AED withdrawal at home prior to LTM is an efficient and convenient method to increase the diagnostic yield of LTM and appears relatively safe.
Background and ObjectivesTo describe neurologist practice patterns, challenges, and decision support needs pertaining to withdrawal of antiseizure medications (ASMs) in patients with well-controlled epilepsy.MethodsWe sent an electronic survey to (1) US and (2) European physician members of the American Academy of Neurology and (3) members of EpiCARE, a European Reference Network for rare and complex epilepsies. Analyses included frequencies and percentages, and we showed distributions through histograms and violin plots.ResultsWe sent the survey to 4,923 individuals; 463 consented, 411 passed eligibility questions, and 287 responded to at least 1 of these questions. Most respondents indicated that they might ever consider ASM withdrawal, with respondents treating mostly children being more likely ever to consider withdrawal (e.g., medical monotherapy: children 96% vs adults 81%;p< 0.05). The most important factors when making decisions included seizure probability (83%), consequences of seizures (73%), and driving (74%). The top challenges when making decisions included unclear seizure probability (81%), inadequate guidelines (50%), and difficulty communicating probabilities (45%). Respondents would consider withdrawal after a median of 2-year seizure freedom, but also responded that they would begin withdrawal on average only when the postwithdrawal seizure relapse risk in the coming 2 years was less than 15%–30%. Wide variation existed in the use of words or numbers in respondents' counsel methods, for example, percentages vs frequencies or probability of seizure freedom vs seizure. The most highly rated point-of-care methods to inform providers of calculated risk were Kaplan-Meier curves and showing percentages only, rather than pictographs or text recommendations alone.DiscussionMost surveyed neurologists would consider withdrawing ASMs in seizure-free individuals. Seizure probability was the largest factor driving decisions, yet estimating seizure probabilities was the greatest challenge. Respondents on average indicated that they may withdraw ASM after a minimum seizure-free duration of 2 years, yet also on average were willing to withdraw when seizure risk decreased below 15%–30%, which is lower than most patients' postwithdrawal risk at 2-year seizure freedom and lower than the equivalent even of a first seizure of life. These findings will inform future efforts at developing decision support tools aimed at optimizing ASM withdrawal decisions.
Objective: Choosing candidates for antiseizure medication (ASM) withdrawal in well-controlled epilepsy is challenging. We evaluated (a) the correlation between neurologists' seizure risk estimation ("clinician predictions") vs calculated predictions, (b) how viewing calculated predictions influenced recommendations, and (c) barriers to using risk calculation. Methods:We asked US and European neurologists to predict 2-year seizure risk after ASM withdrawal for hypothetical vignettes. We compared ASM withdrawal recommendations before vs after viewing calculated predictions, using generalized linear models.
Background: Choosing candidates for antiseizure medication (ASM) withdrawal in well-controlled epilepsy is challenging. We evaluated 1) the correlation between neurologists' seizure risk estimation (clinician predictions) versus calculated predictions, 2) how viewing calculated predictions influenced recommendations, and 3) barriers to using risk calculation. Methods: We asked neurologists to predict two-year seizure risk after ASM withdrawal for hypothetical vignettes. We compared withdrawal recommendations ASMs before versus after viewing calculated predictions using generalized linear models. Results: Three-hundred forty-six responded. There was moderate correlation between clinician and calculated predictions (Spearman coefficient 0.42). Clinician predictions varied widely, e.g., predictions ranged 5%-100% for a two-year seizure-free adult without epileptiform abnormalities. Mean clinician predictions exceeded calculated predictions for vignettes with epileptiform abnormalities (e.g., childhood absence epilepsy: clinician 65%, 95% confidence interval [CI] 57%-74%; calculated 46%) and surgical vignettes (e.g., focal cortical dysplasia six-months seizure-free mean clinician 56%, 95% CI 52%-60%; calculated 28%). Clinicians overestimated the influence of epileptiform EEG findings on withdrawal risk (26%, 95% CI 24%-28%) compared with calculators (14%, 95% 13%-14%). Viewing calculated predictions slightly reduced willingness to withdraw (-0.8/10 change, 95% CI -1.0 to -0.7), particularly without epileptiform abnormalities. The greatest barrier to calculator use was doubting its accuracy (44%). Conclusions: Clinicians overestimated the influence of abnormal EEGs particularly for low-risk patients and overestimated risk and the influence of seizure-free duration for surgical patients, compared with calculators. These data may question widespread ordering of EEGs or time-based seizure-free thresholds for surgical patients. Viewing calculated predictions reduced willingness to withdraw particularly without epileptiform abnormalities.
Presurgical long-term video-EEG monitoring (LT-VEEG) is an important part of the presurgical evaluation in patients with focal epilepsy. Multiple seizures need to be recorded, often in limited time and with the need to taper anti seizure medication (ASM). The aim of this study was to systematically study the yield -in terms of success -and risks of presurgical LT-VEEG, and to identify all previously reported contributing variables. MethodsA systematic review of the databases of PubMed Medline, Embase, Cochrane Central, and the Cochrane Database of Systematic Reviews were searched following the Preferred Reporting Items for Systematic Reviews (PRISMA) guideline. Publications about presurgical LT-VEEG reporting on variables contributing to yield and risk were included. Study characteristics of all included studies were extracted following a standardized template. Within these articles, studies presenting multivariable analyses of factors contributing to the risk of adverse events or the succes of LT-VEEGwere identified. Results 3We found 36 articles reporting on LT-VEEG, including 4.703 presurgical patients, both children and adults. Presurgical LT-VEEG monitoring has an average yield of 85%. Adverse events occurred with an averaged total event rate of 17%, but the type of included events was variable among studies. Factors reported to independently contribute to successful LT-VEEG were: baseline seizure frequency, shorter interval since most recent seizure, extra-temporal lobe epilepsy, ASM reduction not needed. Factors independently contributing to the occurrence of adverse event were: ASM tapering, history of status epilepticus, history of focal to bilateral tonic clonic seizures, psychiatric comorbidity, and ASM taper rate. ConclusionThis study reveals that data on factors contributing to yield and risk of adverse events is significant variable and often with inadequate statistics. Future research is warrented to develop guidelines for ASM withdrawal during presurgical video-EEG monitoring, taking predefined factors for success and risks of adverse events into account.
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