IMPORTANCE Autoimmune epilepsy is an underrecognized condition, and its true incidence is unknown. Identifying patients with an underlying autoimmune origin is critical because these patients' condition may remain refractory to conventional antiseizure medications but may respond to immunotherapy.OBJECTIVE To determine the prevalence of neurological autoantibodies (Abs) among adult patients with epilepsy of unknown etiology. DESIGN, SETTING, AND PARTICIPANTSConsecutive patients presenting to neurology services with new-onset epilepsy or established epilepsy of unknown etiology were identified. Serum samples were tested for autoimmune encephalitis Abs as well as thyroperoxidase (TPO) and glutamic acid decarboxylase 65 (GAD65) Abs. An antibody prevalence in epilepsy (APE) score based on clinical characteristics was assigned prospectively. Data were collected from June 1, 2015, to June 1, 2016. MAIN OUTCOMES AND MEASURESPresence of neurological Abs. A score based on clinical characteristics was assigned to estimate the probability of seropositivity prior to antibody test results. Good seizure outcome was estimated on the basis of significant reduction of seizure frequency at the first follow-up or seizure freedom. RESULTSOf the 127 patients (68 males and 59 females) enrolled in the study, 15 were subsequently excluded after identification of an alternative diagnosis. Serum Abs suggesting a potential autoimmune etiology were detected in 39 (34.8%) cases. More than 1 Ab was detected in 7 patients (6.3%): 3 (2.7%) had TPO-Ab and voltage-gated potassium channel complex (VGKCc) Ab, 2 (1.

As the potential of smartphone apps and sensors for healthcare and clinical research continues to expand, there is a concomitant need for open, accessible, and scalable digital tools. While many current app platforms offer useful solutions for either clinicians or patients, fewer seek to serve both and support the therapeutic relationship between them. Thus, we aimed to create a novel smartphone platform at the intersection of patient demands for trust, control, and community and clinician demands for transparent, data driven, and translational tools. The resulting LAMP platform has evolved through numerous iterations and with much feedback from patients, designers, sociologists, advocates, clinicians, researchers, app developers, and philanthropists. As an open and free tool, the LAMP platform continues to evolve as reflected in its current diverse use cases across research and clinical care in psychiatry, neurology, anesthesia, and psychology. In this paper, we explore the motivation, features, current progress, and next steps to pair the platform for use in a new digital psychiatry clinic, to advance digital interventions for youth mental health, and to bridge gaps in available mental health care for underserved patient groups. The code for the LAMP platform is freely shared with this paper to encourage others to adapt and improve on our team's efforts.