational study in patients with a diagnosis of epilepsy or PNEEs at West China Hospital of Sichuan University. Data from body fluid tests between 2009 and 2019 were used as a training set. We constructed models with a random forest approach in eight training subsets divided by sex and categories of tests, including electrolyte, blood cell, metabolism, and urine tests. Then, we collected data prospectively from patients between 2020 and 2022 to validate our models and calculated the relative importance of characteristics in robust models. Selected characteristics were finally analyzed with multiple logistic regression to establish nomograms.

RESULTS

A total of 388 patients, including 218 with epilepsy and 170 with PNEEs, were studied. The AUROCs of random forest models of electrolyte and urine tests in the validation phase achieved 80.0% and 79.0%, respectively. Carbon dioxide combining power, anion gap, potassium, calcium, and chlorine in electrolyte tests and specific gravity, pH, and conductivity in urine tests were selected for the logistic regression analysis. C (ROC) of the electrolyte and urine diagnostic nomograms achieved 0.79 and 0.85, respectively.

SIGNIFICANCE

The application of routine indicators of serum and urine may help in the more accurate identification of epileptic and PNEEs.

Classification Model for Epileptic Seizure Using Simple Postictal Laboratory Indices

Distinguishing syncope from epileptic seizures in patients with sudden loss of consciousness is important. Various blood tests have been used to indicate epileptic seizures in patients with impaired consciousness. This retrospective study aimed to predict the diagnosis of epilepsy in patients with transient loss of consciousness using the initial blood test results. A seizure classification model was constructed using logistic regression, and predictors were selected from a cohort of 260 patients using domain knowledge and statistical methods. The study defined the diagnosis of seizures and syncope based on the consistency of the diagnosis made by an emergency medicine specialist at the first visit to the emergency room and the diagnosis made by an epileptologist or cardiologist at the first outpatient visit using the International Classification of Diseases 10th revision (ICD-10) code. Univariate analysis showed higher levels of white blood cells, red blood cells, hemoglobin, hematocrit, delta neutrophil index, creatinine kinase, and ammonia levels in the seizure group. The ammonia level had the highest correlation with the diagnosis of epileptic seizures in the prediction model. Therefore, it is recommended to be included in the first examination at the emergency room.

Risk factors and outcome of hyperammonaemia in people with epilepsy

BACKGROUND

Hyperammonaemia is a recognised complication of antiseizure treatment but risk factors leading to individual patient susceptibility and outcome remain unclear.

OBJECTIVE

To identify risk factors for hyperammonaemia and investigate the impact of its management on clinical outcomes.

METHODS

We carried out a retrospective observational study of adults with epilepsy who had ammonia tested over a 3-year period. Hyperammonaemia was defined as ammonia level > 35 μmol/L. Patients were classified into two groups: hyperammonaemic and non-hyperammonaemic. Association analyses and linear regression analysis were used to identify risk factors for hyperammonaemia.

RESULTS

We reviewed 1002 ammonia requests in total and identified 76 people with epilepsy who had ammonia concentration measured, including 26 with repeated measurements. 59/76 (78%) were found to have hyperammonaemia. There was borderline statistical significance of hyperammonaemia being less common in patients with an established monogenic/metabolic condition than in those with structural or cryptogenic epilepsy (P = 0.05). Drug resistance, exposure to stiripentol and oxcarbazepine were identified as risk factors for hyperammonaemia. We found a dose-dependent association between valproate and hyperammonaemia (P = 0.033). Clinical symptoms were reported in 22/59 (37%) of the hyperammonaemic group. Improved clinical outcomes with concurrent decrease in ammonia concentration were seen in 60% of patients following treatment adjustment.

CONCLUSIONS

Drug resistance and exposure to stiripentol, oxcarbazepine or high-dose valproate are associated with an increased risk of hyperammonaemia. Clinicians should consider symptoms related to hyperammonaemia in patients on high-dose valproate or multiple antiseizure treatments. Prompt identification of hyperammonaemia and subsequent treatment adjustments can lead to improved clinical outcomes.

Biomarkers for posttraumatic epilepsy

A biomarker is a characteristic that can be objectively measured as an indicator of normal biologic processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions. Biomarker modalities include molecular, histologic, radiographic, or physiologic characteristics. To improve the understanding and use of biomarker terminology in biomedical research, clinical practice, and medical product development, the Food and Drug Administration (FDA)-National Institutes of Health (NIH) Joint Leadership Council developed the BEST Resource (Biomarkers, EndpointS, and other Tools). The seven BEST biomarker categories include the following: (a) susceptibility/risk biomarkers, (b) diagnostic biomarkers, (c) monitoring biomarkers, (d) prognostic biomarkers, (e) predictive biomarkers, (f) pharmacodynamic/response biomarkers, and (g) safety biomarkers. We hypothesize some potential overlap between the reported biomarkers of traumatic brain injury (TBI), epilepsy, and posttraumatic epilepsy (PTE). Here, we tested this hypothesis by reviewing studies focusing on biomarker discovery for posttraumatic epileptogenesis and epilepsy. The biomarker modalities reviewed here include plasma/serum and cerebrospinal fluid molecular biomarkers, imaging biomarkers, and electrophysiologic biomarkers. Most of the reported biomarkers have an area under the receiver operating characteristic curve greater than 0.800, suggesting both high sensitivity and high specificity. Our results revealed little overlap in the biomarker candidates between TBI, epilepsy, and PTE. In addition to using single parameters as biomarkers, machine learning approaches have highlighted the potential for utilizing patterns of markers as biomarkers. Although published data suggest the possibility of identifying biomarkers for PTE, we are still in the early phase of the development curve. Many of the seven biomarker categories lack PTE-related biomarkers. Thus, further exploration using proper, statistically powered, and standardized study designs with validation cohorts, and by developing and applying novel analytical methods, is needed for PTE biomarker discovery.

Hyperammonemia in Patients With Status Epilepticus Treated With or Without Valproic Acid

BACKGROUND

Hyperammonemia is a common side effect of valproic acid (VPA) and can occur after generalized seizures, but the clinical significance is unclear. The aim of this study was to better understand the clinical practice and utility of ammonia testing in status epilepticus (SE) treated with or without VPA.

METHODS

Charts of adult patients with SE from St. Mary's Hospital Intensive Care Units (ICUs) (Mayo Clinic, Rochester, MN) from 2011 to 2016 were reviewed. Clinical factors were compared between patients who had ammonia checked versus those who did not, and those with normal ammonia versus hyperammonemia (>50 µg/dL). Charts were reviewed to determine if hyperammonemia changed clinical management and if it was felt to be symptomatic.

RESULTS

There were 304 patients identified: 94 received VPA, 142 had ammonia checked and receiving VPA was associated with ammonia testing (P<0.001). Hyperammonemia was identified in 32 and associated with younger age, being in a non-neurological intensive care unit, and liver disease, but was not statistically associated with VPA. Only one patient had valproate-induced hyperammonemic encephalopathy; however, many patients received treatment for hyperammonemia such as lactulose, levocarnitine, or VPA dose reductions.

CONCLUSIONS

This study demonstrated variability in ammonia testing and management changes in SE but does not support the routine monitoring of ammonia levels and showed that hyperammonemic encephalopathy was rare in this clinical setting.

Acute metabolic effects of tonic-clonic seizures

OBJECTIVE

Tonic-clonic seizures (TCS) lead to metabolic stress and changes in related blood markers. Such markers may indicate harmful conditions but can also help to identify TCS as a cause of transient loss of consciousness. In this study, we hypothesized that the alterations of circulating markers of metabolic stress depend on the clinical features of TCS.

METHODS

Ninety-one adults undergoing video-EEG monitoring participated in this prospective study. Electrolytes, renal parameters, creatine kinase (CK), prolactin (PRL), lactate, ammonia, glucose, and other parameters were measured at inclusion and different time points after TCS.

RESULTS

A total of 39 TCS were recorded in 32 patients (six generalized onset tonic-clonic seizures in 6 and 33 focal to bilateral tonic-clonic seizures in 26 patients). Shortly after TCS, mean lactate, ammonia, and PRL levels were significantly increased 8.7-fold, 2.6-fold, and 5.1-fold, respectively, with levels of more than twofold above the upper limits of the normal (ULN) in 90%, 71%, and 70% of the TCS and returned to baseline levels within 2 hours. Only postictal lactate levels were significantly correlated with the total duration of the tonic-clonic phase. In contrast, CK elevations above the ULN were found in three TCS (~10%) only with a peak after 48 hours. Immediately after the TCS, hyperphosphatemia occurred in one third of the patients, whereas hypophosphatemia was observed in one third 2 hours later. TCS led to subtle but significant alterations of other electrolytes, creatinine, and uric acid, whereas glucose levels were moderately increased.

SIGNIFICANCE

Lactate is a robust metabolic marker of TCS with elevations found in ~90% of cases within 30 minutes after seizure termination, whereas ammonia rises in ~ 70%, similarly to PRL. Phosphate levels show an early increase and a decrease 2 hours after TCS in a third of patients. CK elevations are rare after video-EEG-documented TCS, challenging its value as a diagnostic marker.

Postictal syndrome: The forgotten continent. An overview of the clinical, biochemical and imaging features

Postictal syndrome (PIS) encompasses the clinical, biological, electroencephalographic (EEG) and magnetic resonance imaging (MRI) signs that follow the termination of a seizure. These signs occur as soon as the epileptic discharge ends, but might remain for a substantially long period of time, making them amenable to clinical observation. As a direct consequence, neurologists and intensivists are more frequently attending patients with PIS than during their seizure. Moreover, careful PIS documentation may help physicians to diagnose epileptic seizure from other non-epileptic disorders. Careful analysis of PIS could also be helpful to better characterize the seizure (seizure subtypes, and to some extent, the localization and/or lateralization of the seizure). This article aims to review the main clinical, biological, EEG and MRI components of PIS, discuss differential diagnoses and propose a general clinical attitude, based on the acronym "WAITTT": W for "Watch", to monitor and investigate PIS in order to provide relevant information on seizure, AIT for "Avoid Inappropriate Treatment", to underscore the risk carrying out unnecessary drug injections and intensive care procedures in the setting of a self-limited symptomatology, and TT for "Take Time", to keep in mind that time remains the clinician's best ally for treating patients with PIS.

Potential use of leukocytosis and anion gap elevation in differentiating psychogenic nonepileptic seizures from epileptic seizures

Epileptic seizures (ES) and psychogenic nonepileptic seizures (PNES) can be difficult to differentiate from each other in the emergency department (ED) setting. We have previously shown that the anion gap (AG) can help differentiate between ES and PNES in the ED. In this study, we explored whether additionally considering leukocytosis can help better differentiate between ES and PNES. We screened a total of 1354 subjects seen in the ED of a tertiary care medical center; 27 PNES and 27 ES patients were identified based on clinical description and subsequent electroencephalography (EEG). Multivariable logistic regression analysis was used to model the association between ES, leukocytosis, and AG. Our results indicated that within 9 hours after the index event, serum AG (adjusted odds ratio [aOR] 2.07) and white blood cell (WBC) count (aOR 1.61) were both independently associated with ES. We derived an equation to help differentiate between ES and PNES: 1.5*AG+WBC. A score >24.8 indicated a >90% likelihood of ES. A score <15.5 indicated a <10% likelihood of ES (ie, the alternate diagnosis of PNES should be considered). This study for the first time provides evidence to help differentiate PNES and ES utilizing acidosis and leukocytosis.

Anion gap can differentiate between psychogenic and epileptic seizures in the emergency setting

Differentiation between psychogenic nonepileptic seizures (PNES) and generalized convulsive epileptic seizures (ES) is important for appropriate triaging in the emergency department (ED). This can be difficult in the ED, as the event is often not witnessed by a medical professional. In the current study, we investigated whether anion gap (AG), bicarbonate, and the Denver Seizure Score (DSS) could differentiate between PNES and ES. Of a total of 1,354 subjects reviewed from a tertiary care medical center, 27 PNES and 27 ES patients were identified based on clinical description and subsequent electroencephalogram. Multivariate logistic regression analysis and receiver operating characteristic curves were used to determine whether there was an association between seizure type and AG, bicarbonate, or DSS (24-bicarbonate + 2 × [AG-12]) when samples were drawn within 24 h of the concerning event. The result showed that sensitivity and negative predictive value dropped markedly for all measures if samples were drawn >2 h after the event; the sensitivity was similar for AG and DSS and higher than for bicarbonate. We propose that AG > 10 (sensitivity of 81.8%, specificity of 100%) in the first 2 h after the event could be used as a potential tool in the ED to help differentiate between PNES and ES.