Clinical and neuropsychological characteristics of children with epilepsy and attention-deficit/hyperactivity disorder

Explainable Artificial Intelligence for Predicting Attention Deficit Hyperactivity Disorder in Children and Adults

Attention Deficit Hyperactivity Disorder (ADHD) is a disorder that starts in childhood, sometimes persisting into adulthood. It puts a strain on their social, professional, family, and environmental lives, which can exacerbate disorders such as anxiety, depression, and bipolar disorder. Background/Objectives: This paper aims to predict ADHD in children and adults and explain the main factors impacting this disorder. Methods: We start by introducing the main symptoms and challenges ADHD poses for children and adults such as epilepsy and depression. Then, we present the results of existing research on three ADHD comorbidities: anxiety, depression, and bipolar disorder, and their possible continuity in adulthood with therapeutic implications. After that, we explain the impact of this disorder and its relationship with these comorbidities on the affected patient's health and environment and list proposed treatments. We propose a methodology for predicting this impairment in children and adults by using Machine Learning algorithms (ML), Explainable Artificial Intelligence (XAI), and two datasets, the National Survey for Children's Health (NSCH) (2022) for the children and the ADHD|Mental Health for the adults. Results: Logistic Regression (LR) was the most suitable algorithm for children, with an accuracy of 99%. As for adults, the XGBoost (XGB) was the most performant ML method, with an accuracy of 100%. Conclusions: Lack of sleep and excessive smiling/laughing are among the factors having an impact on ADHD for children, whereas anxiety and depression affect ADHD adults.

The diagnosis of ADHD in children and adolescents with epilepsy: a scoping review

Attention-deficit hyperactivity disorder (ADHD) is often diagnosed in children and adolescents with epilepsy, but clear clinical guidelines on how to make this diagnosis are still lacking. Without these guidelines, there is no consensus between specialists on how to proceed when assessing children with epilepsy for ADHD, which can negatively impact the quality of care being offered to this population. As a first step toward gaining more specific clinical guidelines, this scoping review was aimed at documenting the tools and procedures used to diagnose ADHD in children and adolescents with epilepsy over time and at determining whether the diagnoses were made in accordance with clinical guidelines and recommendations. The literature search was conducted using PsycINFO, PubMed, and CINAHL. Studies were included if conducted with children and adolescents aged between 4 and 18 years with epilepsy being evaluated for ADHD. Studies were clustered according to their publication date and the reported diagnostic procedures were identified. Forty-nine out of 3854 records were included. Results highlight discrepancies between how ADHD was diagnosed in reviewed studies and clinical guidelines or recommendations. Indeed, most studies did not use a multi-method and multi-informant approach when diagnosing ADHD in children with epilepsy, with no improvement over time. Future studies aimed at diagnosing ADHD in children and adolescents should ensure that they are following clinical guidelines and recommendations, in addition to adapting their diagnostic procedures to the presence of any neurological comorbidities, such as epilepsy.

Advances in the etiology and neuroimaging of children with attention deficit hyperactivity disorder

Attention deficit hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in children, characterized by age-inappropriate inattention, hyperactivity, and impulsivity, which can cause extensive damage to children's academic, occupational, and social skills. This review will present current advancements in the field of attention deficit hyperactivity disorder, including genetics, environmental factors, epigenetics, and neuroimaging features. Simultaneously, we will discuss the highlights of promising directions for further study.

Advances in understanding the pathogenesis of epilepsy: Unraveling the molecular mechanisms: A cross-sectional study

Introduction

Epilepsy is characterized by having two or more unprovoked seizures. Understanding the pathogenesis of epilepsy, requires deep investigation into the molecular mechanisms. This helps develop diagnostic techniques, treatments, and pharmacotherapy. It also enhances precision medicine and individualized treatment processes. This article reviews all the molecular mechanisms predisposing to epileptogenesis, presents the current diagnostic techniques and drug therapy, and suggests future perspectives in treating Epilepsy in a more comprehensive and holistic approach.

Methodology

Four authors searched keywords concerning epilepsy at a molecular level, Epilepsy diagnostic techniques and technologies, and antiepileptic drug therapy and precision medicine. Separate search strategies were conducted for each concern and retrieved articles were reviewed for relevant results.

Results

The traditional diagnostic techniques for Epilepsy and its pathogenesis are insufficient in highlighting dynamic brain changes. For this, emerging technologies including genetic sequencing and profiling, and functional neuroimaging techniques are prevailing. Concerning treatment, the current approach focuses on managing symptoms and stopping seizures using antiseizure medications. However, their usage is limited by developing resistance to such drugs. Some therapies show promise, although most antiseizure drugs do not prevent epilepsy.

Discussion

Understanding epileptogenesis at a molecular and genetic level aids in developing new antiepileptic pharmacotherapy. The aim is to develop therapies that could prevent seizures or modify disease course, decreasing the severity and avoiding drug resistance. Gene therapy and precision medicine are promising but applications are limited due to the heterogeneity in studying the Epileptic brain, dynamically. The dynamic investigation of the epileptic brain with its comorbidities works hand-in-hand with precision medicine, in developing personalized treatment plans.