Global assessment of the severity of epilepsy (GASE) Scale in children: Validity, reliability, responsiveness

Summary Objective The Global Assessment of Severity of Epilepsy (GASE) Scale is a single-item, 7-point global rating scale designed for neurologist-report of overall severity of epilepsy in children. Building on previous preliminary evidence of its validity and reliability for research and clinical use, this study evaluated the GASE Scale\u27s construct validity, reliability, and responsiveness to changes in severity of epilepsy. Methods Data used for the study arose from the Health-Related Quality of Life in Children with Epilepsy Study (HERQULES), a 2-year multicenter prospective cohort study (n = 374) with observations taken at baseline, and 6, 12, and 24 months after diagnosis. Construct validity and reliability were quantified using Spearman\u27s correlation and intraclass correlation coefficient (ICC). Responsiveness was assessed using both distribution-based and anchor-based indices. Results The GASE Scale was at least moderately correlated (r ≥ 0.30) with several key clinical aspects and most strongly correlated with frequency and intensity of seizures and interference of epilepsy or drugs with daily activities (r \u3e 0.30). Total variation in GASE Scale scores explained by seven core clinical aspects of epilepsy increased over time (R2 = 28% at baseline to R2 = 70% at 24 months). The GASE Scale had modest test-retest reliability (ICC range: 0.52-0.64) and was responsive to changes in clinical criteria (standardized response mean range: 0.49-0.68; probability of change range: 0.69-0.75; Guyatt\u27s responsiveness statistic range: 0.56-0.84). The GASE Scale showed potential to discriminate stable and changed patients according to select criteria and to a composite score (area under the receiver operating characteristic [ROC] curve range: 0.50-0.67). Significance Results offer additional evidence in support of the GASE Scale\u27s validity, reliability, as well as responsiveness to changes in severity of epilepsy in children. We conclude that the GASE Scale is a potentially useful tool for assessing the severity of epilepsy in both clinical and research settings

Trajectories of health-related quality of life in children with epilepsy: A cohort study

Purpose Little is known about subgroups of children with epilepsy who may experience less favorable outcomes over time. The objectives of this study were to document trajectories of health-related quality of life (HRQL) and to identify predictors of the trajectory group in children with new-onset epilepsy. Methods Data were obtained from the Health Related Quality of Life in Children with Epilepsy Study, a prospective multisite study of children 4-12 years old with new-onset epilepsy followed for 24 months. Health-related quality of life was measured using the Quality of Life in Childhood Epilepsy questionnaire. Trajectories of HRQL were investigated using latent class trajectory modeling. Multinomial logistic regression was used to identify child, parent, and family predictors of HRQL trajectories. Key Findings A total of 374 families responded at baseline and 283 (76%) completed the study. Five HRQL trajectories were observed: low-increasing (4%), moderate-decreasing (12%), moderate-increasing (22%), high-increasing (32%), and high-stable (30%). Many children in the low-increasing, moderate-increasing, high-increasing, and high-stable had clinically meaningful improvements in HRQL: 82%, 47%, 63%, and 44%, respectively. In contrast, the majority of children in the moderate-decreasing group (56%) experienced clinically meaningful declines in their HRQL. Factors predicting trajectories were number of antiepileptic drugs prescribed, presence of comorbid behavior or cognitive problems, parent depression, and family functioning and demands. Significance Results suggested that children with epilepsy are not homogenous but rather consist of groups with different trajectories and unique predictors of HRQL. Problems associated with child behavior and cognition were the strongest predictors identified. Given that several risk factors are modifiable, it is important to examine these as potential targets within a family-centered framework to improve HRQL of children with new-onset epilepsy. © Wiley Periodicals, Inc. © 2013 International League Against Epilepsy

Quality of life in children with new-onset epilepsy; A 2-year prospective cohort study

Objectives: To assess health-related quality of life (HRQL) over 2 years in children 4-12 years old with new-onset epilepsy and risk factors. Methods: Data are from a multicenter prospective cohort study, the Health-Related Quality of Life Study in Children with Epilepsy Study (HERQULES). Parents reported on children\u27s HRQL and family factors and neurologists on clinical characteristics 4 times. Mean subscale and summary scores were computed for HRQL. Individual growth curve models identified trajectories of change in HRQL scores. Multiple regression identified baseline risk factors for HRQL 2 years later. Results: A total of 374 (82%) questionnaires were returned postdiagnosis and 283 (62%) of eligible parents completed all 4. Growth rates for HRQL summary scores were most rapid during the first 6 months and then stabilized. About one-half experienced clinically meaningful improvements in HRQL, one-third maintained their same level, and one-fifth declined. Compared with the general population, at 2 years our sample scored significantly lower on one-third of CHQ subscales and the psychosocial summary. After controlling for baseline HRQL, cognitive problems, poor family functioning, and high family demands were risk factors for poor HRQL 2 years later. Conclusions: On average, HRQL was relatively good but with highly variable individual trajectories. At least one-half did not experience clinically meaningful improvements or declined over 2 years. Cognitive problems were the strongest risk factor for compromised HRQL 2 years after diagnosis and may be largely responsible for declines in the HRQL of children newly diagnosed with epilepsy. © 2012 by AAN Enterprises, Inc

Ontology-Based Feature Engineering in Machine Learning Workflows for Heterogeneous Epilepsy Patient Records

Biomedical ontologies are widely used to harmonize heterogeneous data and integrate large volumes of clinical data from multiple sources. This study analyzed the utility of ontologies beyond their traditional roles, that is, in addressing a challenging and currently underserved field of feature engineering in machine learning workflows. Machine learning workflows are being increasingly used to analyze medical records with heterogeneous phenotypic, genotypic, and related medical terms to improve patient care. We performed a retrospective study using neuropathology reports from the German Neuropathology Reference Center for Epilepsy Surgery at Erlangen, Germany. This cohort included 312 patients who underwent epilepsy surgery and were labeled with one or more diagnoses, including dual pathology, hippocampal sclerosis, malformation of cortical dysplasia, tumor, encephalitis, and gliosis. We modeled the diagnosis terms together with their microscopy, immunohistochemistry, anatomy, etiologies, and imaging findings using the description logic-based Web Ontology Language (OWL) in the Epilepsy and Seizure Ontology (EpSO). Three tree-based machine learning models were used to classify the neuropathology reports into one or more diagnosis classes with and without ontology-based feature engineering. We used five-fold cross validation to avoid overfitting with a fixed number of repetitions while leaving out one subset of data for testing, and we used recall, balanced accuracy, and hamming loss as performance metrics for the multi-label classification task. The epilepsy ontology-based feature engineering approach improved the performance of all the three learning models with an improvement of 35.7%, 54.5%, and 33.3% in logistics regression, random forest, and gradient tree boosting models respectively. The run time performance of all three models improved significantly with ontology-based feature engineering with gradient tree boosting model showing a 93.8% reduction in the time required for training and testing of the model. Although, all three models showed an overall improved performance across the three-performance metrics using ontology-based feature engineering, the rate of improvement was not consistent across all input features. To analyze this variation in performance, we computed feature importance scores and found that microscopy had the highest importance score across the three models, followed by imaging, immunohistochemistry, and anatomy in a decreasing order of importance scores. This study showed that ontologies have an important role in feature engineering to make heterogeneous clinical data accessible to machine learning models and also improve the performance of machine learning models in multilabel multiclass classification tasks

A structured, blended learning program towards proficiency in epileptology: the launch of the ILAE Academy Level 2 Program

The ILAE Academy is the online learning platform of the International League Against Epilepsy (ILAE) and offers a structured educational program addressing the competency-based ILAE curriculum in epileptology. The platform was launched in July 2020 with a self-paced course portfolio of interactive e-learning modules addressing ILAE Level 1 learning objectives, defined as the entry level in epileptology. Using feedback questionnaires from completed Level 1 courses as well as sociodemographic and learning-related data obtained from 47 participants, we show that over 50% of learners have an entry level in epileptology and do not have access to on-site training and over 40% do not have access to on-site training. Most respondents found the case-based e-learning modules relevant to their practice needs, and the time for completion was regarded as viable for most, reiterating the value of an online self-paced training in the field. Participants who have successfully completed all compulsory e-learning material of the Level 1 program and received their final certificate will now be eligible to subscribe to the Level 2 program. The Level 2 program addressing the proficiency level of the ILAE curriculum of epileptology was launched on the ILAE Academy platform in May 2022. The Level 2 program will offer an evolving series of self-paced, interactive, case-based e-learning modules on diagnosis, treatment, and counseling of common as well as rare epilepsies at a higher level of care. An interactive online EEG and MRI reader was developed and is embedded into the course content to satisfy the demands of the learners. The hallmark of this level will be the blended learning with tutored online courses, e.g., the established VIREPA courses on EEG and the newly introduced VIREPA MRI program. Our distinguished faculty will hold live tutored online courses in small groups in various languages and continental time zones. Finally, the ILAE face-to-face curricular teaching courses at summer schools and congresses will represent another pillar of this advanced teaching level. The ILAE Academy will also provide Continuing Medical Education (CME) credits to support career planning in epileptology

Ensemble-based Classification Models for Predicting Post-Operative Mortality Risk in Coronary Artery Disease

Introduction There has been an increased demand for more accurate prediction tools to aid clinical decision-making regarding disease diagnosis prognosis for coronary artery disease(CAD) patients. Patients undergoing CABG surgery are older and a larger number have had previous heart surgery. Consequently, mortality after CABG is expected to increase despite procedural advances. Objectives and Approach This study aims to compare the predictive performance of random forest(RF) and logistic regression(LR) classifiers for predicting 30-day and 1-year post-operative mortality risk in CAD patients who underwent CABG. Data was obtained by linking the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease(APPROACH) registry, a prospective longitudinal data of patients undergoing cardiac catheterization in Alberta, Canada, to vital statistics database. All patients who underwent first-time isolated CABG between January 1, 2007 and December 31, 2012 were included in the analysis. Area under the receiver operating curve(AUC) was used to compare the predictive performance of LR and RF regression. Results Of the 4,908 eligible subjects who underwent isolated CABG during the study period, mortality estimates of 30-day and 1-year post CABG surgery were 1.59% and 3.85%, respectively. Descriptive analysis revealed that age, sex, hypertension, dialysis, cerebrovascular disease, chronic obstructive pulmonary disease, and chronic heart failure were associated with 30-day and 1-year mortality. The accuracy of the LR and RF regression classifiers in predicting 30-day mortality were 74.1, and 99.7%, respectively. While the accuracy of the former and latter classifiers in predicting 1-year post CABG mortality were 74% and 97.4%, respectively. Conclusion/Implications This study shows that RF classifier results in better predictive accuracy than LR in predicting post-operating mortality risk in CAD patients. Machine learning models are potentially usefully for developing clinical prediction models that can be used to aid the monitoring of post-discharge outcomes in the management of cardiovascular diseases

A life in progress: motion and emotion in the autobiography of Robert M. La Follette

This article is a study of a La Follette’s Autobiography, the autobiography of the leading Wisconsin progressive Robert M. La Follette, which was published serially in 1911 and, in book form, in 1913. Rather than focusing, as have other historians, on which parts of La Follette’s account are accurate and can therefore be trusted, it explains instead why and how this major autobiography was conceived and written. The article shows that the autobiography was the product of a sustained, complex, and often fraught series of collaborations among La Follette’s family, friends, and political allies, and in the process illuminates the importance of affective ties as well as political ambition and commitment in bringing the project to fruition. In the world of progressive reform, it argues, personal and political experiences were inseparable

Methodology for classification and definition of epilepsy syndromes with list of syndromes: Report of the ILAE Task Force on Nosology and Definitions

Epilepsy syndromes have been recognized for >50 years, as distinct electroclinical phenotypes with therapeutic and prognostic implications. Nonetheless, no formally accepted International League Against Epilepsy (ILAE) classification of epilepsy syndromes has existed. The ILAE Task Force on Nosology and Definitions was established to reach consensus regarding which entities fulfilled criteria for an epilepsy syndrome and to provide definitions for each syndrome. We defined an epilepsy syndrome as "a characteristic cluster of clinical and electroencephalographic features, often supported by specific etiological findings (structural, genetic, metabolic, immune, and infectious)." The diagnosis of a syndrome in an individual with epilepsy frequently carries prognostic and treatment implications. Syndromes often have age-dependent presentations and a range of specific comorbidities. This paper describes the guiding principles and process for syndrome identification in both children and adults, and the template of clinical data included for each syndrome. We divided syndromes into typical age at onset, and further characterized them based on seizure and epilepsy types and association with developmental and/or epileptic encephalopathy or progressive neurological deterioration. Definitions for each specific syndrome are contained within the corresponding position papers

The ILAE consensus classification of focal cortical dysplasia: An update proposed by an ad hoc task force of the ILAE diagnostic methods commission

Ongoing challenges in diagnosing focal cortical dysplasia (FCD) mandate continuous research and consensus agreement to improve disease definition and classification. An International League Against Epilepsy (ILAE) Task Force (TF) reviewed the FCD classification of 2011 to identify existing gaps and provide a timely update. The following methodology was applied to achieve this goal: a survey of published literature indexed with ((Focal Cortical Dysplasia) AND (epilepsy)) between 01/01/2012 and 06/30/2021 (n = 1349) in PubMed identified the knowledge gained since 2012 and new developments in the field. An online survey consulted the ILAE community about the current use of the FCD classification scheme with 367 people answering. The TF performed an iterative clinico-pathological and genetic agreement study to objectively measure the diagnostic gap in blood/brain samples from 22 patients suspicious for FCD and submitted to epilepsy surgery. The literature confirmed new molecular-genetic characterizations involving the mechanistic Target Of Rapamycin (mTOR) pathway in FCD type II (FCDII), and SLC35A2 in mild malformations of cortical development (mMCDs) with oligodendroglial hyperplasia (MOGHE). The electro-clinical-imaging phenotypes and surgical outcomes were better defined and validated for FCDII. Little new information was acquired on clinical, histopathological, or genetic characteristics of FCD type I (FCDI) and FCD type III (FCDIII). The survey identified mMCDs, FCDI, and genetic characterization as fields for improvement in an updated classification. Our iterative clinico-pathological and genetic agreement study confirmed the importance of immunohistochemical staining, neuroimaging, and genetic tests to improve the diagnostic yield. The TF proposes to include mMCDs, MOGHE, and “no definite FCD on histopathology” as new categories in the updated FCD classification. The histopathological classification can be further augmented by advanced neuroimaging and genetic studies to comprehensively diagnose FCD subtypes; these different levels should then be integrated into a multi-layered diagnostic scheme. This update may help to foster multidisciplinary efforts toward a better understanding of FCD and the development of novel targeted treatment options