Clinical outcome assessment in patients with epilepsy: The value of health-related quality of life measurements.

This narrative review provides an overview of the current knowledge on health-related quality of life (HRQOL), a relevant clinical outcome in patients with epilepsy. It shows that the most important factor determining HRQOL in this patient group is seizure frequency. In particular, seizure-freedom is associated with better HRQOL scores. Many other factors may impact perceived HRQOL aspects, but their interrelation is complex and requires further research. Novel analytical approaches, such as hierarchical cluster and symptom network analyses might shed further light on this, and may result in recommendations for interventions on the most 'central' factors influencing different aspects of HRQOL in patients with epilepsy. Next, an overview of the HRQOL tools and analytical methods currently used in epilepsy care, with a focus on clinical trials, is provided. The QOLIE-31 is the most frequently applied and best validated tool. Several other questionnaires focusing on specific aspects of HRQOL (e.g., mood, social impact) are less frequently used. We show some pitfalls that should be taken into account when designing study protocols including HRQOL endpoints. This includes standardized statistical analysis approaches and predefined reporting methods for HRQOL in epilepsy populations. It has been shown in other patient groups that the lack of such standardisation negatively impacts the quality and comparability of results. We conclude with a number of recommendations for future research.

Neurophysiological signatures reflect differences in visual attention during absence seizures.

OBJECTIVE: Absences affect visual attention and eye movements variably. Here, we explore whether the dissimilarity of these symptoms during absences is reflected in differences in electroencephalographic (EEG) features, functional connectivity, and activation of the frontal eye field. METHODS: Pediatric patients with absences performed a computerized choice reaction time task, with simultaneous recording of EEG and eye-tracking. We quantified visual attention and eye movements with reaction times, response correctness, and EEG features. Finally, we studied brain networks involved in the generation and propagation of seizures. RESULTS: Ten pediatric patients had absences during the measurement. Five patients had preserved eye movements (preserved group) and five patients showed disrupted eye movements (unpreserved group) during seizures. Source reconstruction showed a stronger involvement of the right frontal eye field during absences in the unpreserved group than in the preserved group (dipole fraction 1.02% and 0.34%, respectively, p < 0.05). Graph analysis revealed different connection fractions of specific channels. CONCLUSIONS: The impairment of visual attention varies among patients with absences and is associated with differences in EEG features, network activation, and involvement of the right frontal eye field. SIGNIFICANCE: Assessing the visual attention of patients with absences can be usefully employed in clinical practice for tailored advice to the individual patient.

Transcranial magnetic stimulation-evoked electroencephalography responses as biomarkers for epilepsy: A review of study design and outcomes.

Transcranial magnetic stimulation (TMS) with electroencephalography (EEG), that is TMS-EEG, may assist in managing epilepsy. We systematically reviewed the quality of reporting and findings in TMS-EEG studies on people with epilepsy and healthy controls, and on healthy individuals taking anti-seizure medication. We searched the Cochrane Library, Embase, PubMed and Web of Science databases for original TMS-EEG studies comparing people with epilepsy and healthy controls, and healthy subjects before and after taking anti-seizure medication. Studies should involve quantitative analyses of TMS-evoked EEG responses. We evaluated the reporting of study population characteristics and TMS-EEG protocols (TMS sessions and equipment, TMS trials and EEG protocol), assessed the variation between protocols, and recorded the main TMS-EEG findings. We identified 20 articles reporting 14 unique study populations and TMS methodologies. The median reporting rate for the group of people with epilepsy parameters was 3.5/7 studies and for the TMS parameters was 13/14 studies. TMS protocols varied between studies. Fifteen out of 28 anti-seizure medication trials in total were evaluated with time-domain analyses of single-pulse TMS-EEG data. Anti-seizure medication significantly increased N45, and decreased N100 and P180 component amplitudes but in marginal numbers (N45: 8/15, N100: 7/15, P180: 6/15). Eight articles compared people with epilepsy and controls using different analyses, thus limiting comparability. The reporting quality and methodological uniformity between studies evaluating TMS-EEG as an epilepsy biomarker is poor. The inconsistent findings question the validity of TMS-EEG as an epilepsy biomarker. To demonstrate TMS-EEG clinical applicability, methodology and reporting standards are required.

TMS-evoked EEG potentials demonstrate altered cortical excitability in migraine with aura.

Migraine is associated with altered sensory processing, that may be evident as changes in cortical responsivity due to altered excitability, especially in migraine with aura. Cortical excitability can be directly assessed by combining transcranial magnetic stimulation with electroencephalography (TMS-EEG). We measured TMS evoked potential (TEP) amplitude and response consistency as these measures have been linked to cortical excitability but were not yet reported in migraine.We recorded 64-channel EEG during single-pulse TMS on the vertex interictally in 10 people with migraine with aura and 10 healthy controls matched for age, sex and resting motor threshold. On average 160 pulses around resting motor threshold were delivered through a circular coil in clockwise and counterclockwise direction. Trial-averaged TEP responses, frequency spectra and phase clustering (over the entire scalp as well as in frontal, central and occipital midline electrode clusters) were compared between groups, including comparison to sham-stimulation evoked responses.Migraine and control groups had a similar distribution of TEP waveforms over the scalp. In migraine with aura, TEP responses showed reduced amplitude around the frontal and occipital N100 peaks. For the migraine and control groups, responses over the scalp were affected by current direction for the primary motor cortex, somatosensory cortex and sensory association areas, but not for frontal, central or occipital midline clusters.This study provides evidence of altered TEP responses in-between attacks in migraine with aura. Decreased TEP responses around the N100 peak may be indicative of reduced cortical GABA-mediated inhibition and expand observations on enhanced cortical excitability from earlier migraine studies using more indirect measurements.

Tracking cortical excitability dynamics with transcranial magnetic stimulation in focal epilepsy.

INTRODUCTION: The lack of reliable biomarkers constrain epilepsy management. We assessed the potential of repeated transcranial magnetic stimulation with electromyography (TMS-EMG) to track dynamical changes in cortical excitability on a within-subject basis. METHODS: We recruited people with refractory focal epilepsy who underwent video-EEG monitoring and drug tapering as part of the presurgical evaluation. We performed daily TMS-EMG measurements with additional postictal assessments 1-6 h following seizures to assess resting motor threshold (rMT), and motor evoked potentials (MEPs) with single- and paired-pulse protocols. Anti-seizure medication (ASM) regimens were recorded for the day before each measurement and expressed in proportion to the dosage before tapering. Additional measurements were performed in healthy controls to evaluate day-to-day rMT variability. RESULTS: We performed 77 (58 baseline, 19 postictal) measurements in 16 people with focal epilepsy and 35 in seven healthy controls. Controls showed minimal day-to-day rMT variation. Withdrawal of ASMs was associated with a lower rMT without affecting MEPs of single- and paired-pulse TMS-EMG paradigms. Postictal measurements following focal to bilateral tonic-clonic seizures demonstrated unaltered rMT and increased short interval intracortical inhibition, while measurements following focal seizures with impaired awareness showed decreased rMT's and reduced short and long interval intracortical inhibition. CONCLUSION: Serial within-subject rMT measurements yielded reproducible, stable results in healthy controls. ASM tapering and seizures had distinct effects on TMS-EMG excitability indices in people with epilepsy. Drug tapering decreased rMT, indicating increased overall corticospinal excitability, whereas seizures affected intracortical inhibition with contrasting effects between seizure types.

Structural mapping of GABRB3 variants reveals genotype-phenotype correlations.

PURPOSE: Pathogenic variants in GABRB3 have been associated with a spectrum of phenotypes from severe developmental disorders and epileptic encephalopathies to milder epilepsy syndromes and mild intellectual disability (ID). In this study, we analyzed a large cohort of individuals with GABRB3 variants to deepen the phenotypic understanding and investigate genotype-phenotype correlations. METHODS: Through an international collaboration, we analyzed electro-clinical data of unpublished individuals with variants in GABRB3, and we reviewed previously published cases. All missense variants were mapped onto the 3-dimensional structure of the GABRB3 subunit, and clinical phenotypes associated with the different key structural domains were investigated. RESULTS: We characterized 71 individuals with GABRB3 variants, including 22 novel subjects, expressing a wide spectrum of phenotypes. Interestingly, phenotypes correlated with structural locations of the variants. Generalized epilepsy, with a median age at onset of 12 months, and mild-to-moderate ID were associated with variants in the extracellular domain. Focal epilepsy with earlier onset (median: age 4 months) and severe ID were associated with variants in both the pore-lining helical transmembrane domain and the extracellular domain. CONCLUSION: These genotype-phenotype correlations will aid the genetic counseling and treatment of individuals affected by GABRB3-related disorders. Future studies may reveal whether functional differences underlie the phenotypic differences.

Changes in motor nerve excitability in acute phase Guillain-Barré syndrome.

BACKGROUND: The most common subtypes of Guillain-Barré syndrome (GBS) are acute inflammatory demyelinating polyneuropathy (AIDP) and acute motor axonal neuropathy (AMAN). In the first days after the onset of weakness, standard nerve conduction studies (NCS) may not distinguish GBS subtypes. Reduced nerve excitability may be an early symptom of nerve dysfunction, which can be determined with the compound muscle action potential (CMAP) scan. The aim of this study was to explore whether early changes in motor nerve excitability in GBS patients are related to various subtypes. METHODS: Prospective case-control study in 19 GBS patients from The Netherlands and 22 from Bangladesh. CMAP scans were performed within 2 days of hospital admission and NCS 7-14 days after onset of weakness. CMAP scans were also performed in age- and country-matched controls. RESULTS: CMAP scan patterns of patients who were classified as AMAN were distinctly different compared to the CMAP scan patterns of the patients who were classified as AIDP. The most pronounced differences were found in the stimulus intensity parameters. CONCLUSIONS: CMAP scans made at hospital admission demonstrate several characteristics that can be used as an early indicator of GBS subtype.

Determining the Spike-Wave Index Using Automated Detection Software.

PURPOSE: The spike-wave index (SWI) is a key feature in the diagnosis of electrical status epilepticus during slow-wave sleep. Estimating the SWI manually is time-consuming and is subject to interrater and intrarater variability. Use of automated detection software would save time. Thereby, this software will consistently detect a certain EEG phenomenon as epileptiform and is not influenced by human factors. To determine noninferiority in calculating the SWI, we compared the performance of a commercially available spike detection algorithm (P13 software, Persyst Development Corporation, San Diego, CA) with human expert consensus. METHODS: The authors identified all prolonged EEG recordings for the diagnosis or follow-up of electrical status epilepticus during slow-wave sleep carried out from January to December 2018 at an epilepsy tertiary referral center. The SWI during the first 10 minutes of sleep was estimated by consensus of two human experts. This was compared with the SWI calculated by the automated spike detection algorithm using the three available sensitivity settings: "low," "medium," and "high." In the software, these sensitivity settings are denoted as perception values. RESULTS: Forty-eight EEG recordings from 44 individuals were analyzed. The SWIs estimated by human experts did not differ from the SWIs calculated by the automated spike detection algorithm in the "low" perception mode (P = 0.67). The SWIs calculated in the "medium" and "high" perception settings were, however, significantly higher than the human expert estimated SWIs (both P < 0.001). CONCLUSIONS: Automated spike detection (P13) is a useful tool in determining SWI, especially when using the "low" sensitivity setting. Using such automated detection tools may save time, especially when reviewing larger epochs.

Absence epilepsy: Characteristics, pathophysiology, attention impairments, and the related risk of accidents. A narrative review.

OBJECTIVE: Absence epilepsy (AE) is related to both cognitive and physical impairments. In this narrative review, we critically discuss the pathophysiology of AE and the impairment of attention in children and adolescents with AE. In particular, we contextualize the attentive dysfunctions of AE with the associated risks, such as accidental injuries. DATA SOURCE: An extensive literature search on attention deficits and the rate of accidental injuries in AE was run. The search was conducted on Scopus, Pubmed, and the online libraries of the University of Twente and Maastricht University. Relevant references of the included articles were added. Retrospective and prospective studies, case reports, meta-analysis, and narrative reviews were included. Only studies written in English were considered. Date of last search is February 2020. The keywords used were "absence epilepsy" AND "attention"/"awareness", "absence epilepsy" AND "accidental injuries"/"accident*"/"injuries". RESULTS: Ten retrospective and two prospective studies on cognition and AE were fully screened. Seventeen papers explicitly referring to attention in AE were reviewed. Just one paper was found to specifically focus on accidental injuries and AE, while twelve studies generally referring to epilepsy syndromes - among which AE - and related accidents were included. CONCLUSION: Absence epilepsy and attention deficits show some patterns of pathophysiological association. This relation may account for dysfunctions in everyday activities in the pediatric population. Particular metrics, such as the risk related to biking in children with AE, should be used in future studies to address the problem in a novel way and to impact clinical indications.

Using sampled visual EEG review in combination with automated detection software at the EMU.

PURPOSE: Complete visual review of prolonged video-EEG recordings at an EMU (Epilepsy Monitoring Unit) is time consuming and can cause problems in times of paucity of educated personnel. In this study we aimed to show non inferiority for electroclinical diagnosis using sampled review in combination with EEG analysis softreferware (P13 software, Persyst Corporation), in comparison to complete visual review. METHOD: Fifty prolonged video-EEG recordings in adults were prospectively evaluated using sampled visual EEG review in combination with automated detection software of the complete EEG record. Visually assessed samples consisted of one hour during wakefulness, one hour during sleep, half an hour of wakefulness after wake-up and all clinical events marked by the individual and/or nurses. The final electro-clinical diagnosis of this new review approach was compared with the electro-clinical diagnosis after complete visual review as presently used. RESULTS: The electro-clinical diagnosis based on sampled visual review combined with automated detection software did not differ from the diagnosis based on complete visual review. Furthermore, the detection software was able to detect all records containing epileptiform abnormalities and epileptic seizures. CONCLUSION: Sampled visual review in combination with automated detection using Persyst 13 is non-inferior to complete visual review for electroclinical diagnosis of prolonged video-EEG at an EMU setting, which makes this approach promising.

Effective Cerebral Perfusion Pressure: Does the Estimation Method Make a Difference?

INTRODUCTION: The effective cerebral perfusion pressure (CPPe), zero-flow pressure (ZFP), and resistance area product (RAP) are important determinants of cerebral blood flow. ZFP and RAP are usually estimated by linear regression analysis of pressure-velocity relationships of the middle cerebral artery. The aim of this study was to validate 4 other estimation methods against the standard linear regression method. METHODS: In a previous study, electroencephalography, arterial blood pressure, and middle cerebral artery flow velocity were measured in patients during internal cardioverter defibrillator implantation procedures to determine the electroencephalography frequency ranges that represent ischemic changes during periods of circulatory arrest. In this secondary analysis, arterial blood pressure and middle cerebral artery flow velocity were used to estimate CPPe, ZFP, and RAP by 4 different methods-the 3-point intercept calculation (LR3, systolic/mean/diastolic) and methods described by Czosnyka (systolic/diastolic), Belford (mean/diastolic), and Schmidt (systolic/diastolic)-and compare them with the reference linear regression method. CPPe was calculated as the difference between mean arterial pressure and ZFP. The primary endpoint was the difference, correlation, and agreement of these differently estimated CPPe measurements. RESULTS: In total, 174 measurements in 35 patients were collected under steady-state conditions before the first circulatory arrest phase during internal cardioverter defibrillator testing. CPPe, ZFP, and RAP measurements based on the 3-point intercept and Czosnyka calculation methods showed small mean differences, good agreement, low percentage errors, and excellent correlation when compared with the reference method. Agreement and correlation were moderate for the Belford method and unsatisfactory for the Schmidt method. CONCLUSIONS: CPPe, ZFP, and RAP measurements based on 2 alternative calculation methods are comparable to the linear regression reference method.

Epilepsy monitoring units can be safe places; a prospective study in a large cohort.

OBJECTIVE: No international guideline is available for minimum safety measures at epilepsy monitoring units (EMUs), although recommendations for preferred practices exist. These are mostly based on expert opinion, without evidence of effectiveness. We do not apply all of these preferred practices at our EMU setting. We audited adverse events and diagnostic utility at our EMU over one year. METHODS: From May 2018 to May 2019, we prospectively collected data concerning adverse events and diagnostic utility of all EMU admissions (noninvasive video-electroencephalogram (EEG) recordings); during these admissions, individuals can be ambulant within their EMU room. RESULTS: There were 1062 admissions comprising 1518 EMU days. In 2% of the admissions, a complication occurred, mostly a fall without injury (n = 6). In almost half of the falls, this was from the bed. Complications occurred most often during admissions for presurgical evaluation. Antiseizure medication (ASM) was tapered in 86% of presurgical cases, but no serious injury occurred, and occurring seizures were effectively treated with intranasal midazolam if needed. CONCLUSIONS: The overall adverse event rate was low. Falls are the most common adverse event comparable with previously published fall rates at other EMUs where people are restricted to their bed. We showed that restricted ambulation at a well-monitored EMU is not necessary and possibly unwanted. No serious injury due to tapering of ASM occurred, and intranasal midazolam was shown to be effective as acute seizure treatment.

European Consensus Guidelines on the Management of Respiratory Distress Syndrome - 2019 Update.

As management of respiratory distress syndrome (RDS) advances, clinicians must continually revise their current practice. We report the fourth update of "European Guidelines for the Management of RDS" by a European panel of experienced neonatologists and an expert perinatal obstetrician based on available literature up to the end of 2018. Optimising outcome for babies with RDS includes prediction of risk of preterm delivery, need for appropriate maternal transfer to a perinatal centre and timely use of antenatal steroids. Delivery room management has become more evidence-based, and protocols for lung protection including initiation of CPAP and titration of oxygen should be implemented immediately after birth. Surfactant replacement therapy is a crucial part of management of RDS, and newer protocols for its use recommend early administration and avoidance of mechanical ventilation. Methods of maintaining babies on non-invasive respiratory support have been further developed and may cause less distress and reduce chronic lung disease. As technology for delivering mechanical ventilation improves, the risk of causing lung injury should decrease, although minimising time spent on mechanical ventilation using caffeine and, if necessary, postnatal steroids are also important considerations. Protocols for optimising general care of infants with RDS are also essential with good temperature control, careful fluid and nutritional management, maintenance of perfusion and judicious use of antibiotics all being important determinants of best outcome.

Phase clustering in transcranial magnetic stimulation-evoked EEG responses in genetic generalized epilepsy and migraine.

BACKGROUND: Epilepsy and migraine are paroxysmal neurological conditions associated with disturbances of cortical excitability. No useful biomarkers to monitor disease activity in these conditions are available. Phase clustering was previously described in electroencephalographic (EEG) responses to photic stimulation and may be a potential epilepsy biomarker. OBJECTIVE: The objective of this study was to investigate EEG phase clustering in response to transcranial magnetic stimulation (TMS), compare it with photic stimulation in controls, and explore its potential as a biomarker of genetic generalized epilepsy or migraine with aura. METHODS: People with (possible) juvenile myoclonic epilepsy (JME), migraine with aura, and healthy controls underwent single-pulse TMS with concomitant EEG recording during the interictal period. We compared phase clustering after TMS with photic stimulation across the groups using permutation-based testing. RESULTS: We included eight people with (possible) JME (five off medication, three on), 10 with migraine with aura, and 37 controls. The TMS and photic phase clustering spectra showed significant differences between those with epilepsy without medication and controls. Two phase clustering-based indices successfully captured these differences between groups. One participant was tested multiple times. In this case, the phase clustering-based indices were inversely correlated with the dose of antiepileptic medication. Phase clustering did not differ between people with migraine and controls. CONCLUSION: We present methods to quantify phase clustering using TMS-EEG and show its potential value as a measure of brain network activity in genetic generalized epilepsy. Our results suggest that the higher propensity to phase clustering is not shared between genetic generalized epilepsy and migraine.

Automated remote fall detection using impact features from video and audio.

Elderly people and people with epilepsy may need assistance after falling, but may be unable to summon help due to injuries or impairment of consciousness. Several wearable fall detection devices have been developed, but these are not used by all people at risk. We present an automated analysis algorithm for remote detection of high impact falls, based on a physical model of a fall, aiming at universality and robustness. Candidate events are automatically detected and event features are used as classifier input. The algorithm uses vertical velocity and acceleration features from optical flow outputs, corrected for distance from the camera using moving object size estimation. A sound amplitude feature is used to increase detector specificity. We tested the performance and robustness of our trained algorithm using acted data from a public database and real life data with falls resulting from epilepsy and with daily life activities. Applying the trained algorithm to the acted dataset resulted in 90% sensitivity for detection of falls, with 92% specificity. In the real life data, six/nine falls were detected with a specificity of 99.7%; there is a plausible explanation for not detecting each of the falls missed. These results reflect the algorithm's robustness and confirms the feasibility of detecting falls using this algorithm.

Improving staff response to seizures on the epilepsy monitoring unit with online EEG seizure detection algorithms.

OBJECTIVE: User safety and the quality of diagnostics on the epilepsy monitoring unit (EMU) depend on reaction to seizures. Online seizure detection might improve this. While good sensitivity and specificity is reported, the added value above staff response is unclear. We ascertained the added value of two electroencephalograph (EEG) seizure detection algorithms in terms of additional detected seizures or faster detection time. METHODS: EEG-video seizure recordings of people admitted to an EMU over one year were included, with a maximum of two seizures per subject. All recordings were retrospectively analyzed using Encevis EpiScan and BESA Epilepsy. Detection sensitivity and latency of the algorithms were compared to staff responses. False positive rates were estimated on 30 uninterrupted recordings (roughly 24 h per subject) of consecutive subjects admitted to the EMU. RESULTS: EEG-video recordings used included 188 seizures. The response rate of staff was 67%, of Encevis 67%, and of BESA Epilepsy 65%. Of the 62 seizures missed by staff, 66% were recognized by Encevis and 39% by BESA Epilepsy. The median latency was 31 s (staff), 10 s (Encevis), and 14 s (BESA Epilepsy). After correcting for walking time from the observation room to the subject, both algorithms detected faster than staff in 65% of detected seizures. The full recordings included 617 h of EEG. Encevis had a median false positive rate of 4.9 per 24 h and BESA Epilepsy of 2.1 per 24 h. CONCLUSIONS: EEG-video seizure detection algorithms may improve reaction to seizures by improving the total number of seizures detected and the speed of detection. The false positive rate is feasible for use in a clinical situation. Implementation of these algorithms might result in faster diagnostic testing and better observation during seizures.

Automated video-based detection of nocturnal convulsive seizures in a residential care setting.

People with epilepsy need assistance and are at risk of sudden death when having convulsive seizures (CS). Automated real-time seizure detection systems can help alert caregivers, but wearable sensors are not always tolerated. We determined algorithm settings and investigated detection performance of a video algorithm to detect CS in a residential care setting. The algorithm calculates power in the 2-6 Hz range relative to 0.5-12.5 Hz range in group velocity signals derived from video-sequence optical flow. A detection threshold was found using a training set consisting of video-electroencephalogaphy (EEG) recordings of 72 CS. A test set consisting of 24 full nights of 12 new subjects in residential care and additional recordings of 50 CS selected randomly was used to estimate performance. All data were analyzed retrospectively. The start and end of CS (generalized clonic and tonic-clonic seizures) and other seizures considered desirable to detect (long generalized tonic, hyperkinetic, and other major seizures) were annotated. The detection threshold was set to the value that obtained 97% sensitivity in the training set. Sensitivity, latency, and false detection rate (FDR) per night were calculated in the test set. A seizure was detected when the algorithm output exceeded the threshold continuously for 2 seconds. With the detection threshold determined in the training set, all CS were detected in the test set (100% sensitivity). Latency was ≤10 seconds in 78% of detections. Three/five hyperkinetic and 6/9 other major seizures were detected. Median FDR was 0.78 per night and no false detections occurred in 9/24 nights. Our algorithm could improve safety unobtrusively by automated real-time detection of CS in video registrations, with an acceptable latency and FDR. The algorithm can also detect some other motor seizures requiring assistance.

Caffeine and seizures: A systematic review and quantitative analysis.

PURPOSE: Caffeine is the most commonly used central nervous system (CNS) stimulant. The relationship between caffeine, seizures, epilepsy, and antiepileptic drugs (AEDs) is complex and not fully understood. Case reports suggest that caffeine triggers seizures in susceptible people. Our systematic review reports on the relationship between caffeine, seizures, and drugs in animal and human studies. Quantitative analyses were also done on animal studies regarding the effects of caffeine on AEDs. METHODS: PubMed was searched for studies assessing the effects of caffeine on seizure susceptibility, epilepsy, and drug interactions in people and in animal models. To quantify the interaction between AEDs and caffeine, the data of six animal studies were pooled and analyzed using a general linear model univariate analysis or One-way Analysis of Variance (ANOVA). RESULTS: In total, 442 items were identified from which we included 105 studies. Caffeine can increase seizure susceptibility and protect from seizures, depending on the dose, administration type (chronic or acute), and the developmental stage at which caffeine exposure started. In animal studies, caffeine decreased the antiepileptic potency of some drugs; this effect was strongest in topiramate. CONCLUSION: Preclinical studies suggest that caffeine increases seizure susceptibility. In some cases, chronic use of caffeine may protect against seizures. Caffeine lowers the efficacy of several drugs, especially topiramate. It is unclear how these findings in models can be translated to the clinical condition. Until clinical studies suggest otherwise, caffeine intake should be considered as a factor in achieving and maintaining seizure control in epilepsy.