Pitfalls in the diagnosis and misdiagnosis of epilepsy

Is geographical variation in emergency epilepsy admissions related to variation in new epilepsy diagnoses among children and young people across England? An observational study using linked datasets

INTRODUCTION

Previous studies have reported widespread unexplained geographical variations in emergency paediatric admissions for epilepsy.

OBJECTIVES

Our aim was to investigate the extent to which geographical variation in epilepsy admissions among children and young people (CYP) aged 0-18 years, in England, reflects variation in new epilepsy diagnoses.

DESIGN AND SETTING

A retrospective secondary analysis of Hospital Episode Statistics data for emergency admissions between April 2018 and March 2019, and Epilepsy12 audit data for new epilepsy diagnoses in England, between July and November 2018.

OUTCOME MEASURES

The ratios of observed to expected epilepsy admissions and new diagnoses were calculated for each hospital Trust, based on their catchment population, and adjusted for age, sex and deprivation. Standardised ratios of observed to expected epilepsy admissions were plotted against standardised ratios of observed to expected new diagnoses of epilepsy at Trust level and the Pearson correlation coefficient was calculated.

RESULTS

There were 9246 emergency admissions for CYP to 134 Trusts with a primary diagnosis of epilepsy in England during the study period. 60 Trusts (44.4%) had either significantly lower or higher than expected standardised admission ratios for a primary diagnosis of epilepsy. There were 960 new diagnoses of epilepsy between July and November 2018 for 74 Trusts. 14 Trusts (18.9%) had either lower or higher standardised diagnosis ratios for a new diagnosis of epilepsy. There was no correlation between standardised emergency epilepsy admissions ratios and standardised new epilepsy diagnoses ratios at Trust level (Pearson r -0.06, p 0.63).

CONCLUSIONS

Widespread unexplained variation in epilepsy admissions cannot be explained by variation in new epilepsy diagnosis. This raises concerns about the equity and accessibility of epilepsy services. Unit-level benchmarking data on new diagnoses and admissions for epilepsy can inform strategies to improve access to care and health outcomes.

Network-based biomarkers in background electroencephalography in childhood epilepsies-A scoping review and narrative synthesis

BACKGROUND

Brain network analysis is an emerging field of research that could lead to the development, testing and validation of novel biomarkers for epilepsy. This could shorten the diagnostic uncertainty period, improve treatment, decrease seizure risk and lead to better management. This scoping review summarises the current state of electroencephalogram (EEG)-based network abnormalities for childhood epilepsies. The review assesses the overall robustness, potential generalisability, strengths, and limitations of the methodological frameworks of the identified research studies.

REPORTING METHODS

PRISMA guidelines for Scoping Reviews and the PICO framework was used to guide this review. Studies that evaluated candidate network-based features from EEG in children were retrieved from four international indexing databases (Cochrane Central / Embase / MEDLINE/ PsycINFO). Each selected study design, intervention characteristics, methodological design, potential limitations, and key findings were analysed.

RESULTS

Of 2,959 studies retrieved, nine were included. Studies used a group-level based comparison (e.g. based on a statistical test) or a classification-based method (e.g. based on a statistical model, such as a decision tree). A common limitation was the small sample-sizes (limiting further subgroup or confounder analysis) and the overall heterogeneity in epilepsy syndromes and age groups.

CONCLUSION

The heterogeneity of included studies (e.g. study design, statistical framework, outcome metrics) highlights the need for future studies to adhere to standardised frameworks (e.g. STARD) in order to develop standardised and robust methodologies. This would enable rigorous comparisons between studies, which is critical in assessing the potential of network-based approaches in developing novel biomarkers for childhood epilepsies.

Pro-Ictal EEG Scheduling Improves the Yield of Epilepsy Monitoring: Validating the Use of Multiday Seizure Cycles to Optimize Video-EEG Timing

OBJECTIVE

A significant challenge of video-electroencephalography (vEEG) in epilepsy diagnosis is timing monitoring sessions to capture epileptiform activity. In this study, we introduce and validate "pro-ictal EEG scheduling", a method to schedule vEEG monitoring to coincide with periods of increased seizure likelihood as a low-risk approach to enhance the diagnostic yield.

METHODS

A database of long-term ambulatory vEEG monitoring sessions (n = 5,038) of adults and children was examined. Data from linked electronic seizure diaries were extracted (minimum 10 self-reported events) to generate cycle-based estimates of seizure risk. In adults, vEEG monitoring sessions coinciding with periods of estimated high-risk were allocated to the high-risk group (n = 305) and compared to remaining studies (baseline: n = 3,586). Test of proportions and risk-ratios (RR) were applied to index differences in proportions and likelihood of capturing outcome measures (abnormal report, confirmed seizure, and diary event) during monitoring. The impact of clinical and demographic factors (age, sex, epilepsy-type, and medication) was also explored.

RESULTS

During vEEG monitoring, the high-risk group was significantly more likely to have an abnormal vEEG report (190/305:62% vs 1,790/3,586:50% [%change = 12%], RR = 1.25, 95% confidence interval [CI] = [1.137-1.370], p < 0.001), present with a confirmed seizure (56/305:18% vs 424/3,586:11% [%change = 7%], RR = 1.63, 95% CI = [1.265-2.101], p < 0.001) and report an event (153/305:50% vs 1,267/3,586:35% (%change = 15%), RR = 1.420, 95% CI = [1.259:1.602], p < 0.001). Similar effects were observed across clinical and demographic features.

INTERPRETATION

This study provides the first large-scale validation of pro-ictal EEG scheduling in improving the yield of vEEG. This innovative approach offers a pragmatic and low-risk strategy to enhance the diagnostic capabilities of vEEG monitoring, significantly impacting epilepsy management. ANN NEUROL 2024;96:1148-1159.

Preliminary development and validation of the Indonesian Pediatric Epilepsy Questionnaire (INA-PEPSI) to determine epilepsy and distinguish focal and generalized epilepsy in infants and children with unprovoked seizure in low-resource settings

OBJECTIVE

To outline the preliminary development and validation of a questionnaire for diagnosing epilepsy and distinguishing focal and generalized epilepsy among infants and children in Indonesia, where electroencephalography and pediatric neurologists are generally not available.

METHODS

A 10-question questionnaire comprising of 43 items was developed through literature review and expert panel discussions. Then, the questionnaire was administered by pediatricians to 75 children aged 1 month to 18 years old presenting with >1 episode of unprovoked seizures at an interval of >24 h. Subsequently, the questionnaire was assessed for content validity with item-level and scale-level content validity indices and ratio, construct validity with item-total correlation tests, criterion validity with diagnostic parameter assessments, and inter-rater reliability using Cohen's kappa (κ) and internal consistency with Cronbach's alpha (α) coefficient.

RESULTS

The questionnaire exhibited favorable internal validity and reliability in diagnosing epilepsy and distinguishing focal and generalized epilepsy, with excellent content (both indices and ratio at 1) and construct validity (rcount > rtable at p < 0.001), inter-rater reliability (κ = 0.86 and κ = 0.84), and internal consistency (α = 0.634 and α = 0.806). The questionnaire had a sensitivity and specificity of 96.4% (95%CI 89.1-99.5%) and 95.0% (79.5-99.6%) (area under the curve [AUC] 0.946 [0.900-0.992, p < 0.001]) in diagnosing epilepsy and 80.0% (57.4-95.7%) and 97.4% (89.7-99.2%) (AUC 0.889 [0.783-0.995, p < 0.001]) in distinguishing focal and generalized epilepsy, with a misdiagnosis rate of 4.0%.

SIGNIFICANCE

The questionnaire shows promising potential in diagnosing epilepsy and distinguishing focal and generalized epilepsy. Further external validation studies in larger and more diverse populations are required to confirm our findings.

PLAIN LANGUAGE SUMMARY

The diagnosis of epilepsy in children is challenging, particularly in resource-limited settings such as Indonesia, where advanced diagnostic tests and pediatric neurologists are scarce. The Indonesian Pediatric Epilepsy Questionnaire (INA-PEPSI) is designed to address these limitations by enabling healthcare professionals in Indonesia to diagnose epilepsy and classify its types without relying on advanced diagnostic tools. Although the questionnaire is still in the early stages of development and validation, this study demonstrates that the questionnaire exhibits good overall diagnostic performance in diagnosing epilepsy and distinguishing epilepsy types among Indonesian children.

The impact of paediatric epilepsy and co-occurring neurodevelopmental disorders on functional brain networks in wake and sleep

Epilepsy is one of the most common neurological disorders in children. Diagnosing epilepsy in children can be very challenging, especially as it often coexists with neurodevelopmental conditions like autism and ADHD. Functional brain networks obtained from neuroimaging and electrophysiological data in wakefulness and sleep have been shown to contain signatures of neurological disorders, and can potentially support the diagnosis and management of co-occurring neurodevelopmental conditions. In this work, we use electroencephalography (EEG) recordings from children, in restful wakefulness and sleep, to extract functional connectivity networks in different frequency bands. We explore the relationship of these networks with epilepsy diagnosis and with measures of neurodevelopmental traits, obtained from questionnaires used as screening tools for autism and ADHD. We explore differences in network markers between children with and without epilepsy in wake and sleep, and quantify the correlation between such markers and measures of neurodevelopmental traits. Our findings highlight the importance of considering the interplay between epilepsy and neurodevelopmental traits when exploring network markers of epilepsy.

Cerebrospinal fluid neuron specific enolase, interleukin-1β and erythropoietin concentrations in children after seizures

PURPOSE

In the present study, the levels of neuron-specific enolase (NSE), interleukin-1β (IL-1β), and erythropoietin (EPO) in cerebrospinal fluid (CSF) in children with idiopathic epilepsy were measured to illuminate the relationships between these markers with idiopathic epilepsy.

METHODS

Eighty-five children from 6 months to 12.5 years of age with single, previously undiagnosed, and untreated idiopathic epilepsy were participated in this study. The concentrations of CSF NSE, 1L-1β, and EPO were measured by specific ELISA methods.

RESULTS

The mean concentrations of CSF NSE, IL-1β, and EPO in the epileptic groups showed a significant increase (P < 0.01) compared with those in the control groups. Besides, the mutual correlations of NSE, 1L-1β, and EPO were also analyzed. Results showed that there were positive correlations between the levels of IL-1β, NSE, and EPO.

CONCLUSIONS

The changes of NSE, 1L-1β, and EPO level in CSF may be beneficial for the pathophysiology study of epileptic seizures and the identification and diagnosis of a seizure clinically.