Joint use of population pharmacokinetics and machine learning for optimizing antiepileptic treatment in pediatric population.

Purpose: Unpredictable drug efficacy and safety of combined antiepileptic therapy is a major challenge during pharmacotherapy decisions in everyday clinical practice. The aim of this study was to describe the pharmacokinetics of valproic acid (VA), lamotrigine (LTG), and levetiracetam (LEV) in a pediatric population using nonlinear mixed-effect modeling, while machine learning (ML) algorithms were applied to identify any relationships among the plasma levels of the three medications and patients' characteristics, as well as to develop a predictive model for epileptic seizures.

Methods: The study included 71 pediatric patients of both genders, aged 2-18 years, on combined antiepileptic therapy.

The importance of assessing general motor activity in premature infants for predicting neurological outcomes.

Introduction: Conventional methods of neurological assessment of infants can detect nervous system damage, but also have a weakness, i.e., the inability to make predictions for neurological deficits.

Astasia-Abasia and Ganser Syndrome in a Preadolescent Girl: A Case Report.

Introduction: Astasia is the inability to maintain an upright body position without assistance in the absence of motor weakness or sensory loss. Abasia is described as the inability to walk or as uncoordinated walking, while preserving mobility of the lower limbs. Ganser syndrome is described as a dissociative disorder characterized by approximate answers, somatic conversion symptoms, clouding of consciousness, as well as visual and auditory pseudohallucinations.