When is it safe to return to driving following first-ever seizure?

First seizure from sleep: Clinical features and prognosis

OBJECTIVES

Patients with a first-ever unprovoked seizure commonly have subsequent seizures and identifying predictors of recurrence has important management implications. Both prior brain insult and epileptiform abnormalities on electroencephalography (EEG) are established predictors of seizure recurrence. Some studies suggest that a first-ever seizure from sleep has a higher likelihood of recurrence. However, with relatively small numbers and inconsistent definitions, more data are required.

METHODS

Prospective cohort study of adults with first-ever unprovoked seizure seen by a hospital-based first seizure service between 2000 and 2015. Clinical features and outcomes of first-ever seizure from sleep and while awake were compared.

RESULTS

First-ever unprovoked seizure occurred during sleep in 298 of 1312 patients (23%), in whom the 1-year cumulative risk of recurrence was 56.9% (95% confidence interval [CI] 51.3-62.6) compared to 44.2% (95% CI 41.1-47.3, p < .0001) for patients with first-ever seizure while awake. First-ever seizure from sleep was an independent predictor of seizure recurrence, with a hazard ratio [HR] of 1.44 (95% CI 1.23-1.69), similar to epileptiform abnormalities on EEG (HR 1.48, 95% CI 1.24-1.76) and remote symptomatic etiology (HR 1.47, 95% CI 1.27-1.71). HR for recurrence in patients without either epileptiform abnormalities or remote symptomatic etiology was 1.97 (95% CI 1.60-2.44) for a sleep seizure compared to an awake seizure. For first seizure from sleep, 76% of second seizures also arose from sleep (p < .0001), with 65% of third seizures (p < .0001) also from sleep. Seizures from sleep were less likely to be associated with injury other than orolingual trauma, both with the presenting seizure (9.4% vs 30.6%, p < .0001) and first recurrence (7.5% vs 16.3%, p = .001).

SIGNIFICANCE

First-ever unprovoked seizures from sleep are more likely to recur, independent of other risk factors, with recurrences also usually from sleep, and with a lower risk of seizure-related injury. These findings may inform treatment decisions and counseling after first-ever seizure.

Antiseizure Medication Withdrawal Practice Patterns: A Survey Among Members of the American Academy of Neurology and EpiCARE

Background and Objectives

To describe neurologist practice patterns, challenges, and decision support needs pertaining to withdrawal of antiseizure medications (ASMs) in patients with well-controlled epilepsy.

Methods

We sent an electronic survey to (1) US and (2) European physician members of the American Academy of Neurology and (3) members of EpiCARE, a European Reference Network for rare and complex epilepsies. Analyses included frequencies and percentages, and we showed distributions through histograms and violin plots.

Results

We sent the survey to 4,923 individuals; 463 consented, 411 passed eligibility questions, and 287 responded to at least 1 of these questions. Most respondents indicated that they might ever consider ASM withdrawal, with respondents treating mostly children being more likely ever to consider withdrawal (e.g., medical monotherapy: children 96% vs adults 81%; p < 0.05). The most important factors when making decisions included seizure probability (83%), consequences of seizures (73%), and driving (74%). The top challenges when making decisions included unclear seizure probability (81%), inadequate guidelines (50%), and difficulty communicating probabilities (45%). Respondents would consider withdrawal after a median of 2-year seizure freedom, but also responded that they would begin withdrawal on average only when the postwithdrawal seizure relapse risk in the coming 2 years was less than 15%-30%. Wide variation existed in the use of words or numbers in respondents' counsel methods, for example, percentages vs frequencies or probability of seizure freedom vs seizure. The most highly rated point-of-care methods to inform providers of calculated risk were Kaplan-Meier curves and showing percentages only, rather than pictographs or text recommendations alone.

Discussion

Most surveyed neurologists would consider withdrawing ASMs in seizure-free individuals. Seizure probability was the largest factor driving decisions, yet estimating seizure probabilities was the greatest challenge. Respondents on average indicated that they may withdraw ASM after a minimum seizure-free duration of 2 years, yet also on average were willing to withdraw when seizure risk decreased below 15%-30%, which is lower than most patients' postwithdrawal risk at 2-year seizure freedom and lower than the equivalent even of a first seizure of life. These findings will inform future efforts at developing decision support tools aimed at optimizing ASM withdrawal decisions.

Prognosis of adults and children following a first unprovoked seizure

BACKGROUND

Epilepsy is clinically defined as two or more unprovoked epileptic seizures more than 24 hours apart. Given that, a diagnosis of epilepsy can be associated with significant morbidity and mortality, it is imperative that clinicians (and people with seizures and their relatives) have access to accurate and reliable prognostic estimates, to guide clinical practice on the risks of developing further unprovoked seizures (and by definition, a diagnosis of epilepsy) following single unprovoked epileptic seizure.

OBJECTIVES

1. To provide an accurate estimate of the proportion of individuals going on to have further unprovoked seizures at subsequent time points following a single unprovoked epileptic seizure (or cluster of epileptic seizures within a 24-hour period, or a first episode of status epilepticus), of any seizure type (overall prognosis). 2. To evaluate the mortality rate following a first unprovoked epileptic seizure.

SEARCH METHODS

We searched the following databases on 19 September 2019 and again on 30 March 2021, with no language restrictions. The Cochrane Register of Studies (CRS Web), MEDLINE Ovid (1946 to March 29, 2021), SCOPUS (1823 onwards), ClinicalTrials.gov, the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP). CRS Web includes randomized or quasi-randomized, controlled trials from PubMed, Embase, ClinicalTrials.gov, the World Health Organization International Clinical Trials Registry Platform (ICTRP), the Cochrane Central Register of Controlled Trials (CENTRAL), and the Specialized Registers of Cochrane Review Groups including Epilepsy. In MEDLINE (Ovid) the coverage end date always lags a few days behind the search date.

SELECTION CRITERIA

We included studies, both retrospective and prospective, of all age groups (except those in the neonatal period (< 1 month of age)), of people with a single unprovoked seizure, followed up for a minimum of six months, with no upper limit of follow-up, with the study end point being seizure recurrence, death, or loss to follow-up. To be included, studies must have included at least 30 participants. We excluded studies that involved people with seizures that occur as a result of an acute precipitant or provoking factor, or in close temporal proximity to an acute neurological insult, since these are not considered epileptic in aetiology (acute symptomatic seizures). We also excluded people with situational seizures, such as febrile convulsions.

DATA COLLECTION AND ANALYSIS

Two review authors conducted the initial screening of titles and abstracts identified through the electronic searches, and removed non-relevant articles. We obtained the full-text articles of all remaining potentially relevant studies, or those whose relevance could not be determined from the abstract alone and two authors independently assessed for eligibility. All disagreements were resolved through discussion with no need to defer to a third review author. We extracted data from included studies using a data extraction form based on the checklist for critical appraisal and data extraction for systematicreviews of prediction modelling studies (CHARMS). Two review authors then appraised the included studies, using a standardised approach based on the quality in prognostic studies (QUIPS) tool, which was adapted for overall prognosis (seizure recurrence). We conducted a meta-analysis using Review Manager 2014, with a random-effects generic inverse variance meta-analysis model, which accounted for any between-study heterogeneity in the prognostic effect. We then summarised the meta-analysis by the pooled estimate (the average prognostic factor effect), its 95% confidence interval (CI), the estimates of I² and Tau² (heterogeneity), and a 95% prediction interval for the prognostic effect in a single population at three various time points, 6 months, 12 months and 24 months. Subgroup analysis was performed according to the ages of the cohorts included; studies involving all ages, studies that recruited adult only and those that were purely paediatric.

MAIN RESULTS

Fifty-eight studies (involving 54 cohorts), with a total of 12,160 participants (median 147, range 31 to 1443), met the inclusion criteria for the review. Of the 58 studies, 26 studies were paediatric studies, 16 were adult and the remaining 16 studies were a combination of paediatric and adult populations. Most included studies had a cohort study design with two case-control studies and one nested case-control study. Thirty-two studies (29 cohorts) reported a prospective longitudinal design whilst 15 studies had a retrospective design whilst the remaining studies were randomised controlled trials. Nine of the studies included presented mortality data following a first unprovoked seizure. For a mortality study to be included, a proportional mortality ratio (PMR) or a standardised mortality ratio (SMR) had to be given at a specific time point following a first unprovoked seizure. To be included in the meta-analysis a study had to present clear seizure recurrence data at 6 months, 12 months or 24 months. Forty-six studies were included in the meta-analysis, of which 23 were paediatric, 13 were adult, and 10 were a combination of paediatric and adult populations. A meta-analysis was performed at three time points; six months, one year and two years for all ages combined, paediatric and adult studies, respectively. We found an estimated overall seizure recurrence of all included studies at six months of 27% (95% CI 24% to 31%), 36% (95% CI 33% to 40%) at one year and 43% (95% CI 37% to 44%) at two years, with slightly lower estimates for adult subgroup analysis and slightly higher estimates for paediatric subgroup analysis. It was not possible to provide a summary estimate of the risk of seizure recurrence beyond these time points as most of the included studies were of short follow-up and too few studies presented recurrence rates at a single time point beyond two years. The evidence presented was found to be of moderate certainty.

AUTHORS' CONCLUSIONS

Despite the limitations of the data (moderate-certainty of evidence), mainly relating to clinical and methodological heterogeneity we have provided summary estimates for the likely risk of seizure recurrence at six months, one year and two years for both children and adults. This provides information that is likely to be useful for the clinician counselling patients (or their parents) on the probable risk of further seizures in the short-term whilst acknowledging the paucity of long-term recurrence data, particularly beyond 10 years.

Acute symptomatic seizures and hippocampal sclerosis: the major contributor for post-stroke epilepsy?

OBJECTIVE

Hippocampal sclerosis (HS) is a prominent biomarker of epilepsy. If acquired later in life, it usually occurs in the context of degenerative or acute inflammatory-infectious disease. Conversely, acute symptomatic seizures (ASS) are considered a risk factor for developing post-stroke epilepsy, but other factors remain unrecognized. Here, we hypothesize that silent hippocampal injury contributes to the development of post-stroke epilepsy.

METHODS

We performed a retrospective observational study of patients hospitalized between 1/2007 and 12/2018 with an acute stroke in the Stroke Center of the Geneva University Hospital. Patients were included if they had a documented normal hippocampal complex at onset and a control MRI at ≥ 2 year interval without new lesion in the meantime.

RESULTS

162 patients fulfilled our inclusion criteria. ASS during the first week (p < 0.0001) and epileptiform abnormalities in electroencephalography (EEG; p = 0.02) were more frequently associated with the development of epilepsy. Hemorrhagic stroke was strongly associated to both ASS and future focal epilepsy (p = 0.00097). Three patients (1.8%) developed hippocampal sclerosis ipsilateral to the cerebrovascular event between 2 and 5 years, all with ASS and hemorrhagic stroke.

INTERPRETATION

ASS and epileptiform EEG abnormalities are strong predictors of post-stroke epilepsy. HS develops in a minority of patients after hemorrhagic lesions, leading to focal epilepsy. Prospective studies are required, including follow-up with EEG and if characterized by epileptiform discharges, with MRI, to determine the true frequency of HS and to better understand predictors of post-stroke epilepsy (AAS, stroke type, and HS), and their impact on stroke recovery.

Identification and Characterization of Pure Sleep Epilepsy in a Cohort of Patients With a First Seizure

OBJECTIVES

To study the development of pure sleep epilepsy (PSE) after a first-ever seizure from sleep in adults.

METHODS

Prospective observational study of patients seen at a tertiary hospital-based first seizure clinic between 2000 and 2011. Adults with a first-ever unprovoked seizure from sleep were consecutively recruited. All patients were followed up at least once after the initial seizure and those not requiring regular clinical review were contacted every one to two years. The timing and pattern of subsequent seizures as well as potential predictors of future awake seizures were analyzed.

RESULTS

239 adults with a first-ever unprovoked seizure from sleep were identified, 61% male; mean age 43 years (range 14-88 years) and median follow-up of 8.8 years (range 2 months -18 years). Of the 174 patients who had recurrent seizures, 130 patients (75%) had their second seizure from sleep, and of these, 76 of 94 (81%) also had their third seizure from sleep. 89 patients (37%) developed awake seizures during follow up. In half of these patients, the awake seizure occurred within two years of the initial seizure. The risk of an awake seizure within 1 year of a first-ever seizure from sleep was 13.9% (95%CI 9.4-18.3), falling to 2.0-5.3% per year after 3 years. The risks of an awake seizure within 1 year of a second or third consecutive sleep seizure were 9.9% (95%CI 4.6-15.3) and 8.7% (95%CI 2.0-15.4) respectively, and similarly decreased with time.

CONCLUSION

Most initial seizure recurrences after a first-ever sleep seizure occur during sleep. Whilst over one third eventually had awake seizures, the annual risk of an awake seizure was ≤14% and decreased with time, albeit with a small ongoing risk of between 2 and 5% per year. These findings may be utilized in counselling patients with seizures from sleep and inform driving recommendations.

Risk of seizure recurrence in people with single seizures and early epilepsy - Model development and external validation

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Model predicts risk of seizure recurrence after single fit or epilepsy diagnosis.

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Model performs well in independent data.

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Future work required to ensure the model is adopted in clinical practice.

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Model can improve the lives of people with single seizures and early epilepsy.

Purpose

Following a single seizure, or recent epilepsy diagnosis, it is difficult to balance risk of medication side effects with the potential to prevent seizure recurrence. A prediction model was developed and validated enabling risk stratification which in turn informs treatment decisions and individualises counselling.

Methods

Data from a randomised controlled trial was used to develop a prediction model for risk of seizure recurrence following a first seizure or diagnosis of epilepsy. Time-to-event data was modelled via Cox's proportional hazards regression. Model validity was assessed via discrimination and calibration using the original dataset and also using three external datasets – National General Practice Survey of Epilepsy (NGPSE), Western Australian first seizure database (WA) and FIRST (Italian dataset of people with first tonic-clonic seizures).

Results

People with neurological deficit, focal seizures, abnormal EEG, not indicated for CT/MRI scan, or not immediately treated have a significantly higher risk of seizure recurrence. Discrimination was fair and consistent across the datasets (c-statistics: 0.555 (NGPSE); 0.558 (WA); 0.597 (FIRST)). Calibration plots showed good agreement between observed and predicted probabilities in NGPSE at one and three years. Plots for WA and FIRST showed poorer agreement with the model underpredicting risk in WA, and over-predicting in FIRST. This was resolved following model recalibration.

Conclusion

The model performs well in independent data especially when recalibrated. It should now be used in clinical practice as it can improve the lives of people with single seizures and early epilepsy by enabling targeted treatment choices and more informed patient counselling.

Brainwaves beyond diagnosis: Wider applications of electroencephalography in idiopathic generalized epilepsy

Electroencephalography (EEG) has long been used as a versatile and noninvasive diagnostic tool in epilepsy. With the advent of digital EEG, more advanced applications of EEG have emerged. Compared with technologically advanced practice in focal epilepsies, the utilization of EEG in idiopathic generalized epilepsy (IGE) has been lagging, often restricted to a simple diagnostic tool. In this narrative review, we provide an overview of broader applications of EEG beyond this narrow scope, discussing how the current clinical and research applications of EEG may potentially be extended to IGE. The current literature, although limited, suggests that EEG can be used in syndromic classification, guiding antiseizure medication therapy, predicting prognosis, unraveling biorhythms, and investigating functional brain connectivity of IGE. We emphasize the need for longer recordings, particularly 24-h ambulatory EEG, to capture discharges reflecting circadian and sleep-wake cycle-associated variations for wider EEG applications in IGE. Finally, we highlight the challenges and limitations of the current body of literature and suggest future directions to encourage and enhance more extensive applications of this potent tool.

Long-term seizure recurrence after eclampsia: A systematic review and meta-analysis

BACKGROUND

Seizure recurrence after a fit has implications for both individuals and healthcare providers guiding neurologic prognosis, treatment, and driving and work restrictions. A systematic review of long-term seizure recurrence after eclampsia will help to quantify recurrence risk in this setting.

OBJECTIVE

To evaluate the long-term recurrence of seizures after eclampsia.

SEARCH STRATEGY

After PROSPERO registration, Medline (Ovid), Embase, and Cochrane Library were searched by using the terms (eclampsia OR eclamp* OR eclamptic seizure* OR eclamptic fit*) AND (recur* OR recurrent fit* OR recurrent seizure*) for studies published up until December 2019.

SELECTION CRITERIA

Studies describing long-term seizure recurrence after a diagnosis of eclampsia were included.

DATA COLLECTION AND ANALYSIS

Data were extracted from studies independently by two authors. Pooled prevalence was calculated and weighted based on sample size with a 95% confidence interval (CI).

MAIN RESULTS

Initially, 1754 unique studies were identified and 4 were included in the final analysis. The studies involved 1896 women, of whom 7 (0.37%) were affected by a further seizure. The weighted pooled prevalence of seizure recurrence was 0.18% (95% CI, 0.03-1.02).

CONCLUSION

The absolute rate of long-term seizure recurrence after eclampsia is extremely low and within safe limits for driving.

Epilepsy after severe traumatic brain injury: frequency and injury severity

Objective: To estimate national frequency of posttraumatic epilepsy (PTE) after severe traumatic brain injury (TBI) and assess injury severity (Glasgow Coma Scale (GCS) and posttraumatic amnesia (PTA)) as prognostic factors for PTE.

METHODS

Data on patients ≥18 years surviving severe TBI 2004-2016 were retrieved from the Danish Head Trauma Database (n = 1010). The cumulative incidence proportion (CIP) was estimated using death as competing event. The association between injury severity and PTE was assessed using multivariable competing risk regressions.

RESULTS

CIP of PTE 28 days and one year post-TBI was 6.8% (95% confidence interval (CI) 5.4-8.5) and 18.5% (95% CI 16.1-21.1%), respectively. Injury severity was not associated with PTE within 28 days post-TBI but indicated higher PTE-rates in less severely injured patients. PTA-duration >70 days was associated with PTE 29-365 days post-TBI (Adjusted sub-hazard ratio 4.23 (95% CI 1.79-9.99)). GCS was not associated with PTE 29-365 days post-TBI.

CONCLUSION

The PTE frequency was higher compared to previous estimates. Increasing injury severity was associated with PTE 29-365 days post-TBI when measured with PTA, but not with GCS. Though nonsignificant, the increased PTE-risk within 28 days in lower severity suggests an underdiagnosing of PTE.

The other side of the leaf: Seizures associated with synthetic cannabinoid use

There has recently been a marked rise in the medicinal use of cannabis for epilepsy and multiple other conditions. While seizures have been reported in association with synthetic cannabinoids, the clinical features and prognosis have not been studied. Thirty patients with a history of seizures occurring within 24 h of synthetic cannabinoid use were identified from a first seizure clinic database in Perth, Western Australia between 2011 and 2016. Eight had a prior history of seizures, three related to synthetic cannabinoid use, with an additional three patients having risk factors for seizures. The presenting event was a tonic-clonic seizure in 27 patients (90%). "Kronic" was the synthetic cannabinoid used by 16 patients. Absorption was via smoking in all cases, with seizures occurring within 30 min of inhalation in 14 patients (46%). Electroencephalography (EEG) showed epileptiform abnormalities in 11%, and neuroimaging revealed epileptogenic lesions in 12%. Nine of 24 patients with follow-up had subsequent seizures, occurring in the setting of further synthetic cannabinoid use in two patients. This seizure recurrence rate is similar to seizures provoked by other acute systemic insults. In conclusion, smoking of some synthetic cannabinoids is associated with seizures, and this may relate to an intrinsic proconvulsant effect.

Understanding variability in driving recommendations for patients with seizures

BACKGROUND

There is lack of consensus regarding driving restrictions for patients with epilepsy. Regulations vary by state. New York State (NYS) recommends driving restrictions for one year in a person with an episode of loss of consciousness (LOC), with physician discretion. Often, providers make recommendations to permit their patients to drive after a shorter seizure-free period than proposed guidelines. The prevalence and reasons behind more lenient recommendations have not been elucidated.

METHODS

Forty-one neurologists were surveyed anonymously in Nassau County, New York. They were questioned about the length of recommended driving restrictions (≤1, 3, 6, or ≥12months) that they typically provide to patients with suspected seizures in different clinical scenarios and overall reasons for doing so. Data about level of training, setting of practice, use of antiepileptic drug (AED) levels, and electroencephalogram (EEG) were also collected.

RESULTS

Of the 41 neurologists surveyed, 72% reported recommending driving restrictions <12months for patients who experienced LOC, without a confirmed diagnosis of seizure. The majority also recommended driving restriction of <12months for other scenarios including acute symptomatic seizure, exclusively simple partial seizures, nocturnal seizures, psychogenic nonepileptic seizures (PNES), and seizures occurring with or during AED reduction. The most common rationale was to improve patient autonomy and independence. Less than a third of neurologists estimated that the majority of their patients were noncompliant with driving recommendations.

CONCLUSION

We found that many neurologists' recommendations for limiting driving for patients with seizure-related episodes are shorter than those recommended by NYS. Furthermore, as there are no specific guidelines for questionable epileptic scenarios and seizures occurring nocturnally or without LOC, this appears to contribute to substantial variability in the duration of recommended driving restrictions. This opens a broad discussion about approaches towards advising driving limitations in order to protect public and patient safety while maintaining patient autonomy.

Risk of a seizure recurrence after a breakthrough seizure and the implications for driving: further analysis of the standard versus new antiepileptic drugs (SANAD) randomised controlled trial

OBJECTIVES

A breakthrough seizure is one occurring after at least 12 months seizure freedom while on treatment. The Driver and Vehicle Licensing Agency (DVLA) allows an individual to return to driving once they have been seizure free for 12 months following a breakthrough seizure. This is based on the assumption that the risk of a further seizure in the next 12 months has dropped <20%. This analysis considers whether the prescribed 1 year off driving following a breakthrough seizure is sufficient for this and stratifies risk according to clinical characteristics. DESIGN, SETTING, PARTICIPANTS, INTERVENTIONS AND MAIN OUTCOME MEASURES: The multicentre UK-based Standard versus New Antiepileptic Drugs (SANAD) study was a randomised controlled trial assessing standard and new antiepileptic drugs for patients with newly diagnosed epilepsy. For participants aged at least 16 with a breakthrough seizure, data have been analysed to estimate the annual seizure recurrence risk following a period of 6, 9 and 12 months seizure freedom. Regression modelling was used to investigate how antiepileptic drug treatment and a number of clinical factors influence the risk of seizure recurrence.

RESULTS

At 12 months following a breakthrough seizure, the overall unadjusted risk of a recurrence over the next 12 months is lower than 20%, risk 17% (95% CI 15% to 19%). However, some patient subgroups have been identified which have an annual recurrence risk significantly greater than 20% after an initial 12-month seizure-free period following a breakthrough seizure.

CONCLUSIONS

This reanalysis of SANAD provides estimates of seizure recurrence risks following a breakthrough seizure that will inform policy and guidance about regaining an ordinary driving licence. Further guidance is needed as to how such data should be used.

TRIAL REGISTRATION NUMBER

SANAD is registered with the International Standard Randomised Controlled Trial Number Register ISRCTN38354748.

Counselling adults who experience a first seizure

PURPOSE

A first seizure can result in significant uncertainty, fear and apprehension. One of the key roles of the clinician in the setting of first seizure is to provide accurate, timely information and counselling.

METHOD

We review the numerous components to be considered when counselling an adult patient after a first seizure.

RESULTS

We provide a framework and manner to provide that counselling. We focus on an individualized approach and provide recommendations and information on issues of diagnosis, etiology, prognosis, the role and importance of medical testing, lifestyle considerations, driving, medication and other key counselling considerations.

CONCLUSION

Accurate, timely counselling can allay fears and anxieties, remove misconceptions and reduce the risk for injury in seizure recurrence.

Predictive value of S100-B and copeptin for outcomes following seizure: the BISTRO International Cohort Study

Objective

To evaluate the performance of S100-B protein and copeptin, in addition to clinical variables, in predicting outcomes of patients attending the emergency department (ED) following a seizure.

Methods

We prospectively included adult patients presented with an acute seizure, in four EDs in France and the United Kingdom. Participants were followed up for 28 days. The primary endpoint was a composite of seizure recurrence, all-cause mortality, hospitalization or rehospitalisation, or return visit in the ED within seven days.

Results

Among the 389 participants included in the analysis, 156 (40%) experienced the primary endpoint within seven days and 195 (54%) at 28 days. Mean levels of both S100-B (0.11 μg/l [95% CI 0.07–0.20] vs 0.09 μg/l [0.07–0.14]) and copeptin (23 pmol/l [9–104] vs 17 pmol/l [8–43]) were higher in participants meeting the primary endpoint. However, both biomarkers were poorly predictive of the primary outcome with a respective area under the receiving operator characteristic curve of 0.57 [0.51–0.64] and 0.59 [0.54–0.64]. Multivariable logistic regression analysis identified higher age (odds ratio [OR] 1.3 per decade [1.1–1.5]), provoked seizure (OR 4.93 [2.5–9.8]), complex partial seizure (OR 4.09 [1.8–9.1]) and first seizure (OR 1.83 [1.1–3.0]) as independent predictors of the primary outcome. A second regression analysis including the biomarkers showed no additional predictive benefit (S100-B OR 3.89 [0.80–18.9] copeptin OR 1 [1.00–1.00]).

Conclusion

The plasma biomarkers S100-B and copeptin did not improve prediction of poor outcome following seizure. Higher age, a first seizure, a provoked seizure and a partial complex seizure are independently associated with adverse outcomes.