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Objective: To use clinically informed machine learning to derive prediction models for early and late premature death in epilepsy., Methods: This was a population-based primary care observational cohort study. All patients meeting a case definition for incident epilepsy in the Health Improvement Network database for inclusive years 2000-2012 were included. A modified Delphi process identified 30 potential risk factors. Outcome was early (within 4 years of epilepsy diagnosis) and late (4 years or more from diagnosis) mortality. We used regularized logistic regression, support vector machines, Gaussian naive Bayes, and random forest classifiers to predict outcomes. We assessed model calibration, discrimination, and generalizability using the Brier score, mean area under the receiver operating characteristic curve (AUC) derived from stratified fivefold cross-validation, plotted calibration curves, and extracted measures of association where possible., Results: We identified 10 499 presumed incident cases from 11 194 182 patients. All models performed comparably well following stratified fivefold cross-validation, with AUCs ranging from 0.73 to 0.81 and from 0.71 to 0.79 for early and late death, respectively. In addition to comorbid disease, social habits (alcoholism odds ratio [OR] for early death = 1.54, 95% confidence interval [CI] = 1.12-2.11 and OR for late death = 2.62, 95% CI = 1.66-4.16) and treatment patterns (OR for early death when no antiseizure medication [ASM] was prescribed at baseline = 1.33, 95% CI = 1.07-1.64 and OR for late death after receipt of enzyme-inducing ASM at baseline = 1.32, 95% CI = 1.04-1.66) were significantly associated with increased risk of premature death. Baseline ASM polytherapy (OR = 0.55, 95% CI = 0.36-0.85) was associated with reduced risk of early death., Significance: Clinically informed models using routine electronic medical records can be used to predict early and late mortality in epilepsy, with moderate to high accuracy and evidence of generalizability. Medical, social, and treatment-related risk factors, such as delayed ASM prescription and baseline prescription of enzyme-inducing ASMs, were important predictors., (© 2020 International League Against Epilepsy.)

Purpose: The purpose of this article was to investigate the accuracy of the WISC-IV short forms in estimating Full Scale Intelligence Quotient (FSIQ) and General Ability Index (GAI) in pediatric epilepsy., Methods: One hundred and four children with epilepsy completed the WISC-IV as part of a neuropsychological assessment at a tertiary-level children's hospital. The clinical accuracy of eight short forms was assessed in two ways: (a) accuracy within +/- 5 index points of FSIQ and (b) the clinical classification rate according to Wechsler conventions. The sample was further subdivided into low FSIQ (≤ 80) and high FSIQ (> 80)., Results: All short forms were significantly correlated with FSIQ. Seven-subtest (Crawford et al. [2010] FSIQ) and 5-subtest (BdSiCdVcLn) short forms yielded the highest clinical accuracy rates (77%-89%). Overall, a 2-subtest (VcMr) short form yielded the lowest clinical classification rates for FSIQ (35%-63%). The short form yielding the most accurate estimate of GAI was VcSiMrBd (73%-84%)., Conclusions: Short forms show promise as useful estimates. The 7-subtest (Crawford et al., 2010) and 5-subtest (BdSiVcLnCd) short forms yielded the most accurate estimates of FSIQ. VcSiMrBd yielded the most accurate estimate of GAI. Clinical recommendations are provided for use of short forms in pediatric epilepsy.

Objectives: The purpose of this paper was to investigate the contributions of sociodemographic, neurologic, and neuropsychological variables to health-related quality of life (HRQoL) in children with epilepsy and high seizure burden. Focus was placed on the relationship between memory and HRQoL, which has not been previously investigated., Methods: Ninety children with epilepsy receiving clinical care at a tertiary-level children's hospital were retrospectively identified. Primary assessment measures were verbal memory (California Verbal Learning Test-Children's Version) and HRQoL. Other neuropsychological variables included intellectual function, executive function, emotional and behavioral function, and adaptive function. Sociodemographic and neurologic variables were extracted from chart review., Results: No significant correlations were found between HRQoL and sociodemographic or neurologic variables. Moderate correlations were found between neuropsychological variables and HRQoL. Emotional function (Child Behavior Checklist) and verbal memory (California Verbal Learning Test-Children's Version) emerged as significant predictor variables of HRQoL. Low verbal memory was associated with a twofold risk of low HRQoL, emotional and behavioral difficulty with a 10-fold risk, and the combination of emotional and behavioral difficulty and low verbal memory with a 17-fold risk., Conclusions: Verbal memory and emotional and behavioral difficulty are associated with increased risk of low HRQoL, even when other important variables are considered in children with high seizure burden. The results reinforce the importance of neuropsychological assessment in clinical care in pediatric epilepsy and suggest important areas of focus for psychological intervention.

Rationale: The purposes of this study were to 1) conduct a review of neuropsychological (NP) outcomes after epilepsy surgery for DNET and 2) present pre/post-surgical NP results from a series of children with DNET., Methods: First, a systematic literature review was conducted with specific inclusion criteria. Second, a review of DNET surgical patients seen at two tertiary-care hospitals using reliable change methods of NP functioning was conducted., Results: Of 300 citations retrieved, 7 studies met criteria. Studies reported low average to average pre-surgical IQ. Engel Class I outcome was approximately 85%., Case Series: Thirteen children completed pre/post-surgical NP assessments. Pre-surgically, children demonstrated low average to average functioning. Post-surgically, few patients showed reliable change. One-third of children demonstrated psychological improvement., Conclusions: NP outcome following DNET has not been well-described. Children with DNET demonstrate low average to average NP functioning pre-surgically, good seizure outcome, and stable NP functioning post-surgically., (Copyright © 2011 Elsevier Inc. All rights reserved.)