Measuring the prediction difficulty of individual cases in a dataset using machine learning.

Different levels of prediction difficulty are one of the key factors that researchers encounter when applying machine learning to data. Although previous studies have introduced various metrics for assessing the prediction difficulty of individual cases, these metrics require specific dataset preconditions. In this paper, we propose three novel metrics for measuring the prediction difficulty of individual cases using fully-connected feedforward neural networks. The first metric is based on the complexity of the neural network needed to make a correct prediction. The second metric employs a pair of neural networks: one makes a prediction for a given case, and the other predicts whether the prediction made by the first model is likely to be correct. The third metric assesses the variability of the neural network's predictions. We investigated these metrics using a variety of datasets, visualized their values, and compared them to fifteen existing metrics from the literature. The results demonstrate that the proposed case difficulty metrics were better able to differentiate various levels of difficulty than most of the existing metrics and show constant effectiveness across diverse datasets. We expect our metrics will provide researchers with a new perspective on understanding their datasets and applying machine learning in various fields.

Epilepsy surgery in adults older than 50 years: A systematic review and meta-analysis.

OBJECTIVE: Despite the general safety and efficacy of epilepsy surgery, there is evidence that epilepsy surgery remains underutilized. Although there are an increasing number of studies reporting epilepsy surgery in older adults, there is no consensus on whether epilepsy surgery is efficacious or safe for this population. Our objective was to systematically assess the efficacy as well as safety of resective surgery in people aged 50 years or older with drug-resistant epilepsy. METHODS: We considered studies that examine the efficacy and safety of epilepsy surgery in adults aged 50 years and older. Study eligibility was limited to studies carried out after 1990, with a minimum of 10 participants and 6 months of follow-up. We searched the following databases for published studies: Ovid MEDLINE, Ovid Embase, Cumulative Index to Nursing and Allied Health Literature, PsychInfo, and Web of Science Conference Proceedings Citation Index - Science. The risk of bias of each included study was independently assessed by two reviewers using the MINORS (Methodological Index for Non-Randomized Studies) instrument. RESULTS: Eleven case series and 14 cohort studies met the criteria for inclusion, for a total of 1111 older adults who underwent epilepsy surgery along with 4111 adults younger than 50 years as control groups. The pooled cumulative incidence of older adults achieving seizure freedom after resective surgery was 70.1% (95% confidence interval [CI] = 65.3-74.7). There was no evident difference in the incidence of seizure freedom among older adults as compared to younger adults (risk ratio [RR] = 1.05, 95% CI = .97-1.14) in cohort studies. The pooled cumulative incidence of perioperative complications in older adults was 26.2% (95% CI = 21.3-31.7). Among them, 7.5% (95% CI = 5.8-9.5) experienced major complications. Older adults were significantly more at risk of experiencing any complication than younger adults (RR = 2.8, 95% CI = 1.5-5.4). SIGNIFICANCE: Despite important considerations, epilepsy surgery may be considered appropriate among carefully selected individuals older than 50 years.

The Evolving Role of Electroencephalography in Postarrest Care.

Electroencephalography is an accessible, portable, noninvasive and safe means of evaluating a patient's brain activity. It can aid in diagnosis and management decisions for post-cardiac arrest patients with seizures, myoclonus and other non-epileptic movements. It also plays an important role in a multimodal approach to neuroprognostication predicting both poor and favorable outcomes. Individuals ordering, performing and interpreting these tests, regardless of the indication, should understand the supporting evidence, logistical considerations, limitations and impact the results may have on postarrest patients and their families as outlined herein.

A Prospective Post-Marketing Observational Study of Brivaracetam in People With Focal Epilepsy.

We evaluated the effectiveness and tolerability of brivaracetam (BRV), an adjunctive antiseizure medication, as a treatment for focal epilepsy in adults. In this prospective study, we enrolled 51 participants from 3 sites across Canada. At 6 months, 68% (26/38) of participants were still taking BRV, among whom 35% (8/23) attained seizure freedom and 48% (11/23) saw their seizure frequency reduced by over 50%. We did not measure any significant change in irritability, quality of life, depression, and anxiety while treated with BRV. Our findings suggest BRV is effective in reducing seizure frequency among adults with focal epilepsy.

Association of comorbid-socioeconomic clusters with mortality in late onset epilepsy derived through unsupervised machine learning.

BACKGROUND AND OBJECTIVES: Late-onset epilepsy is a heterogenous entity associated with specific aetiologies and an elevated risk of premature mortality. Specific multimorbid-socioeconomic profiles and their unique prognostic trajectories have not been described. We sought to determine if specific clusters of late onset epilepsy exist, and whether they have unique hazards of premature mortality. METHODS: We performed a retrospective observational cohort study linking primary and hospital-based UK electronic health records with vital statistics data (covering years 1998-2019) to identify all cases of incident late onset epilepsy (from people aged ≥65) and 1:10 age, sex, and GP practice-matched controls. We applied hierarchical agglomerative clustering using common aetiologies identified at baseline to define multimorbid-socioeconomic profiles, compare hazards of early mortality, and tabulating causes of death stratified by cluster. RESULTS: From 1,032,129 people aged ≥65, we identified 1048 cases of late onset epilepsy who were matched to 10,259 controls. Median age at epilepsy diagnosis was 68 (interquartile range: 66-72) and 474 (45%) were female. The hazard of premature mortality related to late-onset epilepsy was higher than matched controls (hazard ratio [HR] 1.73; 95% confidence interval [95%CI] 1.51-1.99). Ten unique phenotypic clusters were identified, defined by 'healthy' males and females, ischaemic stroke, intracerebral haemorrhage (ICH), ICH and alcohol misuse, dementia and anxiety, anxiety, depression in males and females, and brain tumours. Cluster-specific hazards were often similar to that derived for late-onset epilepsy as a whole. Clusters that differed significantly from the base late-onset epilepsy hazard were 'dementia and anxiety' (HR 5.36; 95%CI 3.31-8.68), 'brain tumour' (HR 4.97; 95%CI 2.89-8.56), 'ICH and alcohol misuse' (HR 2.91; 95%CI 1.76-4.81), and 'ischaemic stroke' (HR 2.83; 95%CI 1.83-4.04). These cluster-specific risks were also elevated compared to those derived for tumours, dementia, ischaemic stroke, and ICH in the whole population. Seizure-related cause of death was uncommon and restricted to the ICH, ICH and alcohol misuse, and healthy female clusters. SIGNIFICANCE: Late-onset epilepsy is an amalgam of unique phenotypic clusters that can be quantitatively defined. Late-onset epilepsy and cluster-specific comorbid profiles have complex effects on premature mortality above and beyond the base rates attributed to epilepsy and cluster-defining comorbidities alone.

Machine learning using multimodal clinical, electroencephalographic, and magnetic resonance imaging data can predict incident depression in adults with epilepsy: A pilot study.

OBJECTIVE: This study was undertaken to develop a multimodal machine learning (ML) approach for predicting incident depression in adults with epilepsy. METHODS: We randomly selected 200 patients from the Calgary Comprehensive Epilepsy Program registry and linked their registry-based clinical data to their first-available clinical electroencephalogram (EEG) and magnetic resonance imaging (MRI) study. We excluded patients with a clinical or Neurological Disorders Depression Inventory for Epilepsy (NDDI-E)-based diagnosis of major depression at baseline. The NDDI-E was used to detect incident depression over a median of 2.4 years of follow-up (interquartile range [IQR] = 1.5-3.3 years). A ReliefF algorithm was applied to clinical as well as quantitative EEG and MRI parameters for feature selection. Six ML algorithms were trained and tested using stratified threefold cross-validation. Multiple metrics were used to assess model performances. RESULTS: Of 200 patients, 150 had EEG and MRI data of sufficient quality for ML, of whom 59 were excluded due to prevalent depression. Therefore, 91 patients (41 women) were included, with a median age of 29 (IQR = 22-44) years. A total of 42 features were selected by ReliefF, none of which was a quantitative MRI or EEG variable. All models had a sensitivity > 80%, and five of six had an F1 score ≥ .72. A multilayer perceptron model had the highest F1 score (median = .74, IQR = .71-.78) and sensitivity (84.3%). Median area under the receiver operating characteristic curve and normalized Matthews correlation coefficient were .70 (IQR = .64-.78) and .57 (IQR = .50-.65), respectively. SIGNIFICANCE: Multimodal ML using baseline features can predict incident depression in this population. Our pilot models demonstrated high accuracy for depression prediction. However, overall performance and calibration can be improved. This model has promise for identifying those at risk for incident depression during follow-up, although efforts to refine it in larger populations along with external validation are required.

Sensitivity and specificity of alternative screening methods for systematic reviews using text mining tools.

OBJECTIVES: To evaluate the impact of text mining (TM) on the sensitivity and specificity of title and abstract screening strategies for systematic reviews (SRs). STUDY DESIGN AND SETTING: Twenty reviewers each evaluated a 500-citation set. We compared five screening methods: conventional double screen (CDS), single screen, double screen with TM, combined double screen and single screen with TM, and single screen with TM. Rayyan, Abstrackr, and SWIFT-Review were used for each TM method. The results of a published SR were used as the reference standard. RESULTS: The mean sensitivity and specificity achieved by CDS were 97.0% (95% confidence interval [CI]: 94.7, 99.3) and 95.0% (95% CI: 93.0, 97.1). When compared with single screen, CDS provided a greater sensitivity without a decrease in specificity. Rayyan, Abstrackr, and SWIFT-Review identified all relevant studies. Specificity was often higher for TM-assisted methods than that for CDS, although with mean differences of only one-to-two percentage points. For every 500 citations not requiring manual screening, 216 minutes (95% CI: 169, 264) could be saved. CONCLUSION: TM-assisted screening methods resulted in similar sensitivity and modestly improved specificity as compared to CDS. The time saved with TM makes this a promising new tool for SR.

Independent Associations of Incident Epilepsy and Enzyme-Inducing and Non-Enzyme-Inducing Antiseizure Medications With the Development of Osteoporosis.

Importance: Both epilepsy and enzyme-inducing antiseizure medications (eiASMs) having varying reports of an association with increased risks for osteoporosis. Objective: To quantify and model the independent hazards for osteoporosis associated with incident epilepsy and eiASMS and non-eiASMs. Design, Setting, and Participants: This open cohort study covered the years 1998 to 2019, with a median (IQR) follow-up of 5 (1.7-11.1) years. Data were collected for 6275 patients enrolled in the Clinical Practice Research Datalink and from hospital electronic health records. No patients who met inclusion criteria (Clinical Practice Research Datalink-acceptable data, aged 18 years or older, follow-up after the Hospital Episode Statistics patient care linkage date of 1998, and free of osteoporosis at baseline) were excluded or declined. Exposure: Incident adult-onset epilepsy using a 5-year washout and receipt of 4 consecutive ASMs. Main Outcomes and Measures: The outcome was incident osteoporosis as determined through Cox proportional hazards or accelerated failure time models where appropriate. Incident epilepsy was treated as a time-varying covariate. Analyses controlled for age, sex, socioeconomic status, cancer, 1 or more years of corticosteroid use, body mass index, bariatric surgery, eating disorders, hyperthyroidism, inflammatory bowel disease, rheumatoid arthritis, smoking status, falls, fragility fractures, and osteoporosis screening tests. Subsequent analyses (1) excluded body mass index, which was missing in 30% of patients; (2) applied propensity score matching for receipt of an eiASM; (3) restricted analyses to only those with incident onset epilepsy; and (4) restricted analyses to patients who developed epilepsy at age 65 years or older. Analyses were performed between July 1 and October 31, 2022, and in February 2023 for revisions. Results: Of 8 095 441 adults identified, 6275 had incident adult-onset epilepsy (3220 female [51%] and 3055 male [49%]; incidence rate, 62 per 100 000 person-years) with a median (IQR) age of 56 (38-73) years. When controlling for osteoporosis risk factors, incident epilepsy was independently associated with a 41% faster time to incident osteoporosis (time ratio [TR], 0.59; 95% CI, 0.52-0.67; P < .001). Both eiASMs (TR, 0.91; 95% CI, 0.87-0.95; P < .001) and non-eiASMs (TR, 0.77; 95% CI, 0.76-0.78; P < .001) were also associated with significant increased risks independent of epilepsy, accounting for 9% and 23% faster times to development of osteoporosis, respectively. The independent associations among epilepsy, eiASMs, and non-eiASMs remained consistent in propensity score-matched analyses, cohorts restricted to adult-onset epilepsy, and cohorts restricted to late-onset epilepsy. Conclusions and Relevance: These findings suggest that epilepsy is independently associated with a clinically meaningful increase in the risk for osteoporosis, as are both eiASMs and non-eiASMs. Routine screening and prophylaxis should be considered in all people with epilepsy.

Patient experiences of virtual care across specialist neuroscience and psychiatry clinics related to the second wave of the COVID-19 pandemic in Calgary, Alberta.

Purpose: The emergence of the COVID-19 (SARS-CoV-2) pandemic has led to public health restrictions and a shift towards virtual care and telehealth. The aim of this study was to explore barriers and facilitators of virtual care from the perspective of neurological and psychiatric patients. Methods: One-on-one interviews were conducted remotely using telephone and online video teleconferencing. There was a total of 57 participants, and a thematic content analysis was conducted using NVivo software. Results: The two main themes were (1) virtual health service delivery and (2) virtual physician/patient interaction, with subthemes around how virtual care improved accessibility of care for patients and improved patient-centered care; how privacy and technical issues impact patients using virtual care; and the need for relationality and connection between health care providers and patients while using virtual care. Conclusions: This study showed that virtual care can increase accessibility and efficiency for patients and providers, indicating its potential for ongoing use in the delivery of clinical care. Virtual care was found to be an acceptable mode of healthcare delivery from the perspective of patients; however, there is a continued need for relationship-building between care providers and patients.

Neuroprognostication in the Post Cardiac Arrest Patient: A Canadian Cardiovascular Society Position Statement.

Cardiac arrest (CA) is associated with a low rate of survival with favourable neurologic recovery. The most common mechanism of death after successful resuscitation from CA is withdrawal of life-sustaining measures on the basis of perceived poor neurologic prognosis due to underlying hypoxic-ischemic brain injury. Neuroprognostication is an important component of the care pathway for CA patients admitted to hospital but is complex, challenging, and often guided by limited evidence. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system to evaluate the evidence underlying factors or diagnostic modalities available to determine prognosis, recommendations were generated in the following domains: (1) circumstances immediately after CA; (2) focused neurologic exam; (3) myoclonus and seizures; (4) serum biomarkers; (5) neuroimaging; (6) neurophysiologic testing; and (7) multimodal neuroprognostication. This position statement aims to serve as a practical guide to enhance in-hospital care of CA patients and emphasizes the adoption of a systematic, multimodal approach to neuroprognostication. It also highlights evidence gaps.

The phenotypic and genotypic spectrum of epilepsy and intellectual disability in adults: Implications for genetic testing.

OBJECTIVE: The phenotypic and genotypic spectrum of adult patients with epilepsy and intellectual disability (ID) is less clear than in children. We investigated an adult patient cohort to further elucidate this and inform the genetic testing approach. METHODS: Fifty-two adult patients (30 male, 22 female) with epilepsy, at least mild ID and no known genetic or acquired cause were included and phenotyped. Variants identified through exome sequencing were evaluated using ACMG criteria. Identified variants were compared with commercially available gene panels. Cluster analysis of two features, age at seizure onset and age at ascertainment of cognitive deficits, was performed. RESULTS: Median age was 27 years (range 20-57 years) with median seizure onset at 3 years and median ascertainment of cognitive deficits at 1 year. Likely pathogenic/pathogenic variants were identified in 16/52 patients (31%) including 14 (27%) single nucleotide variants and 2 (4%) copy number variants. Simulated yield of commercial gene panels varied between 13% in small (≤144 genes) and 27% in large panels (≥1478 genes). Cluster analysis (optimal number 3 clusters) identified a cluster with early seizure onset and early developmental delay (developmental and epileptic encephalopathy, n = 26), a cluster with early developmental delay but late seizure onset (ID with epilepsy, n = 16) and a third cluster with late ascertainment of cognitive deficits and variable seizure onset (n = 7). The smaller gene panels particularly missed the genes identified in the cluster with early ascertainment of cognitive deficits and later onset of epilepsy (0/4) as opposed to the cluster with developmental and epileptic encephalopathy (7/10). SIGNIFICANCE: Our data indicates that adult patients with epilepsy and ID represent a heterogeneous cohort that includes grown-up patients with DEE but also patients with primary ID and later onset of epilepsy. To maximize diagnostic yield in this cohort either large gene panels or exome sequencing should be used.

Medical and surgical treatment of epilepsy in older adults: A national survey.

OBJECTIVE: There are no clinical guidelines dedicated to the treatment of epilepsy in older adults. We investigated physician opinion and practice regarding the treatment of people with epilepsy aged 65 years or older. We also sought to study how our opinion and practice varied between geriatricians, general neurologists, and epilepsy neurologists (i.e., epileptologists). METHODS: We initially piloted our survey to measure test-retest reliability. Once finalized, we disseminated the survey via two rounds of facsimiles, and then conventional mail, to eligible individuals listed in a national directory of Canadian physicians. We used descriptive statistics such as stacked bar charts and tables to illustrate our findings. RESULTS: One hundred forty-four physicians (104 general neurologists, 25 geriatricians, and 15 epileptologists) answered our survey in its entirety (overall response rate of 13.2%). Levetiracetam and lamotrigine were the preferred antiseizure medications (ASMs) to treat older adults with epilepsy. Two thirds of epileptologists and almost half of general neurologists would consider prescribing lacosamide in >50% of people aged >65 years; only one geriatrician was of the same opinion. More than 40% of general neurologists and geriatricians erroneously believed that none of the ASMs mentioned in our survey was previously studied in randomized controlled trials specific to the treatment of epilepsy in older adults. Epileptologists were more likely as compared to general neurologists and geriatricians to recommend epilepsy surgery (e.g., 66.6% vs. 22.9%-37.5% among older adults). SIGNIFICANCE: Therapeutic decisions for older adults with epilepsy are heterogeneous between physician groups and sometimes misalign with available clinical evidence. Our surveyed physicians differed in their approach to ASM choice as well as perception of surgery in older adults with epilepsy. These findings likely reflect the lack of clinical guidelines dedicated to this population and the deficient implementation of best practices.

Association Between Frailty and Antiseizure Medication Tolerability in Older Adults With Epilepsy.

BACKGROUND AND OBJECTIVE: Frailty is an important aspect of biological aging, referring to the increased vulnerability of individuals with frailty to physical and psychological stressors. While older adults with epilepsy are an important and distinct clinical group, there are no data on frailty in this population. We hypothesize that frailty will correlate with the seizure frequency and especially the tolerability of antiseizure medications (ASMs) in older adults with epilepsy. METHODS: We recruited individuals aged 60 years or older with active epilepsy from 4 Canadian hospital centers. We reported the seizure frequency in the 3 months preceding the interview, while ASM tolerability was quantified using the Liverpool Adverse Events Profile (LAEP). We applied 3 measures of frailty: grip strength as a measure of physical frailty, 1 self-reported score (Edmonton frail score [EFS]), and 1 scale completed by a healthcare professional (clinical frailty scale [CFS]). We also administered standardized questionnaires measuring levels of anxiety, depression, functional disability, and quality of life and obtained relevant clinical and demographic data. RESULTS: Forty-three women and 43 men aged 60-93 years were recruited, 87% of whom had focal epilepsy, with an average frequency of 3.4 seizures per month. Multiple linear regression and zero-inflated negative binomial regression models showed that EFS and CFS scores were associated with decreased ASM tolerability, each point increase leading to 1.83 (95% CI: 0.67-4.30) and 2.49 (95% CI: 1.27-2.39) point increases on the LAEP scale, respectively. Neither the EFS and CFS scores nor grip strength were significantly associated with seizure frequency. The EFS was moderately correlated with depression, anxiety, quality of life, and functional disability, demonstrating the best construct validity among the 3 tested measures of frailty. DISCUSSION: The EFS was significantly, both statistically and clinically, associated with ASM tolerability. It also showed multiple advantages in performance while assessing for frailty in older adults with epilepsy, when compared with the 2 other measures of frailty that we tested. Future studies must focus on what role the EFS during epilepsy diagnosis may play in ASM selection among older adults with epilepsy.

Timing of referral to evaluate for epilepsy surgery: Expert Consensus Recommendations from the Surgical Therapies Commission of the International League Against Epilepsy.

Epilepsy surgery is the treatment of choice for patients with drug-resistant seizures. A timely evaluation for surgical candidacy can be life-saving for patients who are identified as appropriate surgical candidates, and may also enhance the care of nonsurgical candidates through improvement in diagnosis, optimization of therapy, and treatment of comorbidities. Yet, referral for surgical evaluations is often delayed while palliative options are pursued, with significant adverse consequences due to increased morbidity and mortality associated with intractable epilepsy. The Surgical Therapies Commission of the International League Against Epilepsy (ILAE) sought to address these clinical gaps and clarify when to initiate a surgical evaluation. We conducted a Delphi consensus process with 61 epileptologists, epilepsy neurosurgeons, neurologists, neuropsychiatrists, and neuropsychologists with a median of 22 years in practice, from 28 countries in all six ILAE world regions. After three rounds of Delphi surveys, evaluating 51 unique scenarios, we reached the following Expert Consensus Recommendations: (1) Referral for a surgical evaluation should be offered to every patient with drug-resistant epilepsy (up to 70 years of age), as soon as drug resistance is ascertained, regardless of epilepsy duration, sex, socioeconomic status, seizure type, epilepsy type (including epileptic encephalopathies), localization, and comorbidities (including severe psychiatric comorbidity like psychogenic nonepileptic seizures [PNES] or substance abuse) if patients are cooperative with management; (2) A surgical referral should be considered for older patients with drug-resistant epilepsy who have no surgical contraindication, and for patients (adults and children) who are seizure-free on 1-2 antiseizure medications (ASMs) but have a brain lesion in noneloquent cortex; and (3) referral for surgery should not be offered to patients with active substance abuse who are noncooperative with management. We present the Delphi consensus results leading up to these Expert Consensus Recommendations and discuss the data supporting our conclusions. High level evidence will be required to permit creation of clinical practice guidelines.

Effect of Training on Visual Identification of High Frequency Oscillations-A Delphi-Style Intervention.

OBJECTIVE: We examined the effect of a simple Delphi-method feedback on visual identification of high frequency oscillations (HFOs) in the ripple (80-250 Hz) band, and assessed the impact of this training intervention on the interrater reliability and generalizability of HFO evaluations. METHODS: We employed a morphology detector to identify potential HFOs at two thresholds and presented them to visual reviewers to assess the probability of each epoch containing an HFO. We recruited 19 board-certified epileptologists with various levels of experience to complete a series of HFO evaluations during three sessions. A Delphi-style intervention was used to provide feedback on the performance of each reviewer relative to their peers. A delayed-intervention paradigm was used, in which reviewers received feedback either before or after the second session. ANOVAs were used to assess the effect of the intervention on the reviewers' evaluations. Generalizability theory was used to assess the interrater reliability before and after the intervention. RESULTS: The intervention, regardless of when it occurred, resulted in a significant reduction in the variability between reviewers in both groups (p GroupDI = 0.037, p GroupEI = 0.003). Prior to the delayed-intervention, the group receiving the early intervention showed a significant reduction in variability (p GroupEI = 0.041), but the delayed-intervention group did not (p GroupDI = 0.414). Following the intervention, the projected number of reviewers required to achieve strong generalizability decreased from 35 to 16. SIGNIFICANCE: This study shows a robust effect of a Delphi-style intervention on the interrater variability, reliability, and generalizability of HFO evaluations. The observed decreases in HFO marking discrepancies across 14 of the 15 reviewers are encouraging: they are necessarily associated with an increase in interrater reliability, and therefore with a corresponding decrease in the number of reviewers required to achieve strong generalizability. Indeed, the reliability of all reviewers following the intervention was similar to that of experienced reviewers prior to intervention. Therefore, a Delphi-style intervention could be implemented either to sufficiently train any reviewer, or to further refine the interrater reliability of experienced reviewers. In either case, a Delphi-style intervention would help facilitate the standardization of HFO evaluations and its implementation in clinical care.

Validity and reliability of global ratings of satisfaction with epilepsy surgery.

OBJECTIVE: We aimed to assess the reliability and validity of single-item global ratings (GR) of satisfaction with epilepsy surgery. METHODS: We recruited 240 patients from four centers in Canada and Sweden who underwent epilepsy surgery ≥1 year earlier. Participants completed a validated questionnaire on satisfaction with epilepsy surgery (the ESSQ-19), plus a single-item GR of satisfaction with epilepsy surgery twice, 4-6 weeks apart. They also completed validated questionnaires on quality of life, depression, health state utilities, epilepsy severity and disability, medical treatment satisfaction and social desirability. Test-retest reliability of the GR was assessed with the intra-class correlation coefficient (ICC). Construct and criterion validity were examined with polyserial correlations between the GR measure of satisfaction and validated questionnaires and with the ESSQ-19 summary score. Non-parametric rank tests evaluated levels of satisfaction, and ROC analysis assessed the ability of GRs to distinguish among clinically different patient groups. RESULTS: Median age and time since surgery were 42 years (IQR 32-54) and 5 years (IQR 2-8), respectively. The GR demonstrated good to excellent test-retest reliability (ICC = 0.76; 95% CI 0.67-0.84) and criterion validity (0.85; 95% CI 0.81-0.89), and moderate correlations in the expected direction with instruments assessing quality of life (0.59; 95% CI 0.51-0.63), health utilities (0.55; 95% CI 0.45-0.65), disability (-0.51; 95% CI -0.41, -0.61), depression (-0.48; 95% CI -0.38, -0.58), and epilepsy severity (-0.48; 95% CI -0.38, -0.58). As expected, correlations were lower for social desirability (0.40; 95% CI 0.28-0.52) and medical treatment satisfaction (0.33; 95% CI 0.21-0.45). The GR distinguished participants who were seizure-free (AUC 0.75; 95% CI 0.67-0.82), depressed (AUC 0.75; 95% CI 0.67-0.83), and self-rated as having more severe epilepsy (AUC 0.78; 95% CI 0.71-0.85) and being more disabled (AUC 0.82; 95% CI 0.74-0.90). SIGNIFICANCE: The GR of epilepsy surgery satisfaction showed good measurement properties, distinguished among clinically different patient groups, and appears well-suited for use in clinical practice and research.

EEG Patterns and Outcomes After Hypoxic Brain Injury: A Systematic Review and Meta-analysis.

Electroencephalography (EEG) is used to prognosticate recovery in comatose patients with hypoxic ischemic brain injury (HIBI) secondary to cardiac arrest. We sought to determine the prognostic use of specific EEG patterns for predicting disability and death following HIBI secondary to cardiac arrest. This systematic review searched Medline, Embase, and Cochrane Central up to January 2020. We included original research involving prospective and retrospective cohort studies relating specific EEG patterns to disability and death in comatose adult patients suffering HIBI post cardiac arrest requiring admission to an intensive care setting. We evaluated study quality using the Quality of Diagnostic Accuracy Studies 2 tool. Descriptive statistics were used to summarize study, patient, and EEG characteristics. We pooled study-level estimates of sensitivity and specificity for EEG patterns defined a priori using a random effect bivariate and univariate meta-analysis when appropriate. Funnel plots were used to assess publication bias. Of 5191 abstracts, 333 were reviewed in full text, of which 57 were included in the systematic review and 32 in meta-analyses. No reported EEG pattern was found to be invariably associated with death or disability across all studies. Pooled specificities of status epilepticus, burst suppression, and electrocerebral silence were high (92-99%), but sensitivities were low (6-39%) when predicting a composite outcome of disability and death. Study quality varied depending on domain; patient flow and timing performed was well conducted in all, whereas EEG interpretation was retrospective in 17 of 39 studies. Accounting for variable study quality, EEG demonstrates high specificity with a low risk of false negative outcome attribution for disability and death when status epilepticus, burst suppression, or electrocerebral silence is detected. Increased use of standardized cross-study protocols and definitions of EEG patterns are required to better evaluate the prognostic use of EEG for comatose patients with HIBI following cardiac arrest.

Repeated measures discriminant analysis using multivariate generalized estimation equations.

Discriminant analysis procedures that assume parsimonious covariance and/or means structures have been proposed for distinguishing between two or more populations in multivariate repeated measures designs. However, these procedures rely on the assumptions of multivariate normality which is not tenable in multivariate repeated measures designs which are characterized by binary, ordinal, or mixed types of response distributions. This study investigates the accuracy of repeated measures discriminant analysis (RMDA) based on the multivariate generalized estimating equations (GEE) framework for classification in multivariate repeated measures designs with the same or different types of responses repeatedly measured over time. Monte Carlo methods were used to compare the accuracy of RMDA procedures based on GEE, and RMDA based on maximum likelihood estimators (MLE) under diverse simulation conditions, which included number of repeated measure occasions, number of responses, sample size, correlation structures, and type of response distribution. RMDA based on GEE exhibited higher average classification accuracy than RMDA based on MLE especially in multivariate non-normal distributions. Three repeatedly measured responses namely severity of epilepsy, current number of anti-epileptic drugs, and parent-reported quality of life in children with epilepsy were used to demonstrate the application of these procedures.