Correlation between EEG during AED withdrawal and epilepsy recurrence: a meta-analysis

[Discontinuation of antiseizure medication in patients with epilepsy]

BACKGROUND

Approximately two thirds of patients with epilepsy become seizure-free with antiseizure medication (ASM). A central question is whether and when ASM can be discontinued.

OBJECTIVE

To present an overview of the current knowledge about risks and benefits of discontinuation of ASM.

MATERIAL AND METHODS

Review of the current literature, discussion of data on and recommendations for discontinuation of ASM.

RESULTS

The risk of seizure recurrence after discontinuation of ASM is approximately 40-50% and thus twice as high as continuing with ASM. Guidelines recommend considering discontinuation of ASM at earliest after a seizure-free period of 2 years. Predictive variables for seizure recurrence after stopping ASM include longer duration of epilepsy and higher number of seizures until remission, a shorter seizure-free interval until stopping ASM, older age at epilepsy onset, developmental delay or IQ < 70, febrile seizures in childhood, absence of a self-limiting epilepsy syndrome, and evidence of epileptiform activity in the electroencephalograph (EEG). The individual risk of seizure recurrence after stopping ASM can be estimated using an online prediction tool.

CONCLUSION

Discontinuation of ASM should be discussed with patients at the earliest after 2 years of seizure freedom in a shared decision-making process weighing up the risks and benefits. The risk of a seizure recurrence depends on a number of clinical variables. Psychosocial aspects, such as impact on driving and occupational issues must be taken into consideration as well as individual fears and concerns of patients about seizure recurrence or the long-term use of ASM.

A meta-analysis of the relationship between abnormal pretreatment EEG and epilepsy recurrence

BACKGROUND

Researchers have studied the risk factors for epilepsy recurrence among patients who withdraw from antiseizure medication (ASM). These studies aimed to determine the optimal time for ASM withdrawal. EEG findings are one of the risk factors that has been studied. However, it remains unclear whether abnormal pretreatment EEG findings are a risk factor for recurrence after ASM withdrawal. We performed this meta-analysis to clarify this issue.

METHODS

We retrieved literature from the PubMed and Embase databases, and used the NewcastleOttawa Scale to evaluate the methodological quality of the included studies. RevMan 5.3 software was used to analyse the data.

RESULTS

In total,710 articles were retrieved from the databases. Ultimately, after screening, 11 articles involving 1686 patients with epilepsy were included. Compared with that for a normal EEG, the odds ratio (OR) for an abnormal EEG was 1.10 (P=0.50), with an I2 value of 32% (P=0.15). Subgroup analysis revealed that the children-to-adolescents subgroup had an OR of 1.21 (P=0.27), and the children-to-adults subgroup had an OR of 0.64 (P=0.14) for an abnormal EEG. A separate subgroup analysis revealed that the focal epilepsy subgroup had an OR of 1.30 (P=0.37), and the generalized epilepsy and focal epilepsy subgroup had an OR of 1.07 (P=0.67) for an abnormal EEG.

CONCLUSIONS

The risk of epilepsy recurrence is not related to pretreatment EEG findings, regardless of age or epilepsy classification. The associations of pre- and posttreatment EEG alterations with epilepsy recurrence are controversial. Due to the limitations of our article, further research is needed.

Postoperative interictal epileptiform discharges predict seizure recurrence after antiepileptic drug withdrawal regardless of concordance with surgical site

Objective

The study aimed to explore the association between the site of interictal epileptic discharges (IEDs) on postoperative electroencephalogram (EEG) and seizure recurrence after antiepileptic drug (AED) withdrawal. The study hypothesizes that the concordance of IED sites with surgical sites indicates incomplete resection of epileptic focus, while non-concordance of IED sites with surgical sites indicates postoperative changes or cortical stimulation. The former has a higher risk of seizure recurrence.

Methods

We retrospectively analyzed the postoperative EEG pattern of 182 consecutive children who underwent resection surgery. To identify the risk factors for seizure recurrence, we compared the attributes of seizure recurred and seizure-free groups by univariate and multivariate analyses. AED tapering was standardized, involving a 25% reduction in the dose of a single type of AED every 2 weeks, independent of the presurgical AED load.

Results

We attempted AED withdrawal in 116 (63.7%) children. Twenty-eight (24.1%) children experienced seizure recurrence during or after AED withdrawal. A greater number of AEDs used at the time of surgery (p=0.005), incomplete resection (p=0.001), and presence of IED on postoperative EEG (p=0.011) are predictors of seizure recurrence. The completeness of resection and seizure recurrence after AED withdrawal were related to the presence of IED on the EEG, but not to the concordance of IED with surgical sites.

Conclusion

For children with abnormal EEG, the decision to discontinue AED should be made more cautiously, regardless of the relative location of the discharge site and the surgical site.

Brain tumor-related epilepsy management: A Society for Neuro-oncology (SNO) consensus review on current management

Tumor-related epilepsy (TRE) is a frequent and major consequence of brain tumors. Management of TRE is required throughout the course of disease and a deep understanding of diagnosis and treatment is key to improving quality of life. Gross total resection is favored from both an oncologic and epilepsy perspective. Shared mechanisms of tumor growth and epilepsy exist, and emerging data will provide better targeted therapy options. Initial treatment with antiseizure medications (ASM) in conjunction with surgery and/or chemoradiotherapy is typical. The first choice of ASM is critical to optimize seizure control and tolerability considering the effects of the tumor itself. These agents carry a potential for drug-drug interactions and therefore knowledge of mechanisms of action and interactions is needed. A review of adverse effects is necessary to guide ASM adjustments and decision-making. This review highlights the essential aspects of diagnosis and treatment of TRE with ASMs, surgery, chemotherapy, and radiotherapy while indicating areas of uncertainty. Future studies should consider the use of a standardized method of seizure tracking and incorporating seizure outcomes as a primary endpoint of tumor treatment trials.

Relapse After Drug Withdrawal in Patients with Epilepsy After Two Years of Seizure-Free: A Cohort Study

BACKGROUND AND STUDY AIMS

Antiepileptic drugs are the first choice of treatment for patients with epilepsy. However, the withdrawal of antiepileptic drugs after seizure-free remains a significant focus for the majority of patients with epilepsy and their families. In this study, we evaluated the risk factors associated with relapse after drug withdrawal in patients with seizure free for 2 years. We aimed to guide patients in seizure-free to assess the risk of drug withdrawal.

PATIENTS AND METHODS

Through screening, 452 patients with epilepsy were included in the study.Patients were followed up for at least 2 years or more. Analyzed their clinical data by applying the χ2-test, Kaplan-Meier survival analysis and multivariate Cox regression analysis.

RESULTS

423 patients completed follow-up, of which 304 cases recurred (71.9%).Related recurrence factors include age of onset, type of seizure, number of AEDs, seizure-free time before withdrawal, and electroencephalogram (EEG) results before drug withdrawal (P<0.05). The results of correlation analysis showed that age of onset, seizure frequency, seizure type, number of AEDs, the period from AEDs treatment to a seizure-free status, EEG results before drug withdrawal, and pre-medication course, were all significantly related to the recurrence of seizures after drug reduction and withdrawal (P<0.05). We identified a range of independent risk factors, including onset age, seizure frequency, Multiple AEDs and the period from AEDs treatment to a seizure-free status.

CONCLUSION

The overall recurrence rate of epilepsy in our patient cohort was high, and the peak recurrence period was within one-year of drug withdrawal. Patients with partial seizures, a short seizure-free time before withdrawal, severe EEG abnormalities before drug reduction, and a long course of the disease, are prone to relapse. Patients with an older age at onset and a high frequency of attack, those taking multi-drug combination therapy, and those that take a long time to gain control, should be managed carefully to AEDs withdrawal.

Risk factors of recurrence after drug withdrawal in children with epilepsy

This study aimed to evaluate the risk factors for recurrence in pediatric patients with epilepsy following normal antiseizure medication (ASM) treatment and drug withdrawal. We retrospectively analyzed 80 pediatric patients who received treatment at the Qilu Hospital of Shandong University between January 2009 and December 2019 after at least 2 years of seizure-free and normal electroencephalography (EEG) before the regular drug reduction. Patients were followed-up for at least 2 years and divided into the recurrence and nonrecurrence groups based on whether relapse occurred. Clinical information was gathered, and the risk variables for recurrence were statistically analyzed. Post 2 years of drug withdrawal, 19 patients showed relapses. The recurrence rate was 23.75%, and the mean time of recurrence was 11.09 ± 7.57 months, where 7 (36.8%) were women and 12 (63.2%) were men. In all, 41 pediatric patients were followed-up until the 3rd year, of which 2 (4.9%) patients experienced a relapse. Among the remaining 39 patients without relapse, 24 were followed-up until the 4th year, and no recurrence occurred. After being monitored for >4 years, 13 patients experienced no recurrence. The differences in the history of febrile seizures, combined use of ≥2 ASMs, and EEG abnormalities after drug withdrawal between the two groups were statistically significant (p < 0.05). Multivariate binary logistic regression analysis revealed that these factors are independent risk factors for recurrence after drug withdrawal in children with epilepsy: history of febrile seizures (OR = 4.322, 95% CI: 1.262-14.804), combined ASM use (OR = 4.783, 95% CI: 1.409-16.238), and EEG abnormalities after drug withdrawal (OR = 4.688, 95% CI: 1.154-19.050). In summary, our results suggest that the probability of seizure recurrence following drug cessation may be greatly increased by a history of febrile seizures, concomitant use of ≥2 ASMs, and EEG abnormalities after drug cessation. The majority of recurrences occurred in the first 2 years following drug discontinuation, whereas the rate of recurrence was minimal thereafter.

Academic attainment following pediatric epilepsy surgery: A systematic review

Academic skills, such as reading, spelling and arithmetic, are central to meaningful engagement with society throughout adolescence and into adulthood. The disruption caused by on-going seizure activity places children with drug-resistant epilepsy at a particularly high risk of poor academic attainment. Though epilepsy surgery during childhood has long-been associated with various cognitive changes, less is known of the extent to which pediatric epilepsy surgery impacts academic attainment. The aim of the present systematic review was to identify the nature of the effect of pediatric epilepsy surgery on the core academic skills of reading, writing, and arithmetic. The electronic databases Embase, Medline, PubMed, PsychInfo, OpenAire, and the ISRCTN registry were searched for studies examining academic attainment following epilepsy surgery in childhood, over the last three decades. Two thousand three-hundred and sixty-eight articles were screened for relevance. Thirteen studies met the inclusion criteria. Study quality and reliability were independently assessed by two reviewers. Results indicate that academic attainment primarily stabilizes in the first year following epilepsy surgery. Though changes to learning ability would not be expected in this early recovery phase, this review indicates that children do not, at least, lose the academic skills they have acquired before surgery. Postoperative declines in performance were most notably recorded in assessments of arithmetic, suggesting an area of potential vulnerability in this cohort. These declines were noted in cohorts with the longest periods between seizure onset and surgery. While older age at onset and seizure freedom correlated with improved academic attainment, further research is necessary to fully understand the specific effect of epilepsy surgery on academic attainment. Still, the present review provides valuable information regarding the likely academic outcomes in the early years following surgical treatment for drug-resistant epilepsy.

Risk of seizure relapse and long-term outcomes after discontinuation of antiseizure medication in children with epilepsy

OBJECTIVES

The aims of this study were to evaluate the demographic and clinical characteristics of children with epilepsy who discontinued their antiseizure medication (ASM), to determine potential predictors of seizure relapse, to calculate the rate of seizure relapse, and to detect long-term seizure outcomes.

METHODS

A total of 269 seizure-free children with epilepsy who were decided to discontinue their ASM and were followed up for at least 18 months after ASM withdrawal were retrospectively evaluated.

RESULTS

The enrolled children had been followed up for a median of 46 months (range 18-126 months; IQR: 29-61) after ASM withdrawal and 90 (33.5%) of their seizures relapsed. The median time to seizure relapse was 8 months (range 0.23-117 months; IQR: 2-25). Seizure relapse occurred in 16.7% of the 90 children at 1 month, 45.6% at 6 months, 62.2% at 1 year, 74.4% at 2 years, and 94.4% at 5 years. Univariate logistic regression analyses revealed six predictors significantly related to relapse: age at first seizure, age at diagnosis of epilepsy, intellectual disability, EEG findings after ASM withdrawal, ASM tapering time, and number of seizures on ASM. In multivariate logistic regression analyses, age at first seizure, intellectual disability, and ASM tapering time were not significantly associated anymore. The other three remained independently predictive. Pharmacological control of seizures with monotherapy was restored in 93.3% of the children with seizure relapse.

CONCLUSION

This study evaluated potential predictors of seizure relapse, some of which have rarely been evaluated in previous studies. Adolescent age at diagnosis, abnormal EEG findings after ASM withdrawal, and high number of seizures on ASM were associated with a higher risk of seizure relapse. Abnormal MRI findings such as malformations of cortical development and hydrocephalus may be potential biomarkers for the risk of seizure relapse.

Abnormal electroencephalogram (EEG) after drug withdrawal is a risk factor for epilepsy recurrence in children: a systematic review and meta-analysis

BACKGROUND

The relationship between abnormal electroencephalogram (EEG) and epilepsy recurrence after antiepileptic drug (AED) withdrawal has been controversial. We aimed to explore the relationship between abnormal EEG after AED withdrawal and the risk of epilepsy recurrence in children.

METHODS

Literature retrieval was performed using the PubMed, EMBASE, Medline, CENTRAL, and China National Knowledge Infrastructure (CNKI) databases. Included literatures were subjects of pediatric epilepsy patients who discontinued medication. The recurrence rate of epilepsy in patients with normal and abnormal EEG after AED withdrawal was observed. The Newcastle-Ottawa scale (NOS) was used to evaluate the quality of literatures. The Chi-square test was used to test heterogeneity. If heterogeneity between the articles existed, a random-effects model was used; otherwise, fixed-effects models were used. Subgroup analysis was used to explore the causes of heterogeneity. The odds ratio (OR) and 95% confidence interval (CI) were calculated using the Mantel-Haenszel statistical method. OR was not adjusted for other factors.

RESULTS

A total of 843 articles were retrieved. Nine studies were included, with a total of 1,663 patients, including 1,299 patients with normal EEG and 364 patients with abnormal EEG. Compared with the normal EEG patients, the OR of recurrence rate after AEDs withdrawal was 3.02 (P=0.0003), with heterogeneity (P<0.0001). The funnel plot indicated that there was no publication bias among the studies. The not partial seizure group analysis showed OR =1.70 (P=0.003) and no heterogeneity (P=0.70) in patients with abnormal EEG compared to those with normal EEG. In the partial seizures subgroup, the OR of the recurrence rate after AED withdrawal was 8.08 (P<0.00001) compared with the normal EEG patients, and there was no heterogeneity (P=0.29). The funnel chart shows that the partial seizures type subgroup analysis revealed positive results, while the not partial seizure group analysis reported negative results, indicating publication bias.

CONCLUSIONS

The risk of epilepsy recurrence is higher in children with abnormal EEG after AED withdrawal, regardless of seizure type. For pediatric epilepsy patients with abnormal EEG after AED withdrawal, a more cautious discontinuation regimen, closer follow-up and monitoring are required.

Patient-Perceived Health System Responsiveness of the Epilepsy Management Project in Rural China during the Period of COVID-19

Health system responsiveness (HSR) measures the experience of health-system users in terms of the non-clinical domains of the health system, which has been regarded as the three major goals of health performance evaluation. Good HSR may promote the use of health services and ultimately the health of patients. However, the HSR has not been measured as the main goal of the Epilepsy Management Project (EMP) in rural China. This study aims to evaluate the levels and distributions of the patient-perceived HSR of the EMP in rural China during the period of COVID-19 and identify its relevant factors so as to provide advice on the improvement of further strategies. Based on the key informant survey (KIS) of responsiveness from the World Health Organization proposal, we conducted a cross-sectional survey of 420 epilepsy patients selected proportional randomly from seven rural areas in the Hunan province of China in 2021. Eight domains of patients-perceived HSR were assessed by face-to-face interview. The overall HSR scored at a fairly “good” level of 8.3 (8.3 out of a maximum of 10.0). During the COVID-19 period, the scores of responsiveness domains were highest at 8.66 to 8.93 in “confidentiality”, “dignity” and “choice of providers”, while lowest at 8.38 to 8.53 in “prompt attention”, “social support” and “basic amenities”. The representative responsiveness equality index (REI) was 0.732, indicating the moderately balanced distributions of responsiveness of the EMP in rural China. Female, old age, and low education were significantly related to the lower HSR scores of rural EMP (p < 0.05). The HSR of EMP in rural China was fairly good. However, measures to improve the patient-perceived HSR are still needed, especially including better service, higher social support, and more comfortable medical environments.

EEG Essentials

PURPOSE OF REVIEW

EEG is the best study for evaluating the electrophysiologic function of the brain. The relevance of EEG is based on an accurate interpretation of the recording. Understanding the neuroscientific basis for EEG is essential. The basis for recording and interpreting EEG is both brain site-specific and technique-dependent to detect and represent a complex series of waveforms. Separating normal from abnormal EEG lies at the foundation of essential interpretative skills.

RECENT FINDINGS

Seizures and epilepsy are the primary targets for clinical use of EEG in diagnosis, seizure classification, and management. Interictal epileptiform discharges on EEG support a clinical diagnosis of seizures, but only when an electrographic seizure is recorded is the diagnosis confirmed. New variations of normal waveforms, benign variants, and artifacts can mimic epileptiform patterns and are potential pitfalls for misinterpretation for inexperienced interpreters. A plethora of medical conditions involve nonepileptiform and epileptiform abnormalities on EEG along the continuum of people who appear healthy to those who are critically ill. Emerging trends in long-term EEG monitoring to diagnose, classify, quantify, and characterize patients with seizures have unveiled epilepsy syndromes in patients and expanded medical and surgical options for treatment. Advances in terminology and application of continuous EEG help unify neurologists in the diagnosis of nonconvulsive seizures and status epilepticus in patients with encephalopathy and prognosticate recovery from serious neurologic injury involving the brain.

SUMMARY

After 100 years, EEG has retained a key role in the neurologist's toolkit as a safe, widely available, versatile, portable test of neurophysiology, and it is likely to remain at the forefront for patients with neurologic diseases. Interpreting EEG is based on qualitative review, and therefore, the accuracy of reporting is based on the interpreter's training, experience, and exposure to many new and older waveforms.

Comparison of Long-Term Outcomes of Monotherapy and Polytherapy in Seizure-Free Patients With Epilepsy Following Antiseizure Medication Withdrawal

Objective: The objectives of this study were to compare the risk and timing of seizure relapse in seizure-free patients with epilepsy following the withdrawal of monotherapy or polytherapy and to identify relevant influencing factors.

Methods: Patients who had achieved at least a 2-year seizure remission and started the withdrawal of antiseizure medication (ASM) were enrolled in this study. All patients were followed for at least 3 years or until seizure relapse. According to the number of ASMs at the time of withdrawalwas about twice than that, patients were divided into two groups: monotherapy group and polytherapy group. The Cox proportional hazards model was used to compare the recurrence risk of the two groups. Univariate analysis and multiple logistic regression analysis were used to analyze potential confounding variables between patients treated with monotherapy and polytherapy.

Results: A total of 188 patients (119 males and 69 females) were included. The average prescribed daily dose of most ASMs at the time of withdrawal was moderate or low (30–50% defined daily dose). The recurrence of most patients (89.2%) occurred within the first 3 years after withdrawal. The recurrence risk in patients treated with polytherapy at the time of withdrawal was about twice than that of the monotherapy group [p = 0.001, hazard ratio (HR) = 2.152, 95% confidence interval (CI) = 1.350–3.428]. Multivariate analysis showed that patients treated with polytherapy were significantly older at seizure onset [p = 0.024, odd ratio (OR) = 1.027, 95% CI = 1.004–1.052] and had a significantly longer duration of epilepsy before treatment (p = 0.004, OR = 1.009, 95% CI = 1.003–1.015) compared to patients in the monotherapy group. In addition, a history of perinatal injury was found to be an independent risk factor of seizure relapse in patients with ASM withdrawal.

Conclusion: The average prescribed daily dose of most ASMs at the time of withdrawal was moderate or low. Patients who received polytherapy at the time of withdrawal, particularly those with later seizure onset age and longer epilepsy duration before treatment, had a higher recurrence risk after ASMs withdrawal compared to patients treated with monotherapy.

Risk of seizure recurrence from antiepileptic drug withdrawal among seizure-free patients for more than two years

OBJECTIVE

The aim of this study was to determine the outcome of antiepileptic drug (AED) withdrawal in patients who were seizure-free for more than two years.

METHODS

Patients with epilepsy who were seizure-free for at least two years and decided to stop AED therapy gradually were followed up every two months for seizure relapse. The inclusion criteria were as follows: (1) diagnosis of epilepsy, defined as the following conditions: ① at least two unprovoked (or reflex) seizures occurring >24 h apart; ② one unprovoked (or reflex) seizure and a probability of further seizures similar to the general recurrence risk (at least 60%) after two unprovoked seizures, occurring over the next 10 years; ③ diagnosis of an epilepsy syndrome; (2) patients remained seizure-free for at least 24 consecutive months during AED therapy; and (3) patients expressed a desire to discontinue AED therapy gradually and agreed to return for regular follow-ups. The time to a seizure relapse and predictive factors were analyzed by survival methods, including sex; age at seizure onset; number of episodes; seizure-free period before AED withdrawal; duration of follow-up after AED withdrawal; AED tapering off period (taper period); results from brain magnetic resonance (MRI); electroencephalogram (EEG) after drug withdrawal; EEG before drug withdrawal; seizure type (classified as generalized, partial, or multiple types based on history); and the number of AEDs administered for long-term seizure control. A log-rank test was used for univariate analysis, and a Cox proportional hazard model was used for multivariate analysis.

RESULTS

We selected 94 patients (58 men, 36 women). The relapse ratio was 29.8%. Univariate analysis and multivariate Cox regression analysis indicated that withdrawal times and multiple AEDs, as well as the seizure-free period before withdrawal and abnormal EEG after drug withdrawal were significantly correlated with seizure recurrence and were significant independent predictive factors, with a hazard ratio of 0.839 and 3.971, 0.957, and 3.684, respectively.

SIGNIFICANCE

The relapse rate in our study was similar to commonly reported overall rates for epilepsy. Distinguishing variables, such as withdrawal times, multiple AEDs, seizure-free period before withdrawal, and abnormal EEG after drug withdrawal, need to be considered when choosing to withdraw from AEDs. Therefore, our recommendation is that after two years of seizure-free survival, patients could consider withdrawal unless they have hippocampal sclerosis (HS).

Multi-Head Self-Attention Model for Classification of Temporal Lobe Epilepsy Subtypes

As a long-standing chronic disease, Temporal Lobe Epilepsy (TLE), resulting from abnormal discharges of neurons and characterized by recurrent episodic central nervous system dysfunctions, has affected more than 70% of drug-resistant epilepsy patients across the world. As the etiology and clinical symptoms are complicated, differential diagnosis of TLE mainly relies on experienced clinicians, and specific diagnostic biomarkers remain unclear. Though great effort has been made regarding the genetics, pathology, and neuroimaging of TLE, an accurate and effective diagnosis of TLE, especially the TLE subtypes, remains an open problem. It is of a great importance to explore the brain network of TLE, since it can provide the basis for diagnoses and treatments of TLE. To this end, in this paper, we proposed a multi-head self-attention model (MSAM). By integrating the self-attention mechanism and multilayer perceptron method, the MSAM offers a promising tool to enhance the classification of TLE subtypes. In comparison with other approaches, including convolutional neural network (CNN), support vector machine (SVM), and random forest (RF), experimental results on our collected MEG dataset show that the MSAM achieves a supreme performance of 83.6% on accuracy, 90.9% on recall, 90.7% on precision, and 83.4% on F1-score, which outperforms its counterparts. Furthermore, effectiveness of varying head numbers of multi-head self-attention is assessed, which helps select the optimal number of multi-head. The self-attention aspect learns the weights of different signal locations which can effectively improve classification accuracy. In addition, the robustness of MSAM is extensively assessed with various ablation tests, which demonstrates the effectiveness and generalizability of the proposed approach.

Prediction of the recurrence risk in patients with epilepsy after the withdrawal of antiepileptic drugs

Many seizure-free patients who consider withdrawing from antiepileptic drugs (AEDs) hope to discontinue treatment to avoid adverse effects. However, withdrawal has certain risks that are difficult to predict. In this study, we performed a literature review, summarized the causes of significant variability in the risk of postwithdrawal recurrent seizures, and reviewed study data on the age at onset, cause, types of seizures, epilepsy syndrome, magnetic resonance imaging (MRI) abnormalities, epilepsy surgery, and withdrawal outcomes of patients with epilepsy. Many factors are associated with recurrent seizures after AED withdrawal. For patients who are seizure-free after treatment, the role of an electroencephalogram (EEG) alone in ensuring safe withdrawal is limited. A series of prediction models for the postwithdrawal recurrence risk have incorporated various potentially important factors in a comprehensive analysis. We focused on the populations of studies investigating five risk prediction models and analyzed the predictive variables and recommended applications of each model, aiming to provide a reference for personalized withdrawal for patients with epilepsy in clinical practice.

An online, interactive, screen-based simulator for learning basic EEG interpretation

OBJECTIVE

Develop and pilot test a simulator that presents ten commonly encountered representative clinical contexts for trainees to learn basic electroencephalogram (EEG) interpretation skills.

METHODS

We created an interactive web-based training simulator that allows self-paced, asynchronous learning and assessment of basic EEG interpretation skills. The simulator uses the information retrieval process via a free-response text box to enhance learning. Ten scenarios were created that present dynamic (scrolling) EEG tracings resembling the clinical setting, followed by questions with free-text answers. The answer was checked against an accepted word/phrase list. The simulator has been used by 76 trainees in total. We report pilot study results from the University of Florida's neurology residents (N = 24). Total percent correct for each scenario and average percent correct for all scenarios were calculated and correlated with most recent In-training Examination (ITE) and United States Medical License Examination (USMLE) scores.

RESULTS

Neurology residents' mean percent correct scenario scores ranged from 27.1-86.0% with an average scenario score of 61.2% ± 7.7. We showed a moderately strong correlation r = 0.49 between the ITE and the average scenario score.

CONCLUSION

We developed an online interactive EEG interpretation simulator to review basic EEG content and assess interpretation skills using an active retrieval approach. The pilot study showed a moderately strong correlation r = 0.49 between the ITE and the average scenario score. Since the ITE is a measure of clinical practice, this is evidence that the simulator can provide self-directed instruction and shows promise as a tool for assessment of EEG knowledge.