Medicine (RMH) - Research Publications
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ItemNo Preview AvailableEpileptic seizure control during and after pregnancy in Australian women(WILEY, 2022-06)OBJECTIVES: To study factors that affected previous epileptic seizure control throughout pregnancy, during labour, and in the post-natal weeks. MATERIALS & METHODS: Analysis of data concerning seizure freedom that was available at various stages of 2337 pregnancies in the Raoul Wallenberg Australian Pregnancy Register of Antiepileptic Drugs, mainly employing multiple variable logistic regression techniques. RESULTS: Based on data available at the outset of pregnancy, the risk of seizure-affected that is, not seizure-free pregnancy was statistically significantly (p < .05) higher in pregnancies where there was previously uncontrolled epilepsy (78.1% vs. 20.8%) and focal epilepsy (51.3% vs. 39.7%), and decreased with later onset-age epilepsy (41.8% vs. 52.2% with onset before age 13 years), The risk did not differ between initially antiseizure medication (ASM)-treated or untreated pregnancies. For epilepsy receiving ASM therapy, 90.6% of 160 pregnancies of women with uncontrolled focal epilepsy that began before the age of 13 were seizure-affected. None of the above factors influenced the risk of seizures during labour, though having seizures during pregnancy increased the hazard (3.93 vs. 0.6%). Either ASM-treated pregnancy or labour being seizure-affected increased the risk of post-partum period seizures (33.0% vs. 6.67% for both stages being seizure-free). Use of particular ASMs had no statistically significant effect on the seizure control situation at any of the pregnancy stages studied. CONCLUSIONS: Obtaining full seizure control before pregnancy appeared to be the main factor in maintaining seizure freedom during pregnancy, labour and the post-natal weeks.
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ItemNo Preview AvailableDeep learning for automated epileptiform discharge detection from scalp EEG: A systematic review(IOP Publishing Ltd, 2022-10-01)Automated interictal epileptiform discharge (IED) detection has been widely studied, with machine learning methods at the forefront in recent years. As computational resources become more accessible, researchers have applied deep learning (DL) to IED detection with promising results. This systematic review aims to provide an overview of the current DL approaches to automated IED detection from scalp electroencephalography (EEG) and establish recommendations for the clinical research community. We conduct a systematic review according to the PRISMA guidelines. We searched for studies published between 2012 and 2022 implementing DL for automating IED detection from scalp EEG in major medical and engineering databases. We highlight trends and formulate recommendations for the research community by analyzing various aspects: data properties, preprocessing methods, DL architectures, evaluation metrics and results, and reproducibility. The search yielded 66 studies, and 23 met our inclusion criteria. There were two main DL networks, convolutional neural networks in 14 studies and long short-term memory networks in three studies. A hybrid approach combining a hidden Markov model with an autoencoder was employed in one study. Graph convolutional network was seen in one study, which considered a montage as a graph. All DL models involved supervised learning. The median number of layers was 9 (IQR: 5-21). The median number of IEDs was 11 631 (IQR: 2663-16 402). Only six studies acquired data from multiple clinical centers. AUC was the most reported metric (median: 0.94; IQR: 0.94-0.96). The application of DL to IED detection is still limited and lacks standardization in data collection, multi-center testing, and reporting of clinically relevant metrics (i.e. F1, AUCPR, and false-positive/minute). However, the performance is promising, suggesting that DL might be a helpful approach. Further testing on multiple datasets from different clinical centers is required to confirm the generalizability of these methods.
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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.
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ItemCerebrospinal fluid neurofilament light chain differentiates primary psychiatric disorders from rapidly progressive, Alzheimer's disease and frontotemporal disorders in clinical settings(WILEY, 2022-11)INTRODUCTION: Many patients with cognitive and neuropsychiatric symptoms face diagnostic delay and misdiagnosis. We investigated whether cerebrospinal fluid (CSF) neurofilament light (NfL) and total-tau (t-tau) could assist in the clinical scenario of differentiating neurodegenerative (ND) from psychiatric disorders (PSY), and rapidly progressive disorders. METHODS: Biomarkers were examined in patients from specialist services (ND and PSY) and a national Creutzfeldt-Jakob registry (Creutzfeldt-Jakob disease [CJD] and rapidly progressive dementias/atypically rapid variants of common ND, RapidND). RESULTS: A total of 498 participants were included: 197 ND, 67 PSY, 161 CJD, 48 RapidND, and 20 controls. NfL was elevated in ND compared to PSY and controls, with highest levels in CJD and RapidND. NfL distinguished ND from PSY with 95%/78% positive/negative predictive value, 92%/87% sensitivity/specificity, 91% accuracy. NfL outperformed t-tau in most real-life clinical diagnostic dilemma scenarios, except distinguishing CJD from RapidND. DISCUSSION: We demonstrated strong generalizable evidence for the diagnostic utility of CSF NfL in differentiating ND from psychiatric disorders, with high accuracy.
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ItemNo Preview AvailableAssociation of Neurocritical Care Services With Mortality and Functional Outcomes for Adults With Brain Injury A Systematic Review and Meta-analysis(AMER MEDICAL ASSOC, 2022-10)IMPORTANCE: Neurocritical care (NCC) aims to improve the outcomes of critically ill patients with brain injury, although the benefits of such subspecialized care are yet to be determined. OBJECTIVE: To evaluate the association of NCC with patient-centered outcomes in adults with acute brain injury who were admitted to intensive care units (ICUs). The protocol was preregistered on PROSPERO (CRD42020177190). DATA SOURCES: Three electronic databases were searched (Ovid MEDLINE, Embase, Cochrane Central Register of Controlled Trials) from inception through December 15, 2021, and by citation chaining. STUDY SELECTION: Studies were included for interventions of neurocritical care units (NCCUs), neurointensivists, or NCC consulting services compared with general care in populations of neurologically ill adults or adults with acute brain injury in ICUs. DATA EXTRACTION AND SYNTHESIS: Data extraction was performed in keeping with PRISMA guidelines and risk of bias assessed through the ROBINS-I Cochrane tool by 2 independent reviewers. Data were pooled using a random-effects model. MAIN OUTCOMES AND MEASURES: The primary outcome was all-cause mortality at longest follow-up until 6 months. Secondary outcomes were ICU length of stay (LOS), hospital LOS, and functional outcomes. Data were measured as risk ratio (RR) if dichotomous or standardized mean difference if continuous. Subgroup analyses were performed for disease and models of NCC delivery. RESULTS: After 5659 nonduplicated published records were screened, 26 nonrandomized observational studies fulfilled eligibility criteria. A meta-analysis of mortality outcomes for 55 792 patients demonstrated a 17% relative risk reduction (RR, 0.83; 95% CI, 0.75-0.92; P = .001) in those receiving subspecialized care (n = 27 061) compared with general care (n = 27 694). Subgroup analyses did not identify subgroup differences. Eight studies including 4667 patients demonstrated a 17% relative risk reduction (RR, 0.83; 95% CI, 0.70-0.97; P = .03) for an unfavorable functional outcome with subspecialized care compared with general care. There were no differences in LOS outcomes. Heterogeneity was substantial in all analyses. CONCLUSIONS AND RELEVANCE: Subspecialized NCC is associated with improved survival and functional outcomes for critically ill adults with brain injury. However, confidence in the evidence is limited by substantial heterogeneity. Further investigations are necessary to determine the specific aspects of NCC that contribute to these improved outcomes and its cost-effectiveness.
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ItemNo Preview AvailableRisk Factors and Prognosis of Early Posttraumatic Seizures in Moderate to Severe Traumatic Brain Injury(AMER MEDICAL ASSOC, 2022-04)IMPORTANCE: Early posttraumatic seizures (EPS) that may occur following a traumatic brain injury (TBI) are associated with poorer outcomes and development of posttraumatic epilepsy (PTE). OBJECTIVE: To evaluate risk factors for EPS, associated morbidity and mortality, and contribution to PTE. DESIGN, SETTING, AND PARTICIPANTS: Data were collected from an Australian registry-based cohort study of adults (age ≥18 years) with moderate to severe TBI from January 2005 to December 2019, with 2-year follow-up. The statewide trauma registry, conducted on an opt-out basis in Victoria (population 6.5 million), had 15 152 patients with moderate to severe TBI identified via Abbreviated Injury Scale (AIS) head severity score, with an opt-out rate less than 0.5% (opt-out n = 136). MAIN OUTCOMES AND MEASURES: EPS were identified via International Statistical Classification of Diseases, Tenth Revision, Australian Modification (ICD-10-AM) codes recorded after the acute admission. Outcome measures also included in-hospital metrics, 2-year outcomes including PTE, and post-discharge mortality. Adaptive least absolute shrinkage and selection operator (LASSO) regression was used to build a prediction model for risk factors of EPS. RESULTS: Among the 15 152 participants (10 457 [69%] male; median [IQR] age, 60 [35-79] y), 416 (2.7%) were identified with EPS, including 27 (0.2%) with status epilepticus. Significant risk factors on multivariable analysis for developing EPS were younger age, higher Charlson Comorbidity Index, TBI sustained from a low fall, subdural hemorrhage, subarachnoid hemorrhage, higher Injury Severity Score, and greater head injury severity, measured using the AIS and Glasgow Coma Score. After adjustment for confounders, EPS were associated with increased ICU admission and ICU length of stay, ventilation and duration, hospital length of stay, and discharge to inpatient rehabilitation rather than home, but not in-hospital mortality. Outcomes in TBI admission survivors at 24 months, including mortality (relative risk [RR] = 2.14; 95% CI, 1.32-3.46; P = .002), development of PTE (RR = 2.91; 95% CI, 2.22-3.81; P < .001), and use of antiseizure medications (RR = 2.44; 95% CI, 1.98-3.02; P < .001), were poorer for cases with EPS after adjustment for confounders. The prediction model for EPS had an area under the receiver operating characteristic curve of 0.72 (95% CI, 0.66-0.79), sensitivity of 66%, and specificity of 73% in the validation set. DISCUSSION: We identified important risk factors for EPS following moderate to severe TBI. Early posttraumatic seizures were associated with longer ICU and hospital admissions, ICU ventilation, and poorer 24-month outcomes including mortality and development of PTE.
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ItemSeizure control in successive pregnancies in Australian women with epilepsy(WILEY, 2022-11)OBJECTIVES: To investigate control of epileptic seizures during pairs of successive pregnancies in antiseizure medication (ASM)-treated women with epilepsy. MATERIALS AND METHODS: Analysis of seizure freedom rates during 436 pairs of successive pregnancies in Australian women with epilepsy, in nearly all instances long-standing epilepsy. RESULT: There was a higher rate of seizure-free second pregnancies compared with first paired pregnancies (63.1% vs. 51.4%; Relative Risk (R.R.) = 1.2277; 95% CI 1.0930, 1.3789) and of seizure-free pre-pregnancy years before second as compared with first paired pregnancies in the same women (63.6% vs. 52.4%; R.R. = 1.2616; 95% CI 1.1337, 1.4040). In 108 women whose ASM therapy was unaltered throughout both of their pregnancies, the seizure-freedom rate was higher in the second of the paired pregnancies (82.4% vs. 69.4%; R.R. = 1.1867, 95% CI 1.0189, 1.3821). CONCLUSIONS: Altered ASM therapy after the first of a pair of successive pregnancies did not fully account for the better overall seizure control in the corresponding second pregnancies. Some additional factor may have been in operation, possibly a greater preparedness to undertake a further pregnancy if seizures were already fully controlled.
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ItemMoving the field forward: detection of epileptiform abnormalities on scalp electroencephalography using deep learning-clinical application perspectives(OXFORD UNIV PRESS, 2022-09-01)The application of deep learning approaches for the detection of interictal epileptiform discharges is a nascent field, with most studies published in the past 5 years. Although many recent models have been published demonstrating promising results, deficiencies in descriptions of data sets, unstandardized methods, variation in performance evaluation and lack of demonstrable generalizability have made it difficult for these algorithms to be compared and progress to clinical validity. A few recent publications have provided a detailed breakdown of data sets and relevant performance metrics to exemplify the potential of deep learning in epileptiform discharge detection. This review provides an overview of the field and equips computer and data scientists with a synopsis of EEG data sets, background and epileptiform variation, model evaluation parameters and an awareness of the performance metrics of high impact and interest to the trained clinical and neuroscientist EEG end user. The gold standard and inter-rater disagreements in defining epileptiform abnormalities remain a challenge in the field, and a hierarchical proposal for epileptiform discharge labelling options is recommended. Standardized descriptions of data sets and reporting metrics are a priority. Source code-sharing and accessibility to public EEG data sets will increase the rigour, quality and progress in the field and allow validation and real-world clinical translation.
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ItemAn Integrated Multi-Omic Network Analysis Identifies Seizure-Associated Dysregulated Pathways in the GAERS Model of Absence Epilepsy(MDPI, 2022-06)Absence epilepsy syndromes are part of the genetic generalized epilepsies, the pathogenesis of which remains poorly understood, although a polygenic architecture is presumed. Current focus on single molecule or gene identification to elucidate epileptogenic drivers is unable to fully capture the complex dysfunctional interactions occurring at a genetic/proteomic/metabolomic level. Here, we employ a multi-omic, network-based approach to characterize the molecular signature associated with absence epilepsy-like phenotype seen in a well validated rat model of genetic generalized epilepsy with absence seizures. Electroencephalographic and behavioral data was collected from Genetic Absence Epilepsy Rats from Strasbourg (GAERS, n = 6) and non-epileptic controls (NEC, n = 6), followed by proteomic and metabolomic profiling of the cortical and thalamic tissue of rats from both groups. The general framework of weighted correlation network analysis (WGCNA) was used to identify groups of highly correlated proteins and metabolites, which were then functionally annotated through joint pathway enrichment analysis. In both brain regions a large protein-metabolite module was found to be highly associated with the GAERS strain, absence seizures and associated anxiety and depressive-like phenotype. Quantitative pathway analysis indicated enrichment in oxidative pathways and a downregulation of the lysine degradation pathway in both brain regions. GSTM1 and ALDH2 were identified as central regulatory hubs of the seizure-associated module in the somatosensory cortex and thalamus, respectively. These enzymes are involved in lysine degradation and play important roles in maintaining oxidative balance. We conclude that the dysregulated pathways identified in the seizure-associated module may be involved in the aetiology and maintenance of absence seizure activity. This dysregulated activity could potentially be modulated by targeting one or both central regulatory hubs.
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ItemNo Preview AvailableClimate change and epilepsy: Insights from clinical and basic science studies(ACADEMIC PRESS INC ELSEVIER SCIENCE, 2021-03)Climate change is with us. As professionals who place value on evidence-based practice, climate change is something we cannot ignore. The current pandemic of the novel coronavirus, SARS-CoV-2, has demonstrated how global crises can arise suddenly and have a significant impact on public health. Global warming, a chronic process punctuated by acute episodes of extreme weather events, is an insidious global health crisis needing at least as much attention. Many neurological diseases are complex chronic conditions influenced at many levels by changes in the environment. This review aimed to collate and evaluate reports from clinical and basic science about the relationship between climate change and epilepsy. The keywords climate change, seasonal variation, temperature, humidity, thermoregulation, biorhythm, gene, circadian rhythm, heat, and weather were used to search the published evidence. A number of climatic variables are associated with increased seizure frequency in people with epilepsy. Climate change-induced increase in seizure precipitants such as fevers, stress, and sleep deprivation (e.g. as a result of more frequent extreme weather events) or vector-borne infections may trigger or exacerbate seizures, lead to deterioration of seizure control, and affect neurological, cerebrovascular, or cardiovascular comorbidities and risk of sudden unexpected death in epilepsy. Risks are likely to be modified by many factors, ranging from individual genetic variation and temperature-dependent channel function, to housing quality and global supply chains. According to the results of the limited number of experimental studies with animal models of seizures or epilepsy, different seizure types appear to have distinct susceptibility to seasonal influences. Increased body temperature, whether in the context of fever or not, has a critical role in seizure threshold and seizure-related brain damage. Links between climate change and epilepsy are likely to be multifactorial, complex, and often indirect, which makes predictions difficult. We need more data on possible climate-driven altered risks for seizures, epilepsy, and epileptogenesis, to identify underlying mechanisms at systems, cellular, and molecular levels for better understanding of the impact of climate change on epilepsy. Further focussed data would help us to develop evidence for mitigation methods to do more to protect people with epilepsy from the effects of climate change.