Medicine (RMH) - Research Publications
Permanent URI for this collection
Search Results
1 - 10 of 12
-
ItemNo Preview AvailableDiagnostic delay in focal epilepsy: Association with brain pathology and age(W B SAUNDERS CO LTD, 2022-03)PURPOSE: Between 16-77% of patients with newly diagnosed epilepsy report seizures before diagnosis but little is known about the risk factors for diagnostic delay. Here, we examined the association between prior seizures and neuroimaging findings in newly diagnosed focal epilepsy. METHODS: Adults diagnosed with focal epilepsy at First Seizure Clinics (FSC) at the Royal Melbourne Hospital or Austin Health, Melbourne, Australia, between 2000 and 2010 were included. Medical records were audited for seizure history accrued from the detailed FSC interview. Potentially epileptogenic brain abnormality type, location and extent was determined from neuroimaging. Statistical analysis comprised multivariate logistic regression. RESULTS: Of 735 patients, 44% reported seizure/s before the index seizure. Among the 260 individuals with a potentially epileptogenic brain imaging abnormality, 34% reported prior seizures. Of 475 individuals with no abnormality, 50% reported prior seizures (p < 0.001). Patients with post-stroke changes had lower odds of prior seizures (n = 24/95, OR 0.5, p = 0.005) compared to patients without abnormalities, as did patients with high-grade tumors (n = 1/10, OR 0.1, p = 0.04). Abnormality location or extent was not associated with seizures. Prior seizures were inversely associated with age, patients aged >50 years had lower odds compared to those 18-30 years (OR 0.5, p = 0.01). CONCLUSIONS: A history of prior seizures is less common in patients with newly diagnosed focal epilepsy associated with antecedent stroke or high-grade tumor than in those without a lesion, and is also less common in older individuals. These findings may be related to age, biological mechanisms or aspects of diagnosis and assessment of these events.
-
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).
-
ItemSub-genic intolerance, ClinVar, and the epilepsies: A whole-exome sequencing study of 29,165 individuals(CELL PRESS, 2021-06-03)Both mild and severe epilepsies are influenced by variants in the same genes, yet an explanation for the resulting phenotypic variation is unknown. As part of the ongoing Epi25 Collaboration, we performed a whole-exome sequencing analysis of 13,487 epilepsy-affected individuals and 15,678 control individuals. While prior Epi25 studies focused on gene-based collapsing analyses, we asked how the pattern of variation within genes differs by epilepsy type. Specifically, we compared the genetic architectures of severe developmental and epileptic encephalopathies (DEEs) and two generally less severe epilepsies, genetic generalized epilepsy and non-acquired focal epilepsy (NAFE). Our gene-based rare variant collapsing analysis used geographic ancestry-based clustering that included broader ancestries than previously possible and revealed novel associations. Using the missense intolerance ratio (MTR), we found that variants in DEE-affected individuals are in significantly more intolerant genic sub-regions than those in NAFE-affected individuals. Only previously reported pathogenic variants absent in available genomic datasets showed a significant burden in epilepsy-affected individuals compared with control individuals, and the ultra-rare pathogenic variants associated with DEE were located in more intolerant genic sub-regions than variants associated with non-DEE epilepsies. MTR filtering improved the yield of ultra-rare pathogenic variants in affected individuals compared with control individuals. Finally, analysis of variants in genes without a disease association revealed a significant burden of loss-of-function variants in the genes most intolerant to such variation, indicating additional epilepsy-risk genes yet to be discovered. Taken together, our study suggests that genic and sub-genic intolerance are critical characteristics for interpreting the effects of variation in genes that influence epilepsy.
-
ItemMachine learning approaches for imaging-based prognostication of the outcome of surgery for mesial temporal lobe epilepsy(WILEY, 2022-05)OBJECTIVES: Around 30% of patients undergoing surgical resection for drug-resistant mesial temporal lobe epilepsy (MTLE) do not obtain seizure freedom. Success of anterior temporal lobe resection (ATLR) critically depends on the careful selection of surgical candidates, aiming at optimizing seizure freedom while minimizing postoperative morbidity. Structural MRI and FDG-PET neuroimaging are routinely used in presurgical assessment and guide the decision to proceed to surgery. In this study, we evaluate the potential of machine learning techniques applied to standard presurgical MRI and PET imaging features to provide enhanced prognostic value relative to current practice. METHODS: Eighty two patients with drug resistant MTLE were scanned with FDG-PET pre-surgery and T1-weighted MRI pre- and postsurgery. From these images the following features of interest were derived: volume of temporal lobe (TL) hypometabolism, % of extratemporal hypometabolism, presence of contralateral TL hypometabolism, presence of hippocampal sclerosis, laterality of seizure onset volume of tissue resected and % of temporal lobe hypometabolism resected. These measures were used as predictor variables in logistic regression, support vector machines, random forests and artificial neural networks. RESULTS: In the study cohort, 24 of 82 (28.3%) who underwent an ATLR for drug-resistant MTLE did not achieve Engel Class I (i.e., free of disabling seizures) outcome at a minimum of 2 years of postoperative follow-up. We found that machine learning approaches were able to predict up to 73% of the 24 ATLR surgical patients who did not achieve a Class I outcome, at the expense of incorrect prediction for up to 31% of patients who did achieve a Class I outcome. Overall accuracies ranged from 70% to 80%, with an area under the receiver operating characteristic curve (AUC) of .75-.81. We additionally found that information regarding overall extent of both total and significantly hypometabolic tissue resected was crucial to predictive performance, with AUC dropping to .59-.62 using presurgical information alone. Incorporating the laterality of seizure onset and the choice of machine learning algorithm did not significantly change predictive performance. SIGNIFICANCE: Collectively, these results indicate that "acceptable" to "good" patient-specific prognostication for drug-resistant MTLE surgery is feasible with machine learning approaches utilizing commonly collected imaging modalities, but that information on the surgical resection region is critical for optimal prognostication.
-
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.
-
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.
-
ItemMetabolic patterns and seizure outcomes following anterior temporal lobectomy(WILEY, 2019-02)OBJECTIVE: We investigated the relationship between the interictal metabolic patterns, the extent of resection of 18 F-fluorodeoxyglucose positron emission tomography (18 FDG-PET) hypometabolism, and seizure outcomes in patients with unilateral drug-resistant mesial temporal lobe epilepsy (MTLE) following anterior temporal lobe (TL) resection. METHODS: Eighty-two patients with hippocampal sclerosis or normal magnetic resonance imaging (MRI) findings, concordant 18 FDG-PET hypometabolism, and at least 2 years of postoperative follow-up were included in this 2-center study. The hypometabolic regions in each patient were identified with reference to 20 healthy controls (p < 0.005). The resected TL volume and the volume of resected TL PET hypometabolism (TLH) were calculated from the pre- and postoperative MRI scans coregistered with interictal 18 FDG-PET. RESULTS: Striking differences in metabolic patterns were observed depending on the lateralization of the epileptogenic TL. The extent of the ipsilateral TLH was significantly greater in left MTLE patients (p < 0.001), whereas right MTLE patients had significantly higher rates of contralateral (CTL) TLH (p = 0.016). In right MTLE patients, CTL hypometabolism was the strongest predictor of an unfavorable seizure outcome, associated with a 5-fold increase in the likelihood of seizure recurrence (odds ratio [OR] = 4.90, 95% confidence interval [CI] = 1.07-22.39, p = 0.04). In left MTLE patients, greater extent of resection of ipsilateral TLH was associated with lower rates of seizure recurrence (p = 0.004) in univariate analysis; however, its predictive value did not reach statistical significance (OR = 0.96, 95% CI = 0.90-1.02, p = 0.19). INTERPRETATION: The difference in metabolic patterns depending on the lateralization of MTLE may represent distinct epileptic networks in patients with right versus left MTLE, and can guide preoperative counseling and surgical planning. Ann Neurol 2019; 1-10 ANN NEUROL 2019;85:241-250.
-
ItemAntiepileptic Drug Teratogenicity and De Novo Genetic Variation Load(WILEY, 2020-06)OBJECTIVE: The mechanisms by which antiepileptic drugs (AEDs) cause birth defects (BDs) are unknown. Data suggest that AED-induced BDs may result from a genome-wide increase of de novo variants in the embryo, a mechanism that we investigated. METHODS: Whole exome sequencing data from child-parent trios were interrogated for de novo single-nucleotide variants/indels (dnSNVs/indels) and de novo copy number variants (dnCNVs). Generalized linear models were applied to assess de novo variant burdens in children exposed prenatally to AEDs (AED-exposed children) versus children without BDs not exposed prenatally to AEDs (AED-unexposed unaffected children), and AED-exposed children with BDs versus those without BDs, adjusting for confounders. Fisher exact test was used to compare categorical data. RESULTS: Sixty-seven child-parent trios were included: 10 with AED-exposed children with BDs, 46 with AED-exposed unaffected children, and 11 with AED-unexposed unaffected children. The dnSNV/indel burden did not differ between AED-exposed children and AED-unexposed unaffected children (median dnSNV/indel number/child [range] = 3 [0-7] vs 3 [1-5], p = 0.50). Among AED-exposed children, there were no significant differences between those with BDs and those unaffected. Likely deleterious dnSNVs/indels were detected in 9 of 67 (13%) children, none of whom had BDs. The proportion of cases harboring likely deleterious dnSNVs/indels did not differ significantly between AED-unexposed and AED-exposed children. The dnCNV burden was not associated with AED exposure or birth outcome. INTERPRETATION: Our study indicates that prenatal AED exposure does not increase the burden of de novo variants, and that this mechanism is not a major contributor to AED-induced BDs. These results can be incorporated in routine patient counseling. ANN NEUROL 2020;87:897-906.
-
ItemNewly diagnosed seizures assessed at two established first seizure clinics: Clinic characteristics, investigations, and findings over 11 years(WILEY, 2021-03)OBJECTIVE: 'First seizure' clinics (FSCs) aim to achieve early expert assessment for individuals with possible new-onset epilepsy. These clinics also have substantial potential for research into epilepsy evolution, outcomes, and costs. However, a paucity of FSCs details has implications for interpretation and utilization of this research. METHODS: We reviewed investigation findings over 11 years (2000-2010) from two established independent FSCs at Austin Health (AH) and Royal Melbourne Hospital (RMH), Australia. These adult clinics are in major public hospitals and operate with similar levels of expertise. Organizational differences include screening and dedicated administration at AH. Included were N = 1555 patients diagnosed with new-onset unprovoked seizures/epilepsy (AH n = 901, RMH n = 654). Protocol-driven interviews and investigations had been recorded prospectively and were extracted from medical records for study. RESULTS: Median patient age was 37 (IQR 26-52, range 18-94) years (AH 34 vs RMH 42 years; P < .001). Eighty-six percent of patients attended FSC within three weeks postindex seizure (median AH 12 vs RMH 25 days; P < .01). By their first appointment, 42% had experienced ≥2 seizures. An EEG was obtained within three weeks postindex seizure in 73% of patients, demonstrating epileptiform discharges in 25% (AH 33% vs RMH 15%). Seventy-six percent of patients had an MRI within 6 weeks. Of those with imaging (n = 1500), 19% had potentially epileptogenic abnormalities (RMH 28% vs AH 12%; P < .01). At both sites, changes due to previous stroke/hemorrhage were the commonest lesions, followed by traumatic brain injury. ≥WHO level 1 brain tumors diagnosed at presentation comprised a very small proportion (<1%) at each clinic. At both sites, epilepsy type could be determined in 60% of patients; RMH had more focal and AH more generalized epilepsy diagnoses. SIGNIFICANCE: Differences between the clinics' administrative and screening practices may contribute to differences in investigation findings. Insight into these differences will facilitate interpretation and utilization, and planning of future research.
-
ItemPolygenic burden in focal and generalized epilepsies(OXFORD UNIV PRESS, 2019-11)Rare genetic variants can cause epilepsy, and genetic testing has been widely adopted for severe, paediatric-onset epilepsies. The phenotypic consequences of common genetic risk burden for epilepsies and their potential future clinical applications have not yet been determined. Using polygenic risk scores (PRS) from a European-ancestry genome-wide association study in generalized and focal epilepsy, we quantified common genetic burden in patients with generalized epilepsy (GE-PRS) or focal epilepsy (FE-PRS) from two independent non-Finnish European cohorts (Epi25 Consortium, n = 5705; Cleveland Clinic Epilepsy Center, n = 620; both compared to 20 435 controls). One Finnish-ancestry population isolate (Finnish-ancestry Epi25, n = 449; compared to 1559 controls), two European-ancestry biobanks (UK Biobank, n = 383 656; Vanderbilt biorepository, n = 49 494), and one Japanese-ancestry biobank (BioBank Japan, n = 168 680) were used for additional replications. Across 8386 patients with epilepsy and 622 212 population controls, we found and replicated significantly higher GE-PRS in patients with generalized epilepsy of European-ancestry compared to patients with focal epilepsy (Epi25: P = 1.64×10-15; Cleveland: P = 2.85×10-4; Finnish-ancestry Epi25: P = 1.80×10-4) or population controls (Epi25: P = 2.35×10-70; Cleveland: P = 1.43×10-7; Finnish-ancestry Epi25: P = 3.11×10-4; UK Biobank and Vanderbilt biorepository meta-analysis: P = 7.99×10-4). FE-PRS were significantly higher in patients with focal epilepsy compared to controls in the non-Finnish, non-biobank cohorts (Epi25: P = 5.74×10-19; Cleveland: P = 1.69×10-6). European ancestry-derived PRS did not predict generalized epilepsy or focal epilepsy in Japanese-ancestry individuals. Finally, we observed a significant 4.6-fold and a 4.5-fold enrichment of patients with generalized epilepsy compared to controls in the top 0.5% highest GE-PRS of the two non-Finnish European cohorts (Epi25: P = 2.60×10-15; Cleveland: P = 1.39×10-2). We conclude that common variant risk associated with epilepsy is significantly enriched in multiple cohorts of patients with epilepsy compared to controls-in particular for generalized epilepsy. As sample sizes and PRS accuracy continue to increase with further common variant discovery, PRS could complement established clinical biomarkers and augment genetic testing for patient classification, comorbidity research, and potentially targeted treatment.