The misdiagnosis of epilepsy

Computer-assisted analysis of routine EEG to identify hidden biomarkers of epilepsy: A systematic review

Background

Computational analysis of routine electroencephalogram (rEEG) could improve the accuracy of epilepsy diagnosis. We aim to systematically assess the diagnostic performances of computed biomarkers for epilepsy in individuals undergoing rEEG.

Methods

We searched MEDLINE, EMBASE, EBM reviews, IEEE Explore and the grey literature for studies published between January 1961 and December 2022. We included studies reporting a computational method to diagnose epilepsy based on rEEG without relying on the identification of interictal epileptiform discharges or seizures. Diagnosis of epilepsy as per a treating physician was the reference standard. We assessed the risk of bias using an adapted QUADAS-2 tool.

Results

We screened 10 166 studies, and 37 were included. The sample size ranged from 8 to 192 (mean=54). The computed biomarkers were based on linear (43%), non-linear (27%), connectivity (38%), and convolutional neural networks (10%) models. The risk of bias was high or unclear in all studies, more commonly from spectrum effect and data leakage. Diagnostic accuracy ranged between 64% and 100%. We observed high methodological heterogeneity, preventing pooling of accuracy measures.

Conclusion

The current literature provides insufficient evidence to reliably assess the diagnostic yield of computational analysis of rEEG.

Significance

We provide guidelines regarding patient selection, reference standard, algorithms, and performance validation.

Pitfalls in scalp EEG: Current obstacles and future directions

Although electroencephalography (EEG) serves a critical role in the evaluation and management of seizure disorders, it is commonly misinterpreted, resulting in avoidable medical, social, and financial burdens to patients and health care systems. Overinterpretation of sharply contoured transient waveforms as being representative of interictal epileptiform abnormalities lies at the core of this problem. However, the magnitude of these errors is amplified by the high prevalence of paroxysmal events exhibited in clinical practice that compel investigation with EEG. Neurology training programs, which vary considerably both in the degree of exposure to EEG and the composition of EEG didactics, have not effectively addressed this widespread issue. Implementation of competency-based curricula in lieu of traditional educational approaches may enhance proficiency in EEG interpretation amongst general neurologists in the absence of formal subspecialty training. Efforts in this regard have led to the development of a systematic, high-fidelity approach to the interpretation of epileptiform discharges that is readily employable across medical centers. Additionally, machine learning techniques hold promise for accelerating accurate and reliable EEG interpretation, particularly in settings where subspecialty interpretive EEG services are not readily available. This review highlights common diagnostic errors in EEG interpretation, limitations in current educational paradigms, and initiatives aimed at resolving these challenges.

Machine-learning for the prediction of one-year seizure recurrence based on routine electroencephalography

Predicting seizure recurrence risk is critical to the diagnosis and management of epilepsy. Routine electroencephalography (EEG) is a cornerstone of the estimation of seizure recurrence risk. However, EEG interpretation relies on the visual identification of interictal epileptiform discharges (IEDs) by neurologists, with limited sensitivity. Automated processing of EEG could increase its diagnostic yield and accessibility. The main objective was to develop a prediction model based on automated EEG processing to predict one-year seizure recurrence in patients undergoing routine EEG. We retrospectively selected a consecutive cohort of 517 patients undergoing routine EEG at our institution (training set) and a separate, temporally shifted cohort of 261 patients (testing set). We developed an automated processing pipeline to extract linear and non-linear features from the EEGs. We trained machine learning algorithms on multichannel EEG segments to predict one-year seizure recurrence. We evaluated the impact of IEDs and clinical confounders on performances and validated the performances on the testing set. The receiver operating characteristic area-under-the-curve for seizure recurrence after EEG in the testing set was 0.63 (95% CI 0.55-0.71). Predictions were still significantly above chance in EEGs with no IEDs. Our findings suggest that there are changes other than IEDs in the EEG signal embodying seizure propensity.

Interictal epileptiform discharges as a predictive biomarker for recurrence of poststroke epilepsy

Poststroke epilepsy is a major ischaemic/haemorrhagic stroke complication. Seizure recurrence risk estimation and early therapeutic intervention are critical, given the association of poststroke epilepsy with worse functional outcomes, quality of life and greater mortality. Several studies have reported risk factors for seizure recurrence; however, in poststroke epilepsy, the role of EEG in predicting the risk of seizures remains unclear. This multicentre observational study aimed to clarify whether EEG findings constitute a risk factor for seizure recurrence in patients with poststroke epilepsy. Patients with poststroke epilepsy were recruited from the PROgnosis of POst-Stroke Epilepsy study, an observational multicentre cohort study. The enrolled patients with poststroke epilepsy were those admitted at selected hospitals between November 2014 and June 2017. All patients underwent EEG during the interictal period during admission to each hospital and were monitored for seizure recurrence over 1 year. Board-certified neurologists or epileptologists evaluated all EEG findings. We investigated the relationship between EEG findings and seizure recurrence. Among 187 patients with poststroke epilepsy (65 were women with a median age of 75 years) admitted to the lead hospital, 48 (25.7%) had interictal epileptiform discharges on EEG. During the follow-up period (median, 397 days; interquartile range, 337-450 days), interictal epileptiform discharges were positively correlated with seizure recurrence (hazard ratio, 3.82; 95% confidence interval, 2.09-6.97; P < 0.01). The correlation remained significant even after adjusting for age, sex, severity of stroke, type of stroke and generation of antiseizure medications. We detected periodic discharges in 39 patients (20.9%), and spiky/sharp periodic discharges were marginally associated with seizure recurrence (hazard ratio, 1.85; 95% confidence interval, 0.93-3.69; P = 0.08). Analysis of a validation cohort comprising 187 patients with poststroke epilepsy from seven other hospitals corroborated the association between interictal epileptiform discharges and seizure recurrence. We verified that interictal epileptiform discharges are a risk factor for seizure recurrence in patients with poststroke epilepsy. Routine EEG may facilitate the estimation of seizure recurrence risk and the development of therapeutic regimens for poststroke epilepsy.

Machine learning and clinical neurophysiology

Clinical neurophysiology constructs a wealth of dynamic information pertaining to the integrity and function of both central and peripheral nervous systems. As with many technological fields, there has been an explosion of data in neurophysiology over recent years, and this requires considerable analysis by experts. Computational algorithms and especially advances in machine learning (ML) have the ability to assist with this task and potentially reveal hidden insights. In this update article, we will provide a brief overview where such technology is being applied in clinical neurophysiology and possible future directions.

The Occurrence and Relationship of Postoperative Seizure and de novo Epilepsy after Craniotomy Surgery: A Retrospective Single-Center Cohort Study

Objective

Postoperative seizures and epilepsy are common complications of craniotomy. In this study, we aimed to investigate the characteristics of seizures and epilepsy after craniotomy.

Methods

A total of 293 consecutive craniotomy surgeries were analyzed. Infratentorial surgeries, epilepsy surgeries, surgeries using the same approach conducted for the same patients, and the cases with incomplete clinical data were excluded. A total of 211 surgeries were included in this study. We evaluated the following clinical characteristics in all patients: sex, age, preoperative epilepsy, use of preoperative antiseizure medication (ASM), indication for operation, early postoperative seizure (EPS), delayed postoperative seizure (DPS), and postoperative de novo epilepsy. The day of onset of EPSs was defined as within 7 days post-surgery, and the day of onset of DPSs was defined as later than 7 days and less than 60 days post-surgery.

Results

Twenty-eight patients were previously diagnosed with epilepsy. Nine patients had EPSs (4.3%), and 10 patients had DPSs (4.7%). Seven cases of EPSs and six cases of DPSs were observed in 183 patients without previous epilepsy (3.8% and 3.3%, respectively). Three of the seven patients with EPSs (42.9%) and all six patients with DPSs (100%) developed de novo epilepsy. Postoperative de novo epilepsy was observed in 9 (4.9%) of the 183 patients without epilepsy. EPSs and DPSs were significant risk factors for epilepsy (p &lt; 0.01). The odds ratios of EPSs and DPSs for the development of epilepsy were 12.71 (95% confidence interval [CI]: 3.94–112.80; p &lt; 0.01) and 22.88 (95% CI: 5.38–55.72; p &lt; 0.01), respectively. ASM was administered prophylactically to 51 patients. The prophylactic use of ASMs did not prevent EPSs or postoperative de novo epilepsy.

Conclusion

EPSs and DPSs occurred in 4.3% and 4.7% of the patients, respectively, after craniotomy. Postoperative de novo epilepsy occurred in 4.9% of patients. This study revealed that EPSs and DPSs were risk factors for de novo epilepsy. Previous epilepsy was not a significant risk factor for EPSs. The prophylactic use of ASMs did not prevent EPSs or de novo epilepsy.

Minimum standards for inpatient long-term video-EEG monitoring: A clinical practice guideline of the international league against epilepsy and international federation of clinical neurophysiology

The objective of this clinical practice guideline is to provide recommendations on the indications and minimum standards for inpatient long-term video-electroencephalographic monitoring (LTVEM). The Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology develop guidelines aligned with the Epilepsy Guidelines Task Force. We reviewed published evidence using The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. We found limited high-level evidence aimed at specific aspects of diagnosis for LTVEM performed to evaluate patients with seizures and nonepileptic events (see Table S1). For classification of evidence, we used the Clinical Practice Guideline Process Manual of the American Academy of Neurology. We formulated recommendations for the indications, technical requirements, and essential practice elements of LTVEM to derive minimum standards used in the evaluation of patients with suspected epilepsy using GRADE (Grading of Recommendations, Assessment, Development, and Evaluation). Further research is needed to obtain evidence about long-term outcome effects of LTVEM and establish its clinical utility.

Minimum standards for inpatient long-term video-electroencephalographic monitoring: A clinical practice guideline of the International League Against Epilepsy and International Federation of Clinical Neurophysiology

The objective of this clinical practice guideline is to provide recommendations on the indications and minimum standards for inpatient long-term video-electroencephalographic monitoring (LTVEM). The Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology develop guidelines aligned with the Epilepsy Guidelines Task Force. We reviewed published evidence using the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) statement. We found limited high-level evidence aimed at specific aspects of diagnosis for LTVEM performed to evaluate patients with seizures and nonepileptic events. For classification of evidence, we used the Clinical Practice Guideline Process Manual of the American Academy of Neurology. We formulated recommendations for the indications, technical requirements, and essential practice elements of LTVEM to derive minimum standards used in the evaluation of patients with suspected epilepsy using GRADE (Grading of Recommendations Assessment, Development, and Evaluation). Further research is needed to obtain evidence about long-term outcome effects of LTVEM and to establish its clinical utility.

Meningitis and high-grade, second-degree atrioventricular block in an adolescent: causal effect or coincidence?

We describe an adolescent with Streptococcus pneumoniae meningitis and symptomatic high-grade, second-degree atrioventricular block requiring permanent pacemaker placement. It is difficult to ascertain if these two diagnoses were independent or had a causal relationship though ongoing symptoms were not present prior to the infection. Because of this uncertainty, awareness that rhythm disturbances can be cardiac in origin but also secondary to other aetiologies, such as infection, is warranted.

Can Assessment of the Tongue on Brain MRI Aid Differentiation of Seizure from Alternative Causes of Transient Loss of Consciousness?

BACKGROUND AND PURPOSE

Transient loss of consciousness is commonly evaluated in the emergency department. Although typically caused by epileptic seizure, syncope, or psychogenic nonepileptic seizure, the underlying etiology is frequently misdiagnosed. Lateral tongue bites are reportedly a specific clinical finding of seizure. We have observed tongue signal abnormality suggesting bite injury on brain MR imaging after seizures. We hypothesized an association between tongue signal abnormality and seizure diagnosis among patients in the emergency department imaged for transient loss of consciousness. Our purposes were to determine the prevalence of tongue signal abnormality among this population and the predictive performance for seizure diagnosis.

MATERIALS AND METHODS

For this retrospective study including 82 brain MR imaging examinations, 2 readers independently assessed tongue signal abnormality on T2-weighted and T2-weighted FLAIR images. Discrepancies were resolved by consensus, and interrater reliability (Cohen κ) was calculated. The final diagnosis was recorded. Proportions were compared using the Fisher exact test.

RESULTS

Tongue signal abnormality was present on 19/82 (23%) MR imaging examinations. Interrater reliability was "substantial" (κ = 0.77). Seizure was diagnosed among 18/19 (95%) patients with tongue signal abnormality and 29/63 (46%) patients without it (P < .001). In our cohort, tongue signal abnormality conveyed 97% specificity, 95% positive predictive value, and 63% accuracy for seizure diagnosis.

CONCLUSIONS

Tongue signal abnormality was observed in 23% of the study cohort and conveyed 97% specificity and 95% positive predictive value for seizure diagnosis. By assessing and reporting tongue signal abnormality, radiologists may facilitate a timely and accurate diagnosis of seizure among patients imaged for transient loss of consciousness.

Importance of access to epilepsy monitoring units during the COVID-19 pandemic: Consensus statement of the International League against epilepsy and the International Federation of Clinical Neurophysiology

Restructuring of healthcare services during the COVID-19 pandemic has led to lockdown of Epilepsy Monitoring Units (EMUs) in many hospitals. The ad-hoc taskforce of the International League Against Epilepsy (ILAE) and the International Federation of Clinical Neurophysiology (IFCN) highlights the detrimental effect of postponing video-EEG monitoring of patients with epilepsy and other paroxysmal events. The taskforce calls for action to continue functioning of Epilepsy Monitoring Units during emergency situations, such as the COVID-19 pandemic. Long-term video-EEG monitoring is an essential diagnostic service. Access to video-EEG monitoring of the patients in the EMUs must be given high priority. Patients should be screened for COVID-19, before admission, according to the local regulations. Local policies for COVID-19 infection control should be adhered to during the video-EEG monitoring. In cases of differential diagnosis where reduction of antiseizure medication is not required, consider home video-EEG monitoring as an alternative in selected patients.

Prevalence of Medically Resistant Epilepsy in Saudi Arabia

OBJECTIVES

The objective of this study was to evaluate the prevalence of medically resistant epilepsy (MRE) in our hospital and to compare the prevalence with that in other populations.

METHODS

We retrospectively analyzed the data of patients who visited the epilepsy clinics at King Fahd University Hospital, Al-Khobar, Saudi Arabia between January 2017 and December 2018. This study included patients aged ≥14 years who had at least 2 unprovoked seizures 24 h apart. Patients who had provoked seizure(s), paroxysmal events, or syncope or had incomplete medical records were excluded. The definition and classification of the International League Against Epilepsy were used. Moreover, we searched the En-glish literature using PubMed and Google Scholar to compare the prevalence of MRE between our population and other populations.

RESULTS

In total, 1,151 patients were screened, and 751 patients were included in the final analysis. Of the 751 patients, 229 (male: 56.3%, female: 43.7%; mean age: 32.07 years, and standard deviation, 12.2 years) had MRE, with a cumulative prevalence of 30%. The etiology was as follows: unknown, 63.3% (n = 145); structural, 31.9% (n = 73); genetic, 3.1% (n = 7); and infectious, 1.7% (n = 4). None of the patients had metabolic or immune-related etiologies.

CONCLUSION

The prevalence of MRE in our population (30%) is close to that in other populations (30-36.5%). Early identification of such patients is crucial to improve their management.

Non-epileptic paroxysmal events in paediatric patients: A single tertiary centre study in Egypt

PURPOSE

The misdiagnosis of non-epileptic seizures (NES) as epilepsy is one of the most common pitfalls in neuropsychiatric practice. This study aimed to describe the percentage and types of NES among children who were referred for a diagnosis of epilepsy in Upper Egypt.

METHODS

We recruited a total of 876 patients who were referred to Sohag University Hospital, a tertiary referral centre in Upper Egypt, for the evaluation of suspected epilepsy. Relevant methods for the diagnosis of epilepsy, including medical history and examination, EEG, video-EEG, laboratory investigations, and brain imaging, were performed for all study participants.

RESULTS

Among the 876 patients who were referred for the diagnosis of suspected epilepsy during the period from June 2017 to October 2018, 171 patients (19.5 %) were diagnosed as having NES. In general, we found that NES in the paediatric age groups did not differ from that reported in various studies across several different populations. The most prevalent NES in our study was breath-holding spells (32.2 %), followed by syncope (17.5 %), psychogenic nonepileptic seizures (12.3 %), motor tics (9.9 %), and benign sleep myoclonus (7.6 %). Other less frequent NES included infantile masturbation (7 %), spasmus nutans (5.3 %), migraine (2.9 %), benign paroxysmal torticollis (2.9 %), night terrors (1.8 %), and shuddering attacks (0.6 %).

CONCLUSION

Ideally, neurologists should not misdiagnose NES as epilepsy, and whenever the diagnosis of NES is uncertain, an accurate diagnosis should be made using long-term video-EEG monitoring, especially in younger paediatric patients.

Machine Learning Techniques for Personalized Detection of Epileptic Events in Clinical Video Recordings

Continuous patient monitoring is essential to achieve an effective and optimal patient treatment in the intensive care unit. In the specific case of epilepsy it is the only way to achieve a correct diagnosis and a subsequent optimal medication plan if possible. In addition to automatic vital sign monitoring, epilepsy patients need manual monitoring by trained personnel, a task that is very difficult to be performed continuously for each patient. Moreover, epileptic manifestations are highly personalized even within the same type of epilepsy. In this work we assess two machine learning methods, dictionary learning and an autoencoder based on long short-term memory (LSTM) cells, on the task of personalized epileptic event detection in videos, with a set of features that were specifically developed with an emphasis on high motion sensitivity. According to the strengths of each method we have selected different types of epilepsy, one with convulsive behaviour and one with very subtle motion. The results on five clinical patients show a highly promising ability of both methods to detect the epileptic events as anomalies deviating from the stable/normal patient status.

Optimized set of criteria for defining interictal epileptiform EEG discharges

OBJECTIVE

To find and validate the optimal combination of criteria that define interictal epileptiform EEG discharges (IEDs). Our target was a specificity over 95%, to avoid over-reading in clinical EEG.

METHODS

We constructed 63 combinations of the six criteria from the operational definition of IEDs, recently issued in the EEG-glossary of the International Federation of Clinical Neurophysiology (IFCN). The diagnostic gold standard was derived from video-EEG recordings. In a testing EEG dataset from 100 patients, we selected the best performing combinations of criteria and then we validated them in an independent dataset from 70 patients. We compared their performance with subjective, expert-scorings and we determined inter-rater agreement (IRA).

RESULTS

Without using criteria, the specificity of expert-scorings was lower than the pre-defined threshold (86%). The best performing combination of criteria was the following: waves with spiky morphology, followed by a slow-afterwave and voltage map suggesting a source in the brain. In the validation dataset this achieved a specificity of 97% and a sensitivity of 89%. IRA was substantial.

CONCLUSIONS

The optimized set of criteria for defining IEDs has high accuracy and IRA.

SIGNIFICANCE

Using these criteria will contribute to decreasing over-reading of EEG and avoid misdiagnosis of epilepsy.

Criteria for defining interictal epileptiform discharges in EEG: A clinical validation study

Objective

To define and validate criteria for accurate identification of EEG interictal epileptiform discharges (IEDs) using (1) the 6 sensor space criteria proposed by the International Federation of Clinical Neurophysiology (IFCN) and (2) a novel source space method. Criteria yielding high specificity are needed because EEG over-reading is a common cause of epilepsy misdiagnosis.

Methods

Seven raters reviewed EEG sharp transients from 100 patients with and without epilepsy (diagnosed definitively by video-EEG recording of habitual events). Raters reviewed the transients, randomized, and classified them as epileptiform or nonepileptiform in 3 separate rounds: in 2, EEG was reviewed in sensor space (scoring the presence/absence of each IFCN criterion for each transient or classifying unrestricted by criteria [expert scoring]); in the other, review and classification were performed in source space.

Results

Cutoff values of 4 and 5 criteria in sensor space and analysis in source space provided high accuracy (91%, 88%, and 90%, respectively), similar to expert scoring (92%). Two methods had specificity exceeding the desired threshold of 95%: using 5 IFCN criteria as cutoff and analysis in source space (both 95.65%); the sensitivity of these methods was 81.48% and 85.19%, respectively.

Conclusions

The presence of 5 IFCN criteria in sensor space and analysis in source space are optimal for clinical implementation. By extracting these objective features, diagnostic accuracy similar to expert scorings is achieved.

Classification of evidence

This study provides Class III evidence that IFCN criteria in sensor space and analysis in source space have high specificity (>95%) and sensitivity (81%–85%) for identification of IEDs.

Seizures as the first clinical manifestation of acute pulmonary embolism: an underestimate issue in neurocritical care

BACKGROUND

The aim of the present review is to analyze the clinical characteristics of patients with acute pulmonary embolism (PE) which seizures were the first clinical manifestation of the disease.

METHODS

After screening 258 articles in PubMed, Scopus, Cochrane Library, and Google Scholar databases, we identified 16 case reports meeting the inclusion criteria.

RESULTS

The mean age of the population was 48.4 ± 19.8 years (9 males and 7 females). About three of four patients (68.7%) were hemodynamically stable at admission, having a systolic blood pressure > 90 mmHg. Intriguingly, the doubt of acute PE was based on clinical suspicion or on instrumental findings in 62.5% and 18.7% of patients, respectively. In 3 subjects (18.7%), the acute cardiovascular disease was not suspected. Half of patients had an unremarkable previous medical history while neurological comorbidities were present in 4 patients (25.0%). During seizures, a transient loss of consciousness (TLOC) was reported in 6 cases. Seizures were retrospectively classified according to the 2017 ILAE classification, whenever possible. A focal and generalized onset was reported in 37.5% and 50% of cases, respectively, in 12.5% of patient's data that were insufficient to classify the events. The mean number of seizure episodes in the population enrolled was 2.0 ± 1.1. Mortality rate was 54.5% but one investigation did not report the patient's outcome.

CONCLUSIONS

The relationship between seizures and acute PE is probably underrecognized. Identifying patients that have a high probability of acute PE is fundamental to avoid any treatment delay and ameliorate their outcomes.

Electrocardiogram and cardiac testing among patients in the emergency department with seizure versus syncope

Objective

Cardiogenic syncope can present as a seizure. The distinction between seizure disorder and cardiogenic syncope can only be made if one considers the diagnosis. Our main objective was to identify whether patients presenting with a chief complaint (reason for visit) as seizure or syncope received an electrocardiogram in the emergency department across all age groups.

Methods

We conducted a secondary analysis of data collected in the 2010 to 2014 National Hospital Ambulatory Medical Care Survey comparing patients presenting with a chief complaint of syncope versus seizure to determine likelihood of getting an evaluation for possible life threatening cardiovascular disease. The primary endpoint was receiving an electrocardiogram in the emergency department; secondary endpoint was receiving cardiac biomarkers.

Results

There was a total of 144,094 patient encounters. Of these visits, 1,553 had syncope and 1,470 had seizure (60.3% vs. 44.2% female, 19.9% vs. 29.0% non-white). After adjusting for age, sex, mode of arrival and insurance, patients with syncope were more likely to receive an electrocardiogram compared to patients with seizure (odds ratio, 10.86; 95% confidence interval [CI], 8.52 to 13.84). This was true across all age groups (0 to 18 years, 56% vs. 7.5%; 18 to 44 years, 60% vs. 27%; 45 to 64 years, 82% vs. 41%; ≥65 years, 85% vs. 68%; P<0.01 for all). Car- diac biomarkers were also obtained more frequently in adult patients with syncope patients (18 to 44 years, 17.5% vs. 10.5%; 45 to 64 years, 33.8% vs. 21.4%; ≥65 years, 47.1% vs. 32.3%; P<0.01 for all).

Conclusion

Patients evaluated in the emergency department for syncope received an electrocar- diogram and cardiac biomarkers more frequently than those that had seizure.

Recurrent episodes of falls and amnestic confusional states as diagnostic challenge in the elderly

New-onset paroxysmal events in patients over 60 years of age are often diagnostically challenging owing to atypical presentation. Recurrent falls and transient states of confusion are especially common in the elderly population, yet their causes often remain undiagnosed due to concomitant cognitive deficits and motor impairments. We present an elderly patient with newly occurring ‘blackouts’ without obvious triggers and transient states of confusion for which he was amnestic. All neurological exams including brain MRI scan and routine electroencephalography (EEG) were normal. Long-term ECG monitoring using an event recorder captured an asystole during a habitual episode, leading to the diagnosis of syncope and pacemaker implantation. A subsequent video EEG monitoring performed due to ongoing unexplained confusional states revealed both bradycardia and long-lasting confusional states to be caused by unrecognised temporal lobe seizures. Ictal video EEG monitoring may play a crucial role in establishing a diagnosis of atypical temporal lobe seizures in the elderly.

Diagnostic criteria to aid the differential diagnosis of patients presenting with transient loss of consciousness: A systematic review

BACKGROUND

Transient loss of consciousness (TLOC) is a common presentation in primary care. Over 90% of these are due to epileptic seizures (ES), syncope, or psychogenic non-epileptic seizures (PNES). Misdiagnosis rates are as high as 30%.

METHODS

Systematic review of inter-ictal clinical criteria to aid differential diagnosis of TLOC. We searched Medline, EMBASE, CINAHL and PsycInfo databases, as well as relevant grey literature depositories and citations of relevant reviews and guidelines for studies giving sensitivity and specificity of inter-ictal clinical characteristics used to differentiate between causes of TLOC. Two independent reviewers selected studies for inclusion and performed critical appraisal of included articles. We performed a narrative synthesis of included studies.

RESULTS

Of 1023 results, 16 papers were included. Two compared syncope, ES, and PNES; all others compared ES and PNES. All were at significant risk of bias in at least one domain. 6 studied patient symptoms, 6 medical and social history, 3 witness reports and 1 examination findings. No individual criterion differentiated between diagnoses with high sensitivity and specificity.

CONCLUSIONS

There is a lack of validated diagnostic criteria to help clinicians assessing patients in primary or emergency care settings to discriminate between common causes of TLOC. Performance may be improved by combining sets of criteria in a clinical decision rule, but no such rule has been validated prospectively against gold-standard diagnostic criteria.

Burden of disease of people with epilepsy during an optimized diagnostic trajectory: costs and quality of life

BACKGROUND

Diagnosing epilepsy can be lengthy and stressful, potentially leading to increased use of healthcare resources and a reduction in quality of life.

AIM

This study aims to determine cost and quality of life before and after an optimized diagnostic procedure for people suspected of having epilepsy from a societal perspective with a follow-up of 12 months. In addition, this study aims to differentiate between people diagnosed with epilepsy during the follow-up of the study and the people who are diagnosed as not having epilepsy or for whom diagnosis is still uncertain.

METHODS

A questionnaire regarding the use of healthcare resources was used accompanied by the EQ-5D-3 L. Multiple imputations by chained equations with predictive mean matching was used to account for missing data. To investigate the uncertainty of the results, non-parametric bootstrapped (1000 times) was used.

RESULTS

In total, 116 people were included in the study. Total average costs per patient made in the previous 3 months had decreased from €4594 before the optimized diagnostic trajectory to €2609 in the 12 months after the optimized diagnostic trajectory. Healthcare costs were the largest expense group (52-66%) and had decreased significantly from baseline measurement to 12 months after baseline (€2395 vs €1581). Productivity costs had decreased from €1367 to €442 per 3 months. Total annual costs were similar between people diagnosed with epilepsy during the follow-up of the study and the people who are diagnosed as not having epilepsy or for whom diagnosis is still uncertain. Quality of Life had significantly increased over the course of 12 months from 0.80 to 0.84 (Dutch tariff).

DISCUSSION

This study indicates that an optimized diagnostic trajectory has positively influenced the use of healthcare resources and the quality of life in people with epilepsy. As chronic care patients make diverse costs, future research should identify the long-term costs after an optimized diagnostic trajectory for patients with epilepsy, possibly identifying patients who are at high risk of becoming high-cost users in the future for early intervention.

Usage of EpiFinder clinical decision support in the assessment of epilepsy

BACKGROUND

The diagnosis of epilepsy is at times elusive for both neurologists and nonneurologists, resulting in delays in diagnosis and therapy. The development of screening methods has been identified as a priority in response to this diagnostic and therapeutic gap. EpiFinder is a novel clinical decision support tool designed to enhance the process of information gathering and integration of patient/proxy respondent data. It is designed specifically to take key terms from a patient's history and incorporate them into a heuristic algorithm that dynamically produces differential diagnoses of epilepsy syndromes.

OBJECTIVE

The objective of this study was to test the usability and diagnostic accuracy of the clinical decision support application EpiFinder in an adult population.

METHODS

Fifty-seven patients were prospectively identified upon admission to the Epilepsy Monitoring Unit (EMU) for episode classification from January through June of 2017. Based on semiologic input, the application generates a list of epilepsy syndromes. The EpiFinder-generated diagnosis for each subject was compared to the final diagnosis obtained via continuous video electroencephalogram (cVEEG) monitoring.

RESULTS

Fifty-three patients had habitual events recorded during their EMU stay. A diagnosis of epilepsy was confirmed (with cVEEG monitoring) in 26 patients while 27 patients were found to have a diagnosis other than epilepsy. The algorithm appropriately predicted differentiation between the presence of an epilepsy syndrome and an alternative diagnosis with 86.8% (46/53 participants) accuracy. EpiFinder correctly identified the presence of epilepsy with a sensitivity of 86.4% (95% confidence interval [CI]: 65.0-97.1) and specificity of 85.1% (95% CI: 70.2-96.4).

CONCLUSION

The initial testing of the EpiFinder algorithm suggests possible utility in differentiating between an epilepsy syndrome and an alternative diagnosis in adult patients.

A Case of Dissociative Seizures Presented like Myoclonic Epilepsy

Psychogenic seizures are often underdiagnosed and epilepsy is very often over-treated which leads to multiple financial, social and stigma related difficulties. The myoclonic seizure itself is a rare phenomenon and when functional movement disorder presents like myoclonus then it's extremely difficult to pinpoint the exact cause. Here, we are presenting a case who was misdiagnosed as having a myoclonic seizure disorder and treated in multiple places without any improvement which ultimately turned out to be functional movement disorder of a rare variety.

Digital Care in Epilepsy: A Conceptual Framework for Technological Therapies

Epilepsy is associated with a significant increase in morbidity and mortality. The likelihood is significantly greater for those patients with specific risk factors. Identifying those at greatest risk of injury and providing expert management from the earliest opportunity is made more challenging by the circumstances in which many such patients present. Despite increasing recognition of the importance of earlier identification of those at risk, there is little or no improvement in outcomes over more than 30 years. Despite ever increasing sophistication of drug development and delivery, there has been no meaningful improvement in 1-year seizure freedom rates over this time. However, in the last few years, there has been an increase in patient-triggered interventions based on automated monitoring of indicators and risk factors facilitated by technological advances. The opportunities such approaches provide will only be realized if accompanied by current working practice changes. Replacing traditional follow-up appointments at arbitrary intervals with dynamic interventions, remotely and at the point and place of need provides a better chance of a substantial reduction in seizures for people with epilepsy. Properly implemented, electronic platforms can offer new opportunities to provide expert advice and management from first presentation thus improving outcomes. This perspective paper provides and proposes an informed critical opinion built on current evidence base of an outline techno-therapeutic approach to harnesses these technologies. This conceptual framework is generic, rather than tied to a specific product or solution, and the same generalized approach could be beneficially applied to other long-term conditions.

Value of clinical features to differentiate refractory epilepsy from mimics: a prospective longitudinal cohort study

BACKGROUND AND PURPOSE

Misdiagnosis of refractory epilepsy (rE) is common and such patients experience a long diagnostic delay. Our aim was to identify key clinical/laboratory factors in order to obtain an alternative diagnosis in patients referred for rE.

METHODS

Between January 2010 and December 2015, 125 consecutive patients with a diagnosis of rE were prospectively enrolled. All patients underwent a comprehensive neurological, neuropsychiatric and cardiological evaluation, and had an observation time of at least 1 year after the study entry.

RESULTS

Diagnosis of rE was confirmed in 104/125 (83.2%) patients (55 women, mean age 38.8 ± 14.3 years). Thirteen/125 patients (10.4%, seven women, mean age 50.8 ± 20.9) were diagnosed with syncope, which was cardiac/cardio inhibitory in 9/13 (69%). The remaining 8/125 patients (6.4%, six women, mean age 41.2 ± 14.6 years) were diagnosed with psychogenic non-epileptic seizures. Age at onset had a high accuracy in differentiating patients with syncope from others, with the best cut-off age at 35 years and above. Abnormal brain magnetic resonance imaging (MRI) had a significant yield of about 70% in rE. A diagnostic model including age at onset and brain MRI was highly accurate in differentiating patients with syncope from others. In patients with cardiac/cardio inhibitory syncope, the point score of historical features was ≥1 and falsely favoured the diagnosis of epileptic seizures.

CONCLUSIONS

This prospective cohort study identifies rE mimics who are at high risk of morbidity and mortality. rE starting in adulthood should raise a high suspicion of cardiac syncope. Brain MRI is accurate in differentiating rE from other conditions.

Optimising the use of EEG in non-epileptic attack disorder: Results of a UK national service evaluation

PURPOSE

To produce an evidence base to formulate guidelines for optimal performance of EEG in patients referred with a possible diagnosis of non-epileptic attack disorder (NEAD).

METHODS

51 UK EEG departments participated in the prospective study. A pro-forma was completed for all consecutive patients aged 5 years and over referred for EEG over a six month period. Information obtained included referral diagnosis, occurrence/type of attack during EEG, the use of suggestion, length of recording and who was present during the EEG.

RESULTS

11,298 patients were entered into the study. 376 psychogenic non-epileptic seizures (PNES) occurred of which 337 were considered to be of the habitual type. In those patients suspected of having NEAD prior to referral, the use of verbal suggestion increased the yield of habitual attacks by a factor of three in both adults and children. Using suggestive techniques twice, improved the yield further. Non-habitual attacks occurred equally whether or not suggestion was used. At least 90% of habitual PNES occurred within the first 30 min of recording even in those patients having prolonged EEGs. In EEGs where additional professional personnel were present, PNES occurred more frequently.

CONCLUSION

This large multicentre study provides evidence to inform recommendations for EEG to investigate NEAD. We recommend the use of verbal suggestion at least twice and where practical the presence of additional professional staff. A thirty minute recording is sufficient to record a habitual PNES in most instances.

Psychogenic non-epileptic seizures: aetiology, diagnosis and management

Psychogenic non-epileptic seizures (PNES) have a significant impact on most patients in terms of distress, disability, loss of income and iatrogenic harm. Three-quarters of patients with PNES are initially misdiagnosed and treated for epilepsy. Misdiagnosis exposes patients to multiple iatrogenic harms and prevents them from accessing psychological treatment. In most cases, the patient's history (and witness accounts) should alert clinicians to the likely diagnosis of PNES. Since this diagnosis may be resisted by patients and may involve ‘un-diagnosing’ epilepsy, video-electroencephalogram recording of typical seizures is often helpful. The underlying causes of PNES are diverse: a model combining predisposing, precipitating and perpetuating factors is a useful way of conceptualising their aetiology. The initial step of treatment should be to limit iatrogenic harm. There is some evidence for the effectiveness of psychotherapy.

Psychiatric comorbidities in epilepsy

Psychiatric comorbidities, including mood, anxiety, and psychotic disorders, are common in epilepsy, often occurring at rates 2-3-fold or higher than in the general population without epilepsy. This article discusses the epidemiology of psychiatric disorders in epilepsy, hypotheses regarding the pathogenesis of these comorbidities, and treatment implications. More specifically, it addresses: (1) How common are major depressive disorder, anxiety disorders, and psychotic disorders in epilepsy? (2) How does one screen for these psychiatric disorders in persons with epilepsy? (3) Why do psychiatric conditions occur in epilepsy? (4) Is the treatment of psychiatric comorbidity in epilepsy associated with seizures? The important topic of suicide and suicidal ideation in epilepsy, risk factors for their occurrence, and how to screen for these co-existent conditions is also discussed. Finally, gaps in knowledge regarding psychiatric conditions in epilepsy are briefly discussed.

Prevalence of epilepsy in 74,949 school children in Khartoum State, Sudan

BACKGROUND

Data on childhood epilepsy in Sudan are scarce and the only published study on its prevalence was published in 1983. This study aimed to determine the current prevalence of epilepsy in school children in Khartoum State.

METHODS

This is an analytical population-based, cross-sectional study conducted in Khartoum State, Sudan. The study included students in the basic (primary) schools aged 6-14 years. Simple random sampling was used to draw a cluster of four of the seven localities comprising Khartoum State. The sample frame consisted of 1609 public schools (808,624 pupils) and 787 private schools (194,613 pupils), a total of 2396 schools (1,003,237 pupils). A sample size of 75 940 pupils was estimated and 250 schools were drawn from a sample frame of 2396 schools using a stratified random sampling technique. Consent was obtained from the headmaster/head teacher of the selected schools who arranged a meeting with the tutor/teacher responsible for each class. The study team asked whether any of the pupils was ever noticed or known to have had any kind of seizures, and a confidential letter was sent to the parents of each identified pupil. The letter included an explanation of the aims of the study, information on the research group and the kind of help the research group could offer; contact numbers and email addresses were made available if they wished to participate in this study. Those who consented to participate were then given an appointment at the Epilepsy Outpatient Department, Gaafar Ibnauf Children's Hospital, Khartoum where they were evaluated by the paediatric neurologist.

RESULTS

Altogether, 74,949 pupils were enrolled for the study, 398 of whom were identified initially as having seizures and 332 of whom (83.4%) were identified by a paediatric neurologist. Of the 332, 303 (91.3%) proved to have epileptic seizures, 250 (82.5%) were known to have epilepsy, and 53 (17.5%) were newly diagnosed during the survey. The male to female ratio was 1.5:1. The total prevalence of epilepsy in Khartoum State was estimated to be 4/1000. The highest prevalence was in Jabal Awliya Locality (4.87/1000) and the lowest was in Khartoum Locality (3.35/1000). Twenty-nine (8.7%) patients proved to have non-epileptic seizures. The majority (15, 51.6%) had psychogenic non-epileptic seizures, and four (13.6%) had syncope. The majority (171, 56.43%) of patients had generalised epilepsy, 109 (35.97%) had focal epilepsy, and 23 (7.6%) had unclassified epilepsy.

CONCLUSION

The prevalence of epilepsy in school children in Khartoum State (4/1000) is higher than that reported previously from Khartoum Province in 1983 (0.9/1000).

My child cannot breathe while sleeping: a report of three cases and review

BACKGROUND

Sudden breath-holding episodes during sleep in young children are potentially related to sudden infant death syndrome and other life-threatening events. Additionally, these episodes can negatively affect child's growth and development.

CASE PRESENTATION

Here, we present 3 cases of preschool children with similar paroxysmal nocturnal waking events associated with choking that had different etiologies (nocturnal frontal lobe epilepsy, nocturnal gastroesophageal reflux disease, and parasomnia, respectively).

CONCLUSIONS

It is important to take into consideration the fact that breath spells during sleep can occur as a rare manifestation of parasomnia due to gastroesophageal reflux or as a symptom of nocturnal frontal lobe epilepsy. Full video electroencephalography, polysomnography, and simultaneous gastric pH monitoring should be used for the differential diagnosis of sleep-related disorders, such as breath spells, in children.

Development and validation of AIIMS modified INCLEN diagnostic instrument for epilepsy in children aged 1 month-18 years

OBJECTIVES

There is shortage of specialists for the diagnosis of children with epilepsy, especially in resource limited settings. Existing INCLEN (International Clinical Epidemiology Network) instrument was validated for children aged 2-9 years. The current study validated modifications of the same including wider symptomatology and age group.

METHODS

The Modified INCLEN tool was validated by a team of experts by modifying the existing tools (2-9 years) to widen the age range from 1 month to 18 years and include broader symptomatology in a tertiary care teaching hospital of North India between January and June 2015. A qualified medical graduate applied the candidate tool which was followed by gold standard evaluation by a Pediatric Neurologist (both blinded to each other).

RESULTS

A total of 197 children {128 boys (65%) and 69 girls (35%)}, with a mean age of 72.08 (±50.96) months, completed the study. The sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio of the modified epilepsy tool were 91.5% (84.5-96.1), 88.6% (80.0-93.5), 89.7% (81.9-95.3), 90.8% (83.7-95.7), 8 (6.6-9.8) and 0.09 (0.07-0.12) respectively.

SIGNIFICANCE

The new modified diagnostic instruments for epilepsy is simple, structured and valid instruments covering 1month to 18 years for use in resource limited settings with acceptable diagnostic accuracy. All seizure semiologies as well as common seizure mimics like breath-holding spells are included in the tool. It also provides for identification of acute symptomatic and febrile seizures.

Challenges in the pharmacological management of epilepsy and its causes in the elderly

Epilepsy represents the third most common neurological disorders in the elderly after cerebrovascular disorders and dementias. The incidence of new-onset epilepsy peaks in this age group. The most peculiar aetiologies of late-onset epilepsy are stroke, dementia, and brain tumours. However, aetiology remains unknown in about half of the patients. Diagnosis of epilepsy may be challenging due to the frequent absence of ocular witnesses and the high prevalence of seizure-mimics (i.e. transient ischemic attacks, syncope, transient global amnesia or vertigo) in the elderly. The diagnostic difficulties are even greater when patients have cognitive impairment or cardiac diseases. The management of late-onset epilepsy deserves special considerations. The elderly can reach seizure control with low antiepileptic drugs (AEDs) doses, and seizure-freedom is possible in the vast majority of patients. Pharmacological management should take into account pharmacokinetics and pharmacodynamics of AEDs and the frequent occurrence of comorbidities and polytherapy in this age group. Evidences from double-blind and open-label studies indicate lamotrigine, levetiracetam and controlled-release carbamazepine as first line treatment in late-onset epilepsy.

Comparison of Cognitive Impairment between Patients having Epilepsy and Psychogenic Nonepileptic Seizures

INTRODUCTION

The aim of this study was to evaluate cognitive impairment in patients having epilepsy or psychogenic nonepileptic seizures (PNESs) using selected neuropsychological tests at different time periods related to the seizure.

METHODS

In this study, selected neurocognitive tests were administered to the patients. Within 24 h, the previously applied neurocognitive tests were repeated within 24 h following the observation of typical seizures when monitoring and normalizing electroencephalography (EEG) activity. Basal neurocognitive tests were also administered to the healthy control group, and repeat neurocognitive evaluation was performed within 24-96 h.

RESULTS

The basal neurocognitive evaluation revealed that verbal learning and memory scores as well as Stroop test interference time were significantly lower in the PNES group compared with those in the controls. In the basal cognitive tests administered to the patients with epilepsy, verbal learning and memory scores, long-term memory, and total recognition test scores were significantly lower than those of the controls. Following the repeat cognitive tests, significant progress was found in the verbal categorical fluency score of the PNES group. No significant difference was determined in the epilepsy group. Significant contraction was determined in the Stroop interference time in the control group, but no similar change was recorded in the epilepsy or PNES groups.

CONCLUSION

While memory problems seemed to be most prominent in the assessed patients with epilepsy, attention and executive function problems were more dominant in the patients with PNESs. These findings are probably related to numerous factors such duration of disease, mood disorders, and specific drug use. No deterioration in attention and executive functions was reported in the early post-seizure period in either patient group.

Telemedicine for epilepsy support in resource-poor settings

The Problem: Epilepsy is a common disease worldwide causing significant physical and social disability. It is one of the most treatable neurological diseases. Yet, in rural, poorer countries like much of India and Nepal, most people with epilepsy are not undergoing any treatment often because they cannot access doctors.

Conventional Approaches: It is being appreciated that perhaps doctors are not the solution and that enabling health workers to treat epilepsy may be better. Few details, however, have been put forward about how that might be achieved.

Thinking Differently: Untreated epilepsy should be considered a public health problem like HIV/AIDS, the various steps needed for treatment identified and solutions found.

Telemedicine Approaches: Telemedicine might contribute to two steps – diagnosis and review. A tool that enables non-doctors to diagnose episodes as epileptic has been developed as a mobile phone app and has good applicability, sensitivity, and specificity for the diagnosis. There are a number of ways in which the use of phone review or short messaging service can improve management.

Conclusion: Telemedicine, as part of a public health program, can potentially help the millions of people in the resource-poor world with untreated epilepsy.

The consequences of refractory epilepsy and its treatment

Seizures in some 30% to 40% of patients with epilepsy fail to respond to antiepileptic drugs or other treatments. While much has been made of the risks of new drug therapies, not enough attention has been given to the risks of uncontrolled and progressive epilepsy. This critical review summarizes known risks associated with refractory epilepsy, provides practical clinical recommendations, and indicates areas for future research. Eight international epilepsy experts from Europe, the United States, and South America met on May 4, 2013, to present, review, and discuss relevant concepts, data, and literature on the consequences of refractory epilepsy. While patients with refractory epilepsy represent the minority of the population with epilepsy, they require the overwhelming majority of time, effort, and focus from treating physicians. They also represent the greatest economic and psychosocial burdens. Diagnostic procedures and medical/surgical treatments are not without risks. Overlooked, however, is that these risks are usually smaller than the risks of long-term, uncontrolled seizures. Refractory epilepsy may be progressive, carrying risks of structural damage to the brain and nervous system, comorbidities (osteoporosis, fractures), and increased mortality (from suicide, accidents, sudden unexpected death in epilepsy, pneumonia, vascular disease), as well as psychological (depression, anxiety), educational, social (stigma, driving), and vocational consequences. Adding to this burden is neuropsychiatric impairment caused by underlying epileptogenic processes ("essential comorbidities"), which appears to be independent of the effects of ongoing seizures themselves. Tolerating persistent seizures or chronic medicinal adverse effects has risks and consequences that often outweigh risks of seemingly "more aggressive" treatments. Future research should focus not only on controlling seizures but also on preventing these consequences.

Pattern of neurological disease seen among patients admitted in tertiary care hospital

BACKGROUND

Neurologic disorders are not uncommon at in patient departments of different hospitals. We have conducted the study to see the pattern and burden of neurologic disorders at different inpatient departments of a tertiary care centre.

METHODOLOGY

This retrospective observational study was carried out from the records and referral notes of neurology department of Dhaka Medical College Hospital (DMCH) from July 2011 to June 2012. A total 335 patients were evaluated by consultant neurologists during this period.

RESULT

Majority of the patients (59.7%) presented after the age of forty years. The mean age at presentation was 45.11 ± 17.3 years with a male predominance (63.3%). Stroke was the most common condition (47.5%) observed at referral, followed by seizure (9.3%), disease of spinal cord (7.8%) and encephalopathy (6.3%). Even after consultation, 30 patients remained undiagnosed and 6 were diagnosed as functional disorder. Department of Medicine (231, 69%) and Cardiology (61, 18.2%) made most of the calls. More than half (56%) of the stroke patients were referred from medicine and one third (35.2%) from cardiology. Seizure (67.7%), problem in spinal cord (92.3%), coma (50%), encephalopathy (57.1%), motor neuron disease (MND) (72.7%) were common reasons for referral from department of Medicine. Whereas patients with cord disease (7.3%), CNS tumor (40%), seizure disorder (6.5%) and stroke (3.8%) were referred from surgery. Department of Obstetrics and Gynecology sought help for stroke (2.5%), seizure (12.9%), MND (27.3%), coma (16.7%) and encephalopathy (9.5%). Hypertension, diabetes, ischemic heart disease, dyslipidaemia and respiratory problem were significantly associated co-morbid conditions in stroke patients (at 95% CI, p value is <0.001, <0.01, <0.001, <0.05, <0.05 respectively). Hematological disorders were common association among patients with cord problem (<0.05).

CONCLUSION

Wide ranges of neurological problems are often managed by physicians and surgeons, especially those from medicine and cardiology. Where ever available consultation from neurologists can help in diagnosing and managing these cases.

Eliciting patients' preferences for epilepsy diagnostics: a discrete choice experiment

BACKGROUND

Diagnosing epilepsy is a lengthy and burdensome process for patients and their family. Although the need for a more patient-centered approach in clinical practice is widely acknowledged, empirical evidence regarding patient preferences for diagnostic modalities in epilepsy is missing. The objectives of this study were 1) to identify to what extent important attributes of diagnostic procedures in epilepsy affect preferences for a procedure, 2) to determine the relative importance of these attributes, and 3) to calculate overall utility scores for routine electroencephalography (EEG) and magnetoencephalography (MEG) recordings.

METHODS

A discrete choice experiment was performed to determine patients' preferences, which involved presentation of pairwise choice tasks regarding hypothetical scenarios. Scenarios varied along six attributes: "way of measuring brain activity", "duration", "freedom of movement", "travel time", "type of additional examination", and "chance of additional examination". Choice tasks were constructed using a statistically efficient design, and the questionnaire contained 15 unique unlabeled choice tasks. Mixed multinomial logistic regression was used to estimate patients' preferences.

RESULTS

A total of 289 questionnaires were included in the analysis. McFadden's pseudo R(2) showed a model fit of 0.28, and all attributes were statistically significant. Heterogeneity in preferences was present for all attributes. "Freedom of movement" and "Chance of additional examination" were perceived as the most important attributes. Overall utility scores did not substantially differ between routine EEG and MEG.

CONCLUSION

This study suggests that the identified attributes are important in determining patients' preference for epilepsy diagnostics. It can be concluded that MEG is not necessarily more patient-friendly than a routine EEG in primary diagnostics and, regarding additional diagnostics, patients have a strong preference for long-term 24-h EEG over EEG after sleep deprivation. Furthermore, barring substantial heterogeneity within the parameters in mind, our study suggests that it is important to take individual preferences into account in medical decision-making.

Vision-based absence seizure detection

In order to diagnose epilepsy, neurologists rely on their experience, performing an equal assessment of the electroencephalogram and the clinical image. Since misdiagnosis reaches a rate of 30% and more than one-third of all epilepsies are poorly understood, a need for leveraging diagnostic precision is obvious. With the aim at enhancing the clinical image assessment procedure, this paper evaluates the suitability of certain facial expression features for detecting and quantifying absence seizures. These features are extracted by means of time-varying signal analysis from signals that are gained by applying computer vision techniques, such as face detection, dense optical flow computation and averaging background subtraction. For the evaluation, video sequences of four patients with absence seizures are used. The classification performance of a C4.5 decision tree shows accuracies of up to 99.96% with a worst percentage of incorrectly classified instances of 0.14%.

New developments in the treatment of partial-onset epilepsy

Although most people presenting with partial-onset seizures will achieve control with antiepileptic medication, a considerable minority will have difficult-to-treat epilepsy that is resistant to existing medication. Over the last few years, a large number of new antiepileptic drugs have been developed. Some of these have a novel mode of action. Many of the older antiepileptic drugs act through sodium channels or by enhancement of gamma amino butyric acid (GABA). Lamotrigine has sodium-channel blocking properties but also has other important modes of action, indicated by efficacy in treating not only partial-onset but also generalized seizures. Vigabatrin and tiagabine both increase GABA activity, by inhibiting GABA transaminase and limiting GABA reuptake, respectively. The main mode of action of gabapentin and pregabalin is not via GABA but through a selective inhibitory effect on voltage-gated calcium channels containing the α(2)δ-1 subunit. Levetiracetam inhibits the recycling of SV2A (synaptic vesicle protein 2A) neurotransmitter vesicles but also has other effects, including inhibition of voltage-dependent calcium channels. Some drugs, eg, felbamate, zonisamide, and topiramate, have multiple modes of action. In many cases, although the main mode of action may have been identified, other modes of action also play a role. Two recently developed antiepileptic drugs appear to have completely novel primary modes of action; retigabine (ezogabine) and perampanel act on the potassium channel and on AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) receptors, respectively. The hope is that antiepileptic drugs with a novel mode of action will be effective where previous drugs have failed and will not have unacceptable adverse effects. However, experience with these medications is too limited to allow any conclusions to be drawn at present.

Epilepsy at a large psychiatric hospital: survey and audit of its management

Objectives: Although epilepsy and psychiatric disorder are known to be associated, little is known about the nature of epilepsy in psychiatric inpatients and how well psychiatrists manage psychiatric patients with epilepsy. The aim of this study was to describe the nature of epilepsy in patients at a large specialist independent psychiatric hospital and to audit the management of epilepsy using patients' records.

Method: Cross-sectional survey of inpatients and audit of clinical documents. Audit standards were derived from good clinical practice and UK guidelines.

Results: In total, 83/488 (17%) patients had a life-time history of epileptic seizures and 67 (14%) were receiving anti-epileptic drugs. The prevalence of epilepsy was 37% among brain injury patients, compared with 10-11% in adult male and female forensic patients and in the elderly and 2% in adolescents. Generalised tonic-clonic seizures predominated. Common aetiological factors were: traumatic brain injury, antipsychotics, cerebral hypoxia, cerebrovascular disease and learning disability. In 53/67 (79%) cases the care plan stated the patient had epilepsy but in only 20 (30%) was the seizure type recorded. For 30 (45%) there was no history of how epilepsy had been diagnosed. Of those patients with a history of status epilepticus, 5/15 (33%) had a readily accessible emergency treatment plan. The patient's last seizure was incompletely documented in 29/44 (66%) cases, while for only 7/67 (10%) patients was there documented evidence of a review of epilepsy management within the past year.

Conclusions: Epilepsy was common in this group of psychiatric inpatients. Documentation and management needed improvement and to be in line with national guidelines.

The misdiagnosis of epilepsy in people with intellectual disabilities: a systematic review

PURPOSE

Epilepsy is common in people with intellectual disabilities. Epilepsy can be difficult to diagnose and may be misdiagnosed in around 25% of cases. A systematic review was conducted to explore: (i) How common the misdiagnosis of epilepsy is amongst people with intellectual disabilities. (ii) Reasons for misdiagnosis of epilepsy. (iii) Implications of misdiagnosis. (iv) Improving diagnosis.

METHODS

Primary studies and systematic reviews published in the English language between 1998 and 2008 were identified from electronic databases, experts, the Internet, grey literature, and citation tracking. Included studies were critically appraised by team members using the appraisal tools produced by the Critical Appraisal Skills Programme (CASP) at the Public Health Resource Unit, Oxford.

RESULTS

Eight studies were included in the review and critically appraised: six cohort studies and two case studies. Where data was provided in the cohort studies between 32% and 38% of people with intellectual disabilities were diagnosed as not having epilepsy or as having nonepileptic events. The main reason for misdiagnosis was the misinterpretation of behavioural, physiological, syndrome related, medication related or psychological events by parents, paid carers and health professionals.

CONCLUSIONS

Those working in epilepsy and intellectual disability services and families must be made more aware of the possibility of misdiagnosis. Future research is needed about the misdiagnosis of epilepsy amongst people with intellectual disabilities and carer knowledge.