NORSE secondary to anti-GAD65 antibody-positive encephalitis treated with novel adjunctive rapid titration VNS protocol.

New Onset Refractory Status Epilepticus (NORSE) is a rare and severe condition characterized by refractory seizures in individuals without a prior history of epilepsy. This case report describes a 37-year-old woman diagnosed with anti-glutamic acid decarboxylase 65 (anti-GAD65) antibody-positive encephalitis-related NORSE. Her seizures were refractory to multiple interventions, including anti-seizure medications, anesthetics, immunotherapies, a ketogenic diet, and electroconvulsive therapy.

Drug Safety During Breastfeeding: A Comparative Analysis of FDA Adverse Event Reports and LactMed.

Background/objectives: While breastfeeding is highly recommended, breastfed infants may be exposed to drugs by milk due to maternal pharmacotherapy, resulting in a risk of adverse drug events (ADE) or reactions (ADRs). The U.S.

Optimizing Individualized Antimicrobial Dosing in Pediatric Patients: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Background: Therapeutic drug monitoring (TDM) and target concentration intervention (TCI) represent significant advancements in individualized medicine, aiming to tailor dosages based on patient-specific characteristics. These approaches account for intra- and inter-individual physiological and clinical variability, with the goal of improving target attainment and clinical remission while reducing treatment failure and adverse effects.

Objectives: The objective is to assess and enhance the current body of randomized controlled trials (RCTs) that have investigated alternative personalized dosing strategies, such as TDM and TCI, in terms of their efficacy and safety for individualized antimicrobial dosing in pediatric populations.

Introducing a novel dataset for facial emotion recognition and demonstrating significant enhancements in deep learning performance through pre-processing techniques.

Facial expression recognition (FER) plays a pivotal role in various applications, ranging from human-computer interaction to psychoanalysis. To improve the accuracy of facial emotion recognition (FER) models, this study focuses on enhancing and augmenting FER datasets. It comprehensively analyzes the Facial Emotion Recognition dataset (FER13) to identify defects and correct misclassifications.