Cenobamate has demonstrated efficacy in patients with treatment-resistant epilepsy, including patients who continued to have seizures after epilepsy surgery. This article provides recommendations for cenobamate use in patients referred for epilepsy surgery evaluation. A panel of six senior epileptologists from the United States and Europe with experience in presurgical evaluation of patients with epilepsy and in the use of antiseizure medications (ASMs) was convened to provide consensus recommendations for the use of cenobamate in patients referred for epilepsy surgery evaluation. Many patients referred for surgical evaluation may benefit from ASM optimization; both ASM and surgical treatment should be individualized. Based on previous clinical studies and the authors' clinical experience with cenobamate, a substantial proportion of patients with treatment-resistant epilepsy can become seizure-free with cenobamate. We recommend a cenobamate trial and ASM optimization in parallel with presurgical evaluations. Cenobamate can be started before phase two monitoring, especially in patients who are found to be suboptimal surgery candidates. As neurostimulation therapies are generally palliative, we recommend trying cenobamate before vagus nerve stimulation (VNS), deep brain stimulation, or responsive neurostimulation (RNS). In surgically remediable cases (mesial temporal sclerosis, benign discrete lesion in non-eloquent cortex, cavernous angioma, etc.), cenobamate use should not delay imminent surgery; however, a patient may decide to defer or even cancel surgery should they achieve sustained seizure freedom with cenobamate. This decision should be made on an individual, case-by-case basis based on seizure etiology, patient preferences, potential surgical risks (mortality and morbidity), and likely surgical outcome. The addition of cenobamate after unsuccessful surgery or palliative neuromodulation may also be associated with better outcomes.
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http://dx.doi.org/10.1007/s40120-024-00651-4 | DOI Listing |
Acta Cardiol Sin
January 2025
School of Medicine, National Yang Ming Chiao Tung University.
J Gen Fam Med
January 2025
Neurozentrum Thalwil Zürich Switzerland.
Background: Patients with somatoform pain experience physical pain that cannot be attributed to any underlying medical or physiological cause, and it is often thought to be related to psychological factors. Health professionals encounter difficulties identifying this specific type of chronic pain, leading to suboptimal treatment strategies. Therefore, we aimed to describe the characteristics of patients with somatoform pain, to support the identification of affected patients.
View Article and Find Full Text PDFJ Chiropr Med
December 2024
Department of Chiropractic, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, New South Wales, Australia.
Objective: The aim of this study was to describe the demographic and clinical characteristics of patients with scoliosis from Australian primary care practices.
Methods: A retrospective review of 190 patient records from August 2017 to April 2020 from a private Australian clinical advisory service database was performed. Deidentified demographic and clinical data were collated and analyzed, along with information regarding the referring practitioners and any accompanying clinical or paraclinical information.
Clin Case Rep
January 2025
Department of Radiology and Radiotherapy, School of Medicine, College of Health Sciences Makerere University Kampala Uganda.
Double outlet right ventricle (DORV) is a rare congenital heart defect where both the aorta and pulmonary artery originate from the right ventricle, often accompanied by additional cardiac anomalies to mitigate circulatory imbalance, though such compensations usually fail. We report a 15-month-old infant with recurrent respiratory infections and poor weight gain, referred for computed tomography angiography. Physical examination showed a small, non-syndromic infant with pallor, tachypnea, irritability, and finger clubbing.
View Article and Find Full Text PDFJAMIA Open
February 2025
Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN 46202, United States.
Objective: Measurement of health-related social needs (HRSNs) is complex. We sought to develop and validate computable phenotypes (CPs) using structured electronic health record (EHR) data for food insecurity, housing instability, financial insecurity, transportation barriers, and a composite-type measure of these, using human-defined rule-based and machine learning (ML) classifier approaches.
Materials And Methods: We collected HRSN surveys as the reference standard and obtained EHR data from 1550 patients in 3 health systems from 2 states.
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