Medicine (RMH) - Research Publications
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ItemAdjunctive Transdermal Cannabidiol for Adults With Focal Epilepsy A Randomized Clinical Trial(AMER MEDICAL ASSOC, 2022-07-08)IMPORTANCE: Cannabidiol has shown efficacy in randomized clinical trials for drug-resistant epilepsy in specific syndromes that predominantly affect children. However, high-level evidence for the efficacy and safety of cannabidiol in the most common form of drug-resistant epilepsy in adults, focal epilepsy, is lacking. OBJECTIVE: To investigate the efficacy, safety, and tolerability of transdermally administered cannabidiol in adults with drug-resistant focal epilepsy. DESIGN, SETTING, AND PARTICIPANTS: A randomized, double-blind, placebo-controlled, multicenter clinical trial at 14 epilepsy trial centers in Australia and New Zealand. Participants were adults with drug-resistant focal epilepsy receiving a stable regimen of up to 3 antiseizure medications. Data were analyzed from July 2017 to November 2018. INTERVENTIONS: Eligible participants were randomized (1:1:1) to 195-mg or 390-mg transdermal cannabidiol or placebo twice daily for 12 weeks, after which they could enroll in an open-label extension study for up to 2 years. MAIN OUTCOMES AND MEASURES: Seizure frequency was self-reported using a daily diary. The primary efficacy end point was the least squares mean difference in the log-transformed total seizure frequency per 28-day period, adjusted to a common baseline log seizure rate, during the 12-week treatment period. RESULTS: A total of 188 patients (45% male [85 patients] and 54.8% female [103 patients]) with a mean (SD) age of 39.2 (12.78) years were randomized, treated, and analyzed (195-mg cannabidiol, 63 participants; 390-mg cannabidiol, 62 participants; placebo, 63 participants). At week 12 of the double-blind period, there was no difference in seizure frequency between placebo (mean [SD] 2.49 [1.31] seizures per 28 days) and 195-mg cannabidiol (mean [SD] 2.51 [1.15] seizures per 28 days; least squares mean difference, 0.014; 95% CI, -0.175 to 0.203; P = .89) or 390-mg cannabidiol (mean [SD] 2.59 [1.12] seizures per 28 days; least squares mean difference, 0.096; 95% CI, -0.093 to 0.285; P = .32). By month 6 of the open-label extension, 115 patients (60.8%) achieved a seizure reduction of at least 50%. Treatment-emergent adverse events occurred in 50.4% (63 of 125 participants) of the cannabidiol group vs 41.3% (26 of 63 participants) in the placebo group, with a treatment difference of 9.1% (95% CI, -6.0% to 23.6%), and occurred at similar rates in the cannabidiol groups. Few participants discontinued (7% [14 of 188 participants]), and most (98% [171 of 174 participants]) continued into the open-label extension. CONCLUSIONS AND RELEVANCE: Both doses of transdermal cannabidiol were well tolerated and safe. No significant difference in efficacy was observed between cannabidiol and placebo during the double-blind treatment period. The open-label extension demonstrated the long-term safety, tolerability, and acceptability of transdermal cannabidiol delivery. TRIAL REGISTRATION: ACTRN12616000510448 (double-blind); ACTRN12616001455459 (open-label).
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ItemInterictal EEG and ECG for SUDEP Risk Assessment: A Retrospective Multicenter Cohort Study(FRONTIERS MEDIA SA, 2022-03-18)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.
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ItemAssociation Between Psychiatric Comorbidities and Mortality in Epilepsy(LIPPINCOTT WILLIAMS & WILKINS, 2021-10)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.