Predictive models of epilepsy outcomes.

PURPOSE OF REVIEW: Multiple complex medical decisions are necessary in the course of a chronic disease like epilepsy. Predictive tools to assist physicians and patients in navigating this complexity have emerged as a necessity and are summarized in this review. RECENT FINDINGS: Nomograms and online risk calculators are user-friendly and offer individualized predictions for outcomes ranging from safety of antiseizure medication withdrawal (accuracy 65-73%) to seizure-freedom, naming, mood, and language outcomes of resective epilepsy surgery (accuracy 72-81%). Improving their predictive performance is limited by the nomograms' inability to ingest complex data inputs. Conversely, machine learning offers the potential of multimodal and expansive model inputs achieving human-expert level accuracy in automated scalp electroencephalogram (EEG) interpretation but lagging in predictive performance or requiring validation for other applications. SUMMARY: Good to excellent predictive models are now available to guide medical and surgical epilepsy decision-making with nomograms offering individualized predictions and user-friendly tools, and machine learning approaches offering the potential of improved performance. Future research is necessary to bridge the two approaches for optimal translation to clinical care.

Predictors of therapeutic response following thalamic neuromodulation for drug-resistant pediatric epilepsy: A systematic review and individual patient data meta-analysis.

We sought to perform a systematic review and individual participant data meta-analysis to identify predictors of treatment response following thalamic neuromodulation in pediatric patients with medically refractory epilepsy. Electronic databases (MEDLINE, Ovid, Embase, and Cochrane) were searched, with no language or data restriction, to identify studies reporting seizure outcomes in pediatric populations following deep brain stimulation (DBS) or responsive neurostimulation (RNS) implantation in thalamic nuclei. Studies featuring individual participant data of patients with primary or secondary generalized drug-resistant epilepsy were included. Response to therapy was defined as >50% reduction in seizure frequency from baseline. Of 417 citations, 21 articles reporting on 88 participants were eligible. Mean age at implantation was 13.07 ± 3.49 years. Fifty (57%) patients underwent DBS, and 38 (43%) RNS. Sixty (68%) patients were implanted in centromedian nucleus and 23 (26%) in anterior thalamic nucleus, and five (6%) had both targets implanted. Seventy-four (84%) patients were implanted bilaterally. The median time to last follow-up was 12 months (interquartile range = 6.75-26.25). Sixty-nine percent of patients achieved response to treatment. Age, target, modality, and laterality had no significant association with response in univariate logistic regression. Until thalamic neuromodulation gains widespread approval for use in pediatric patients, data on efficacy will continue to be limited to small retrospective cohorts and case series. The inherent bias of these studies can be overcome by using individual participant data. Thalamic neuromodulation appears to be a safe and effective treatment for epilepsy. Larger, prolonged prospective, multicenter studies are warranted to further evaluate the efficacy of DBS over RNS in this patient population where resection for curative intent is not a safe option.

Prediction tools and risk stratification in epilepsy surgery.

OBJECTIVE: This study was undertaken to conduct external validation of previously published epilepsy surgery prediction tools using a large independent multicenter dataset and to assess whether these tools can stratify patients for being operated on and for becoming free of disabling seizures (International League Against Epilepsy stage 1 and 2). METHODS: We analyzed a dataset of 1562 patients, not used for tool development. We applied two scales: Epilepsy Surgery Grading Scale (ESGS) and Seizure Freedom Score (SFS); and two versions of Epilepsy Surgery Nomogram (ESN): the original version and the modified version, which included electroencephalographic data. For the ESNs, we used calibration curves and concordance indexes. We stratified the patients into three tiers for assessing the chances of attaining freedom from disabling seizures after surgery: high (ESGS = 1, SFS = 3-4, ESNs > 70%), moderate (ESGS = 2, SFS = 2, ESNs = 40%-70%), and low (ESGS = 2, SFS = 0-1, ESNs < 40%). We compared the three tiers as stratified by these tools, concerning the proportion of patients who were operated on, and for the proportion of patients who became free of disabling seizures. RESULTS: The concordance indexes for the various versions of the nomograms were between .56 and .69. Both scales (ESGS, SFS) and nomograms accurately stratified the patients for becoming free of disabling seizures, with significant differences among the three tiers (p < .05). In addition, ESGS and the modified ESN accurately stratified the patients for having been offered surgery, with significant difference among the three tiers (p < .05). SIGNIFICANCE: ESGS and the modified ESN (at thresholds of 40% and 70%) stratify patients undergoing presurgical evaluation into three tiers, with high, moderate, and low chance for favorable outcome, with significant differences between the groups concerning having surgery and becoming free of disabling seizures. Stratifying patients for epilepsy surgery has the potential to help select the optimal candidates in underprivileged areas and better allocate resources in developed countries.

Fully automatic segmentation of brain lacunas resulting from resective surgery using a 3D deep learning model.

The rapid and constant development of deep learning (DL) strategies is pushing forward the quality of object segmentation in images from diverse fields of interest. In particular, these algorithms can be very helpful in delineating brain abnormalities (lesions, tumors, lacunas, etc), enabling the extraction of information such as volume and location, that can inform doctors or feed predictive models. In this study, we describe ResectVol DL, a fully automatic tool developed to segment resective lacunas in brain images of patients with epilepsy. ResectVol DL relies on the nnU-Net framework that leverages the 3D U-Net deep learning architecture. T1-weighted MRI datasets from 120 patients (57 women; 31.5 ± 15.9 years old at surgery) were used to train (n=78) and test (n=48) our tool. Manual segmentations were carried out by five different raters and were considered as ground truth for performance assessment. We compared ResectVol DL with two other fully automatic methods: ResectVol 1.1.2 and DeepResection, using the Dice similarity coefficient (DSC), Pearson's correlation coefficient, and relative difference to manual segmentation. ResectVol DL presented the highest median DSC (0.92 vs. 0.78 and 0.90), the highest correlation coefficient (0.99 vs. 0.63 and 0.94) and the lowest median relative difference (9 vs. 44 and 12 %). Overall, we demonstrate that ResectVol DL accurately segments brain lacunas, which has the potential to assist in the development of predictive models for postoperative cognitive and seizure outcomes.

Telemedicine as a path to bridging inequities in patients with epilepsy.

OBJECTIVE: Access to epilepsy specialist care is not uniform in the USA, with prominent gaps in rural areas. Understanding the reasons for nonattendance at epilepsy appointments may help identify access hurdles faced by patients. This study was undertaken to better understand clinic absenteeism in epilepsy and how it may be influenced by telemedicine. METHODS: In this retrospective study, social determinants of health were collected for all adult patients scheduled in epilepsy clinic, as either an in-person or telemedicine appointment, at University of Kentucky between July 2021 and December 2022. The primary outcome measure was attendance or absence at the appointment. Subgroup analyses were done to better understand the drivers of attendance at telemedicine visits and evaluate telemedicine utilization by underserved populations. RESULTS: A total of 3025 patient encounters of in-person and telemedicine visits were included. The no-show rate was significantly higher for in-person visits (32%) compared with telemedicine visits (20%, p < .001). A nominal logistic regression model identified seven factors increasing risk of absenteeism, including in-person visits, prior missed appointments, longer lead times to appointment, Medicaid/Medicare as payors, no significant other, lower mean annual income, and minority race. For each $10 000 increase in mean annual income, the odds of missing the appointment decreased by 8% (odds ratio = .92, 95% confidence interval = .89-.96, p < .001). Forty-one percent of underserved population opted for telemedicine visits, and they had a lower no-show rate (22%) as compared with in-person visits (33%, p < .001). Predictors of no-shows to televisits (1382) included Medicare/Medicaid coverage (as opposed to private insurance), no significant others, and a history of missing appointments. SIGNIFICANCE: Telemedicine is effective at improving attendance, overcoming socioeconomic hurdles, and widening access to epilepsy care, particularly among underserved populations. Access to telecare depends on insurance coverage and emphasizes the need to include telemedicine in insurance plans to ensure uniform access to high-quality epilepsy care, irrespective of socioeconomic status.

Molecular subtypes of epilepsy associated with post-surgical seizure recurrence.

Approximately 50% of individuals who undergo resective epilepsy surgery experience seizure recurrence. The heterogenous post-operative outcomes are not fully explained by clinical, imaging and electrophysiological variables. We hypothesized that molecular features may be useful in understanding surgical response, and that individuals with epilepsy can be classified into molecular subtypes that are associated with seizure freedom or recurrence after surgical resection. Pre-operative blood samples, brain tissue and post-operative seizure outcomes were collected from a cohort of 40 individuals with temporal lobe epilepsy, 23 of whom experienced post-operative seizure recurrence. Messenger RNA and microRNA extracted from the blood and tissue samples were sequenced. The messenger RNA and microRNA expression levels from the blood and brain were each subjected to a novel clustering approach combined with multiple logistic regression to separate individuals into genetic clusters that identify novel subtypes associated with post-operative seizure outcomes. We then compared the microRNAs and messenger RNAs from patient blood and brain tissue that were significantly associated with each subtype to identify signatures that are similarly over- or under-represented for an outcome and more likely to represent endophenotypes with common molecular aetiology. These target microRNAs and messenger RNAs were further characterized by pathway analysis to assess their functional role in epilepsy. Using blood-derived microRNA and messenger RNA expression levels, we identified two subtypes of epilepsy that were significantly associated with seizure recurrence (clusters A1 and B4) (adjusted P < 0.20). A total of 551 microRNAs and 2486 messenger RNAs were associated with clusters A1 and B4, respectively (adjusted P < 0.05). Clustering of brain-tissue messenger RNA expression levels revealed an additional subtype (C2) associated with seizure recurrence that had high overlap of dysregulated messenger RNA transcripts with cluster B4. Clusters A1, B4 and C2 also shared significant overlap of subjects, which altogether suggests a coordinated mechanism by which microRNA and messenger RNA transcripts may be related to seizure recurrence. Epileptic subtypes A1, B4 and C2 reveal both known and novel microRNA and messenger RNA targets in seizure recurrence. Furthermore, targets identified in A1 and B4 are quantifiable in pre-operative blood samples and could potentially serve as biomarkers for surgical resection outcomes.

The impact of skull thickness on pediatric stereoencephalography electrode implantation and technical considerations.

OBJECTIVE: One consideration in pediatric stereoencephalography (SEEG) is decreased skull thicknesses compared with adults, which may limit traditional bolt-based anchoring of electrodes. The authors aimed to investigate the safety profile, complication rates, and technical adaptations of placing SEEG electrodes in pediatric patients. METHODS: The authors retrospectively reviewed all patients aged 12 years or younger at the time of SEEG implantation at their institution. Postimplantation CT scans were used to measure skull thickness at the entry point of each SEEG lead. Postimplantation lead accuracy was also assessed. RESULTS: Fifty-three patients were reviewed. The median skull thickness was 4.1 (interquartile range [IQR] 3.15-5.2) mm. There were 5 total complications: 1 retained bolt fragment, 3 asymptomatic subdural hematomas, and 1 asymptomatic intracranial hemorrhage. Median radial error from the lead target was 3.5 (IQR 2.24-5.25) mm. Linear regression analysis revealed that increasing skull thickness decreased the deviation from the intended target, implying an improved accuracy to target at thicker skull entry points; this trended towards improved accuracy, but did not achieve statistical significance (p = 0.54). CONCLUSIONS: This study found a 1.9% hardware complication rate and a 9.4% asymptomatic hemorrhage rate. Suturing electrodes to the scalp may represent a reasonable option if there are concerns of young age or a thin skull. These data indicate that invasive SEEG evaluation is safe among patients 12 years old or younger.

Determinants of epileptogenic zone identification and seizure outcome in children with refractory epilepsy undergoing stereoelectroencephalography.

OBJECTIVE: The objective of this paper was to investigate the factors associated with successful epileptogenic zone (EZ) identification and postsurgical seizure freedom in pediatric patients with drug-resistant epilepsy who underwent first-time stereoelectroencephalography (SEEG). METHODS: The authors conducted a retrospective cohort study of all consecutive patients younger than 18 years of age at the time of recommendation for invasive evaluation with SEEG who were treated from July 2009 to June 2020. The authors excluded patients who had undergone failed prior resective epilepsy surgery or prior intracranial electrode evaluation for seizure localization. For their primary outcome, the authors evaluated the relationship between clinical and radiographic factors and successful identification of a putative EZ. For their secondary outcome, the authors investigated whether these factors had a significant relationship with seizure freedom (according to the Engel classification) at last follow-up. RESULTS: The authors included 101 patients in this study. SEEG was safe, with no major morbidity or mortality experienced. The population was complex, with an MRI lesion present in less than 40% of patients and patients as young as 2.9 years included. A proposed EZ was identified in 88 (87%) patients. Patients with an older onset of epilepsy (OR 1.20/year, p = 0.04) or epilepsy etiology suspected to be due to a developmental lesion (OR 8.38, p = 0.02) were more likely to have proposed EZ identification. Patients with a preimplantation bilateral seizure-onset hypothesis (OR 0.29, p = 0.047) and those who underwent longer periods of monitoring (OR 0.86/day, p = 0.006) were somewhat less likely to have proposed EZ identification. The presence of an MRI lesion was a positive factor on secondary analyses (OR 4.18, p = 0.049; 1-tailed test). Fifty percent of patients who underwent surgical treatment with resection or laser ablation achieved Engel class I outcomes, in contrast to 0% of patients who underwent neuromodulation. Patients with a preimplantation hypothesis in the frontal/parietal lobes had increased odds of seizure freedom compared with patients with a hypothesis in other locations (OR 3.64, p = 0.01). CONCLUSIONS: Pediatric SEEG is safe and often identifies a proposed resectable EZ. These results suggest that SEEG is effective in patients with frontal/parietal preimplantation hypothesis, with or without identified lesions on MRI.

Machine Learning for Precision Epilepsy Surgery.

Brain surgery offers the best chance of seizure-freedom for patients with focal drug-resistant epilepsy, but only 50% achieve sustained seizure-freedom. With the explosion of data collected during routine presurgical evaluations and recent advances in computational science, we now have a tremendous potential to achieve precision epilepsy surgery: a data-driven tailoring of surgical planning. This review highlights the clinical need, the relevant computational science focusing on machine learning, and discusses some specific applications in epilepsy surgery.

Association of Neighborhood Deprivation With Cognitive and Mood Outcomes in Adults With Pharmacoresistant Temporal Lobe Epilepsy.

BACKGROUND AND OBJECTIVES: Temporal lobe epilepsy (TLE) is the most common adult form of epilepsy and is associated with a high risk of cognitive deficits and depressed mood. However, little is known about the role of environmental factors on cognition and mood in TLE. This cross-sectional study examined the relationship between neighborhood deprivation and neuropsychological function in adults with TLE. METHODS: Neuropsychological data were obtained from a clinical registry of patients with TLE and included measures of intelligence, attention, processing speed, language, executive function, visuospatial skills, verbal/visual memory, depression, and anxiety. Home addresses were used to calculate the Area Deprivation Index (ADI) for each individual, which were separated into quintiles (i.e., quintile 1 = least disadvantaged and quintile 5 = most disadvantaged). Kruskal-Wallis tests compared quintile groups on cognitive domain scores and mood and anxiety scores. Multivariable regression models, with and without ADI, were estimated for overall cognitive phenotype and for mood and anxiety scores. RESULTS: A total of 800 patients (median age 38 years; 58% female) met all inclusion criteria. Effects of disadvantage (increasing ADI) were observed across nearly all measured cognitive domains and with significant increases in symptoms of depression and anxiety. Furthermore, patients in more disadvantaged ADI quintiles had increased odds of a worse cognitive phenotype (p = 0.013). Patients who self-identified as members of minoritized groups were overrepresented in the most disadvantaged ADI quintiles and were 2.91 (95% CI 1.87-4.54) times more likely to be in a severe cognitive phenotype than non-Hispanic White individuals (p < 0.001). However, accounting for ADI attenuated this relationship, suggesting neighborhood deprivation may account for some of the relationship between race/ethnicity and cognitive phenotype (ADI-adjusted proportional odds ratio 1.82, 95% CI 1.37-2.42). DISCUSSION: These findings highlight the importance of environmental factors and regional characteristics in neuropsychological studies of epilepsy. There are many potential mechanisms by which neighborhood disadvantage can adversely affect cognition (e.g., fewer educational opportunities, limited access to health care, food insecurity/poor nutrition, and greater medical comorbidities). Future research will seek to investigate these potential mechanisms and determine whether structural and functional alterations in the brain moderate the relationship between ADI and cognition.

Immunometabolic rewiring in long COVID patients with chronic headache.

Almost 20% of patients with COVID-19 experience long-term effects, known as post-COVID condition or long COVID. Among many lingering neurologic symptoms, chronic headache is the most common. Despite this health concern, the etiology of long COVID headache is still not well characterized. Here, we present a longitudinal multi-omics analysis of blood leukocyte transcriptomics, plasma proteomics and metabolomics of long COVID patients with chronic headache. Long COVID patients experienced a state of hyper-inflammation prior to chronic headache onset and maintained persistent inflammatory activation throughout the progression of chronic headache. Metabolomic analysis also revealed augmented arginine and lipid metabolisms, skewing towards a nitric oxide-based pro-inflammation. Furthermore, metabolisms of neurotransmitters including serotonin, dopamine, glutamate, and GABA were markedly dysregulated during the progression of long COVID headache. Overall, these findings illustrate the immuno-metabolomics landscape of long COVID patients with chronic headache, which may provide insights to potential therapeutic interventions.

Predictive models for starting antiseizure medication withdrawal following epilepsy surgery in adults.

More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications. We aimed to identify predictors of seizure recurrence after starting postoperative antiseizure medication withdrawal and develop and validate predictive models. We performed an international multicentre observational cohort study in nine tertiary epilepsy referral centres. We included 850 adults who started antiseizure medication withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting antiseizure medication withdrawal. We developed a model predicting recurrent seizures, other than focal non-motor aware seizures, using Cox proportional hazards regression in a derivation cohort (n = 231). Independent predictors of seizure recurrence, other than focal non-motor aware seizures, following the start of antiseizure medication withdrawal were focal non-motor aware seizures after surgery and before withdrawal [adjusted hazard ratio (aHR) 5.5, 95% confidence interval (CI) 2.7-11.1], history of focal to bilateral tonic-clonic seizures before surgery (aHR 1.6, 95% CI 0.9-2.8), time from surgery to the start of antiseizure medication withdrawal (aHR 0.9, 95% CI 0.8-0.9) and number of antiseizure medications at time of surgery (aHR 1.2, 95% CI 0.9-1.6). Model discrimination showed a concordance statistic of 0.67 (95% CI 0.63-0.71) in the external validation cohorts (n = 500). A secondary model predicting recurrence of any seizures (including focal non-motor aware seizures) was developed and validated in a subgroup that did not have focal non-motor aware seizures before withdrawal (n = 639), showing a concordance statistic of 0.68 (95% CI 0.64-0.72). Calibration plots indicated high agreement of predicted and observed outcomes for both models. We show that simple algorithms, available as graphical nomograms and online tools (predictepilepsy.github.io), can provide probabilities of seizure outcomes after starting postoperative antiseizure medication withdrawal. These multicentre-validated models may assist clinicians when discussing antiseizure medication withdrawal after surgery with their patients.

Beyond seizure freedom: Dissecting long-term seizure control after surgical resection for drug-resistant epilepsy.

OBJECTIVE: This study was undertaken to better understand the long-term palliative and disease-modifying effects of surgical resection beyond seizure freedom, including frequency reduction and both late recurrence and remission, in patients with drug-resistant epilepsy. METHODS: This retrospective database-driven cohort study included all patients with >9 years of follow-up at a single high-volume epilepsy center. We included patients who underwent lobectomy, multilobar resection, or lesionectomies for drug-resistant epilepsy; we excluded patients who underwent hemispherectomies. Our main outcomes were (1) reduction in frequency of disabling seizures (at 6 months, each year up to 9 years postoperatively, and at last follow-up), (2) achievement of seizure remission (>6 months, >1 year, and longest duration), and (3) seizure freedom at last follow-up. RESULTS: We included 251 patients; 234 (93.2%) achieved 6 months and 232 (92.4%) experienced 1 year of seizure freedom. Of these, the average period of seizure freedom was 10.3 years. A total of 182 (72.5%) patients were seizure-free at last follow-up (defined as >1 year without seizures), with a median 11.9 years since remission. For patients not completely seizure-free, the mean seizure frequency reduction at each time point was 76.2%, and ranged from 66.6% to 85.0%. Patients decreased their number of antiseizure medications on average by .58, and 53 (21.2%) patients were on no antiseizure medication at last follow-up. Nearly half (47.1%) of those seizure-free at last follow-up were not seizure-free immediately postoperatively. SIGNIFICANCE: Patients who continue to have seizures after resection often have considerable reductions in seizure frequency, and many are able to achieve seizure freedom in a delayed manner.

Alpha to Omicron: Disease Severity and Clinical Outcomes of Major SARS-CoV-2 Variants.

BACKGROUND: Four severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants predominated in the United States since 2021. Understanding disease severity related to different SARS-CoV-2 variants remains limited. METHOD: Viral genome analysis was performed on SARS-CoV-2 clinical isolates circulating March 2021 through March 2022 in Cleveland, Ohio. Major variants were correlated with disease severity and patient outcomes. RESULTS: In total 2779 patients identified with either Alpha (n 1153), Gamma (n 122), Delta (n 808), or Omicron variants (n 696) were selected for analysis. No difference in frequency of hospitalization, intensive care unit (ICU) admission, and death were found among Alpha, Gamma, and Delta variants. However, patients with Omicron infection were significantly less likely to be admitted to the hospital, require oxygen, or admission to the ICU (2 12.8, P .001; 2 21.6, P .002; 2 9.6, P .01, respectively). In patients whose vaccination status was known, a substantial number had breakthrough infections with Delta or Omicron variants (218/808 [26.9] and 513/696 [73.7], respectively). In breakthrough infections, hospitalization rate was similar regardless of variant by multivariate analysis. No difference in disease severity was identified between Omicron subvariants BA.1 and BA.2. CONCLUSIONS: Disease severity associated with Alpha, Gamma, and Delta variants is comparable while Omicron infections are significantly less severe. Breakthrough disease is significantly more common in patients with Omicron infection.

A comprehensive SARS-CoV-2-human protein-protein interactome reveals COVID-19 pathobiology and potential host therapeutic targets.

Studying viral-host protein-protein interactions can facilitate the discovery of therapies for viral infection. We use high-throughput yeast two-hybrid experiments and mass spectrometry to generate a comprehensive SARS-CoV-2-human protein-protein interactome network consisting of 739 high-confidence binary and co-complex interactions, validating 218 known SARS-CoV-2 host factors and revealing 361 novel ones. Our results show the highest overlap of interaction partners between published datasets and of genes differentially expressed in samples from COVID-19 patients. We identify an interaction between the viral protein ORF3a and the human transcription factor ZNF579, illustrating a direct viral impact on host transcription. We perform network-based screens of >2,900 FDA-approved or investigational drugs and identify 23 with significant network proximity to SARS-CoV-2 host factors. One of these drugs, carvedilol, shows clinical benefits for COVID-19 patients in an electronic health records analysis and antiviral properties in a human lung cell line infected with SARS-CoV-2. Our study demonstrates the value of network systems biology to understand human-virus interactions and provides hits for further research on COVID-19 therapeutics.

Epilepsy Surgery Outcome of Traumatic Intradiploic Meningoencephalocele: A Case Report and Literature Review.

We highlight an under-recognized epileptic pathology in a 56-year-old left-handed female with progressive right facial numbness and weekly focal seizures characterized by episodic aphasia. She was found to have a left frontoparietal intradiploic meningoencephalocele (IDME). Her only epilepsy risk factor was minor head trauma 10 years prior to presentation. She underwent craniotomy for encephalocele resection and mesh cranioplasty without residual neurological deficits and excellent seizure outcome: at 3-year follow-up, she was still seizure-free since surgery, except for an isolated breakthrough seizure at 7 postoperative months when she discontinued her preoperative regimen of Lacosamide monotherapy. Traumatic IDME is a rare condition and rarely presents with seizures. Symptoms may arise up to decades following minor head trauma and are progressive in nature. The likely definitive treatment is cranioplasty and dural repair with or without resecting the protruding parenchyma.

Genetic and molecular features of seizure-freedom following surgical resections for focal epilepsy: A pilot study.

Objective: Seizure outcomes after brain surgery for drug-resistant epilepsy (DRE) are very heterogeneous and difficult to predict with models utilizing the current clinical, imaging, and electrophysiological variables. In this pilot study, we investigated whether genetic and molecular biomarkers (e.g., genomic, transcriptomic) can provide additional insight into differential response to surgery. Methods: Post-operative seizure-outcomes were collected at last follow-up (>6 months) for 201 adult patients with DRE who underwent surgery between 2004 and 2020. Resected tissue was sent for miRNA sequencing (n = 132) and mRNA sequencing (n = 135). Following the selection of 10 genes (SCN1A, NBEA, PTEN, GABRA1, LGL1, DEPDC5, IL1A, ABCB1, C3, CALHM1), we investigated SNPs in those 10 genes from previously acquired exome sequencing data (n = 106). Logistic regression was performed to test for associations between individual features (mRNAs, miRNAs, and SNPs) and post-operative seizure-outcome with an exploratory FDR P < 0.25 as the threshold for significance. Post-operative time-to-seizure analyses were performed for each SNP using a Cox proportional hazards model. Results: The majority of patients (83%) had temporal lobe epilepsy. Mean age at surgery was 38.3 years, and 56% were female. Three SNPs (rs10276036, rs11975994, rs1128503) in multi-drug resistance gene, ABCB1, were associated with post-operative seizure outcomes. Patients with alternate alleles in ABCB1 were more likely to be seizure-free at last follow-up (52-56% reduction in seizure recurrence; FDR P = 0.24). All three SNPs were in linkage disequilibrium and highly correlated with each other. Median post-operative time-to-seizure was 63 months for patients with 2 alternate alleles, 24-33 months with 1 alternate allele, and 10-11 months with 0 alternate alleles. These SNPs improved outcome prediction beyond MRI and sex alone. No independent miRNAs or mRNAs were significantly associated with seizure-outcome (P > 0.05). However, pathway analysis identified "cancer drug resistance by drug efflux" (mir-154 and mir-379) as enriched (P = 0.02), supporting the role of drug response genes in post-operative seizure recurrence. Significance: ABCB1 may have a role in epileptogenesis and surgery outcomes independent of its drug efflux activity necessitating further investigation. SNPs in ABCB1 may serve as independent predictors of post-operative outcome.

Does Stereoelectroencephalography Add Value in Patients with Lesional Epilepsy?

OBJECTIVE: Stereoelectroencephalography (SEEG) has gained popularity as an invasive monitoring modality for epileptogenic zone (EZ) localization. The need and indications for SEEG in patients with evident brain lesions or associated abnormalities on imaging is debated. We report our experience with SEEG as a presurgical evaluation tool for patients with lesional epilepsy. METHODS: A retrospective cohort study was performed of 131 patients with lesional or magnetic resonance imaging abnormality-associated medically refractory focal epilepsy who underwent resections from 2010 to 2017. Seventy-one patients had SEEG followed by resection, and 60 had no invasive recordings. Volumetric analysis of resection cavities from 3T magnetic resonance imaging was performed. RESULTS: Mean lesion and resection volumes for SEEG and non-SEEG were 16.2 (standard deviation [SD] = 29) versus 23.7 cm3 (SD = 38.4) and 28.1 (SD = 23.2) versus 43.6 cm3 (SD = 43.5), respectively (P = 0.009). Comparing patients with seizure recurrence and patients who remained seizure free, significantly associated variables with seizure recurrence included mean number of failed antiseizure medications (6.86 [SD = 0.32] vs. 5.75 [SD = 0.32]; P = 0.01) and in SEEG patients the mean number of electrodes implanted (8.1 [SD = 0.8] vs. 5.0 [SD = 0.8]; P = 0.005). After multivariate analysis, only failed numbers of medication remained significantly associated with seizure recurrence. CONCLUSIONS: Seizure outcomes did not correlate with final resection volume after SEEG evaluation. SEEG evaluation presurgically can be used to maintain the efficacy of resection and decrease the volume and subsequent risk of extensive tissue removal. We believe that this technology allows resective surgery to proceed in a subpopulation of patients with lesional epilepsy who may otherwise not have been considered surgical candidates.

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.

What is a clinical practice guideline? A roadmap to their development. Special report from the Guidelines Task Force of the International League Against Epilepsy.

Clinical practice guidelines (CPGs) are statements that provide evidence-based recommendations aimed at optimizing patient care. However, many other documents are often published as "guidelines" when they are not; these documents, although also important in clinical practice, are usually not systematically produced following rigorous processes linking the evidence to the recommendations. Specifically, the International League Against Epilepsy (ILAE) guideline development toolkit aims to ensure that high-quality CPGs are developed to fill knowledge gaps and optimize the management of epilepsy. In addition to adhering to key methodological processes, guideline developers need to consider that effective CPGs should lead to improvements in clinical processes of care and health care outcomes. This requires monitoring the effectiveness of epilepsy-related CPGs and interventions to remove the barriers to epilepsy CPG implementation. This article provides an overview of what distinguishes quality CPGs from other documents and discusses their benefits and limitations. We summarize the recently revised ILAE CPG development process and elaborate on the barriers and facilitators to guideline dissemination, implementation, and adaptation.