Applying the ILAE diagnostic criteria for Lennox-Gastaut syndrome in the real-world setting: A multicenter retrospective cohort study.

OBJECTIVE: Lennox-Gastaut syndrome (LGS) is an archetypal developmental and epileptic encephalopathy, for which novel treatments are emerging. Diagnostic criteria for LGS have recently been defined by the International League Against Epilepsy (ILAE). We aimed to apply these criteria in a real-world setting. METHODS: We applied ILAE diagnostic criteria to a cohort of patients diagnosed with LGS by epileptologists following inpatient video-EEG monitoring (VEM) at tertiary comprehensive epilepsy centers between 1995 and 2015. We also assessed mortality in this cohort. RESULTS: Sixty patients diagnosed with LGS and had complete records available for review were identified. Among them, 29 (48%) patients met ILAE diagnostic criteria for LGS (ILAE-DC group). Thirty-one did not meet criteria (non-ILAE-DC) due to the absence of documented tonic seizures (n = 7), EEG features (n = 12), or both tonic seizures and EEG features (n = 10), intellectual disability (n = 1), or drug resistance (n = 1). The ILAE-DC group had a shorter duration of epilepsy at VEM than the non-ILAE-DC group (median = 12.0 years vs. 23.7 years, respectively; p = 0.015). The proportions of patients with multiple seizure types (100% vs. 96.7%), ≤2.5 Hz slow spike-and-wave EEG activity (100% vs. 90%), seizure-related injuries (27.6% vs. 25.8%), and mortality (standardized mortality ratio 4.60 vs. 5.12) were similar between the groups. SIGNIFICANCE: Up to 52% of patients diagnosed with LGS following VEM may not meet recently accepted ILAE criteria for LGS diagnosis. This may reflect both the limitations of retrospective medical record review and a historical tendency of applying the LGS diagnosis to a broad spectrum of severe, early-onset drug-resistant epilepsies with drop attacks. The ILAE criteria allow the delineation of LGS based on distinct electroclinical features, potentiating accurate diagnosis, prognostication, and management formulation. Nonetheless, mortality outcomes between those who did and did not meet ILAE diagnostic criteria for LGS were similarly poor, and both groups suffered high rates of seizure-related injury. PLAIN LANGUAGE SUMMARY: More than half of patients diagnosed with Lennox-Gastaut Syndrome (LGS) at three Australian epilepsy monitoring units between 1995 and 2015 did not meet the recently devised International League Against Epilepsy (ILAE) diagnostic criteria for LGS. Mortality was equally high in those who did and did not meet the ILAE diagnostic criteria, and seizure-related injury was common. The ILAE diagnostic criteria will guide accurate diagnosis, management, prognostication, and research in patients with LGS, however may be limited in their practical application to patients with a longer duration of epilepsy, or to those for whom detailed assessment is difficult.

Risk of sudden unexpected death in epilepsy (SUDEP) with lamotrigine and other sodium channel-modulating antiseizure medications.

OBJECTIVE: In vitro data prompted U.S Food and Drug Administration warnings that lamotrigine, a common sodium channel modulating anti-seizure medication (NaM-ASM), could increase the risk of sudden death in patients with structural or ischaemic cardiac disease, however, its implications for Sudden Unexpected Death in Epilepsy (SUDEP) are unclear. METHODS: This retrospective, nested case-control study identified 101 sudden unexpected death in epilepsy (SUDEP) cases and 199 living epilepsy controls from Epilepsy Monitoring Units (EMUs) in Australia and the USA. Differences in proportions of lamotrigine and NaM-ASM use were compared between cases and controls at the time of admission, and survival analyses from the time of admission up to 16 years were conducted. Multivariable logistic regression and survival analyses compared each ASM subgroup adjusting for SUDEP risk factors. RESULTS: Proportions of cases and controls prescribed lamotrigine (P = 0.166), one NaM-ASM (P = 0.80), or ≥2NaM-ASMs (P = 0.447) at EMU admission were not significantly different. Patients taking lamotrigine (adjusted hazard ratio [aHR] = 0.56; P = 0.054), one NaM-ASM (aHR = 0.8; P = 0.588) or ≥2 NaM-ASMs (aHR = 0.49; P = 0.139) at EMU admission were not at increased SUDEP risk up to 16 years following admission. Active tonic-clonic seizures at EMU admission associated with >2-fold SUDEP risk, irrespective of lamotrigine (aHR = 2.24; P = 0.031) or NaM-ASM use (aHR = 2.25; P = 0.029). Sensitivity analyses accounting for incomplete ASM data at follow-up suggest undetected changes to ASM use are unlikely to alter our results. SIGNIFICANCE: This study provides additional evidence that lamotrigine and other NaM-ASMs are unlikely to be associated with an increased long-term risk of SUDEP, up to 16 years post-EMU admission.

Identification of factors associated with new-onset vascular disease in patients admitted for video-EEG monitoring: A longitudinal cohort study.

OBJECTIVE: People with epilepsy are at a higher risk of developing vascular disease. Understanding the risk factors in observational studies is hampered by the challenge in separating epilepsy-related risk and treatment-related risk, and uncertainty in the epilepsy diagnosis. This study aimed to identify factors associated with risk of subsequent vascular disease in patients with video-EEG monitoring (VEM) confirmed epilepsy. METHODS: We included patients with a diagnosis of epilepsy and nonepileptic disorders between January 1, 1995, and December 31, 2015. Incident cardiovascular, cerebrovascular, and peripheral vascular disease was determined by linkage to a state-wide hospital admissions database between 1st July 1994 and 28th February 2018. Incidence was compared with the general population. RESULTS: 1728 patients (59.7% female, median age 35 years) underwent VEM, and were followed up for a median of 9.2 years (range 2.2-22.9 years). Eight-hundred and thirty -two were diagnosed with epilepsy and 896 nonepileptic disorders. The incidence of cerebrovascular disease was higher in both patients with epilepsy (incidence rate ratio [IRR] 1.78, p = 0.001) and with nonepileptic disorders (IRR 1.61, p < 0.001) than in the general population. Patients who took valproic acid (VPA) were at a lower risk of vascular disease than those taking enzyme-inducing antiseizure medications (EIASM, subdistribution hazard ratio [SHR] 0.42, p = 0.013), and those taking neither VPA nor EIASM (SHR 0.47, p = 0.03). There was no difference in the incidence of vascular disease between patients with epilepsy and those without epilepsy (SHR 0.94, p = 0.766). Factors associated with increased risk included age (SHR 1.04, p < 0.001), male sex (SHR 1.50, p = 0.017), and smoking (SHR 1.68, p = 0.017). SIGNIFICANCE: In this study, both patients with epilepsy and without epilepsy had increased vascular risk. This suggests that the increased risk may be in part due to factors not directly related to epilepsy, such as EIASM use and vascular risk factors.

Interictal EEG and ECG for SUDEP Risk Assessment: A Retrospective Multicenter Cohort Study.

Objective: Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality. Although lots of effort has been made in identifying clinical risk factors for SUDEP in the literature, there are few validated methods to predict individual SUDEP risk. Prolonged postictal EEG suppression (PGES) is a potential SUDEP biomarker, but its occurrence is infrequent and requires epilepsy monitoring unit admission. We use machine learning methods to examine SUDEP risk using interictal EEG and ECG recordings from SUDEP cases and matched living epilepsy controls. Methods: This multicenter, retrospective, cohort study examined interictal EEG and ECG recordings from 30 SUDEP cases and 58 age-matched living epilepsy patient controls. We trained machine learning models with interictal EEG and ECG features to predict the retrospective SUDEP risk for each patient. We assessed cross-validated classification accuracy and the area under the receiver operating characteristic (AUC) curve. Results: The logistic regression (LR) classifier produced the overall best performance, outperforming the support vector machine (SVM), random forest (RF), and convolutional neural network (CNN). Among the 30 patients with SUDEP [14 females; mean age (SD), 31 (8.47) years] and 58 living epilepsy controls [26 females (43%); mean age (SD) 31 (8.5) years], the LR model achieved the median AUC of 0.77 [interquartile range (IQR), 0.73-0.80] in five-fold cross-validation using interictal alpha and low gamma power ratio of the EEG and heart rate variability (HRV) features extracted from the ECG. The LR model achieved the mean AUC of 0.79 in leave-one-center-out prediction. Conclusions: Our results support that machine learning-driven models may quantify SUDEP risk for epilepsy patients, future refinements in our model may help predict individualized SUDEP risk and help clinicians correlate predictive scores with the clinical data. Low-cost and noninvasive interictal biomarkers of SUDEP risk may help clinicians to identify high-risk patients and initiate preventive strategies.

Association Between Psychiatric Comorbidities and Mortality in Epilepsy.

OBJECTIVE: To explore the impact of psychiatric comorbidities on all-cause mortality in adults with epilepsy from a cohort of patients admitted for video-EEG monitoring (VEM) over 2 decades. METHODS: A retrospective medical record audit was conducted on 2,709 adults admitted for VEM and diagnosed with epilepsy at 3 Victorian comprehensive epilepsy programs from 1995 to 2015. A total of 1,805 patients were identified in whom the record of a clinical evaluation by a neuropsychiatrist was available, excluding 27 patients who died of a malignant brain tumor known at the time of VEM admission. Epilepsy and lifetime psychiatric diagnoses were determined from consensus opinion of epileptologists and neuropsychiatrists involved in the care of each patient. Mortality and cause of death were determined by linkage to the Australian National Death Index and National Coronial Information System. RESULTS: Compared with the general population, mortality was higher in people with epilepsy (PWE) with a psychiatric illness (standardized mortality ratio [SMR] 3.6) and without a psychiatric illness (SMR 2.5). PWE with a psychiatric illness had greater mortality compared with PWE without (hazard ratio 1.41, 95% confidence interval 1.02-1.97) after adjusting for age and sex. No single psychiatric disorder by itself conferred increased mortality in PWE. The distribution of causes of death remained similar between PWE with psychiatric comorbidities and those without. CONCLUSION: The presence of comorbid psychiatric disorders in adults with epilepsy is associated with increased mortality, highlighting the importance of identifying and treating psychiatric comorbidities in these patients.

Association of Short-term Heart Rate Variability and Sudden Unexpected Death in Epilepsy.

BACKGROUND AND OBJECTIVES: We compared heart rate variability (HRV) in sudden unexpected death in epilepsy (SUDEP) cases and living epilepsy controls. METHODS: This international, multicenter, retrospective, nested case-control study examined patients admitted for video-EEG monitoring (VEM) between January 1, 2003, and December 31, 2014, and subsequently died of SUDEP. Time domain and frequency domain components were extracted from 5-minute interictal ECG recordings during sleep and wakefulness from SUDEP cases and controls. RESULTS: We identified 31 SUDEP cases and 56 controls. Normalized low-frequency power (LFP) during wakefulness was lower in SUDEP cases (median 42.5, interquartile range [IQR] 32.6-52.6) than epilepsy controls (55.5, IQR 40.7-68.9; p = 0.015, critical value = 0.025). In the multivariable model, normalized LFP was lower in SUDEP cases compared to controls (contrast -11.01, 95% confidence interval [CI] -20.29 to 1.73; p = 0.020, critical value = 0.025). There was a negative correlation between LFP and the latency to SUDEP, where each 1% incremental reduction in normalized LFP conferred a 2.7% decrease in the latency to SUDEP (95% CI 0.95-0.995; p = 0.017, critical value = 0.025). Increased survival duration from VEM to SUDEP was associated with higher normalized high-frequency power (HFP; p = 0.002, critical value = 0.025). The survival model with normalized LFP was associated with SUDEP (c statistic 0.66, 95% CI 0.55-0.77), which nonsignificantly increased with the addition of normalized HFP (c statistic 0.70, 95% CI 0.59-0.81; p = 0.209). CONCLUSIONS: Reduced short-term LFP, which is a validated biomarker for sudden death, was associated with SUDEP. Increased HFP was associated with longer survival and may be cardioprotective in SUDEP. HRV quantification may help stratify individual SUDEP risk. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that in patients with epilepsy, some measures of HRV are associated with SUDEP.

Mortality in patients with psychogenic nonepileptic seizures.

OBJECTIVE: To investigate the hypothesis that patients diagnosed with psychogenic nonepileptic seizures (PNES) on video-EEG monitoring (VEM) have increased mortality by comparison to the general population. METHODS: This retrospective cohort study included patients evaluated in VEM units of 3 tertiary hospitals in Melbourne, Australia, between January 1, 1995, and December 31, 2015. Diagnosis was based on consensus opinion of experienced epileptologists and neuropsychiatrists at each hospital. Mortality was determined in patients diagnosed with PNES, epilepsy, or both conditions by linkage to the Australian National Death Index. Lifetime history of psychiatric disorders in PNES was determined from formal neuropsychiatric reports. RESULTS: A total of 5,508 patients underwent VEM. A total of 674 (12.2%) were diagnosed with PNES, 3064 (55.6%) with epilepsy, 175 (3.2%) with both conditions, and 1,595 (29.0%) received other diagnoses or had no diagnosis made. The standardized mortality ratio (SMR) of patients diagnosed with PNES was 2.5 (95% confidence interval [CI] 2.0-3.3). Those younger than 30 had an 8-fold higher risk of death (95% CI 3.4-19.8). Direct comparison revealed no significant difference in mortality rate between diagnostic groups. Among deaths in patients diagnosed with PNES (n = 55), external causes contributed 18%, with 20% of deaths in those younger than 50 years attributed to suicide, and "epilepsy" was recorded as the cause of death in 24%. CONCLUSIONS: Patients diagnosed with PNES have a SMR 2.5 times above the general population, dying at a rate comparable to those with drug-resistant epilepsy. This emphasizes the importance of prompt diagnosis, identification of risk factors, and implementation of appropriate strategies to prevent potential avoidable deaths.