Fig 2 - available via license: Creative Commons Attribution 4.0 International
Content may be subject to copyright.
Source publication
There have been increasing efforts to develop prediction models supporting personalised detection, prediction, or treatment of ADHD. We overviewed the current status of prediction science in ADHD by: (1) systematically reviewing and appraising available prediction models; (2) quantitatively assessing factors impacting the performance of published m...
Context in source publication
Context 1
... Among the eligible studies, 88.0% reported on diagnostic prediction models, 5.0% on prognostic models (with outcomes such as symptom change or development of substance use disorders), and 7.0% on treatmentresponse models. The retained studies most frequently used clinical (35.0%), neuroimaging (31.0%) and cognitive (27.0%), predictors (Fig. 2). The total sample size was 323,554 individuals, ranging from 10 to 238,696 individuals per study. The average age was 15.7 years. The source of data encompassed case-control studies (73 studies, 73.0%), cohort studies (23 studies, 23.0%), and clinical trials (4 studies, 4.0%). AUC was the most commonly reported measure of model ...
Similar publications
Background
Neonatal jaundice is a common condition that can lead to brain damage and disabilities when severe cases go undetected. Low- and middle-income countries often lack accurate methods for detecting neonatal jaundice and rely on visual assessment, resulting in a higher incidence of adverse consequences. Picterus Jaundice Pro (Picterus JP), a...
Objective: This comprehensive scope review critically examines the landscape of empirical research on strategy implementation (SI) over the past decade, from 2014 to 2024. Despite its critical role in determining organizational success or failure, strategy implementation remains an underexplored area within the vast domain of strategic management l...
Citations
... This was because the study aimed to understand the association between single-dose and longer-term response in adults with ADHD, and neurotypicals were only included to facilitate the interpretation of treatment-related effects on rsfc. The resulting sample size, as well as missing data, precluded us from using more complex machine-learning approaches, e.g. using support vector machines, to identify characteristics associated with treatment response 83 . However, given the challenges inherent to collecting repeated-measures neuroimaging and behavioural data within a pharmacological study, especially in neurodivergent participants, our sample size was appropriate to provide initial proof-of-concept that the brain response to single-dose MPH relates to clinical response post dose-optimization in ADHD; while providing insights into the underlying biological mechanisms. ...
Stimulants, such as methylphenidate (MPH), are beneficial for attention-deficit/hyperactivity disorder (ADHD), but individual response varies. A deeper understanding of the mechanisms underpinning response is needed. Previous studies suggest that a single MPH dose modulates resting-state functional connectivity (rs-fc). We investigated whether single-dose induced rs-fc changes were associated with post-dose optimization clinical response. Fifty-six adults with ADHD underwent rs-functional magnetic resonance imaging (rs-fMRI) under placebo and a single MPH dose, before starting MPH treatment. Clinical response was measured at two months. We tested if a single MPH dose (vs. placebo) shifted rs-fc; how these shifts were associated with treatment response (categorical approach); and whether these associations were driven by improvement on either ADHD symptom domain. A single MPH dose (vs. placebo) increased rs-fc in three subcortical-cortical and cerebellar-cortical clusters. Enhanced rs-fc between the cerebellar vermis (lobule 6) and the left precentral gyrus was associated with a greater probability of responding to treatment (χ²(7) = 22.740, p = .002) and with an improvement on both inattentive and hyperactive/impulsive symptoms (both p ≤ .001). We provide proof-of-concept that the brain functional response to a single MPH dose, administered before starting routine treatment, is indicative of two-month clinical response in adult ADHD. This may encourage future replication using clinically applicable measures.
... parent training) (Faraone et al., 2021;Groom & Cortese, 2022). Although clinical trials have consistently demonstrated benefits of ADHD medication on core symptoms (Cortese et al., 2018) and quality of life (Bellato, Perrott, et al., 2024), there is heterogeneity in treatment response at the individual level (Coghill et al., 2023;Salazar de Pablo et al., 2024). Clinical trials have not identified any characteristics consistently associated with this variability. ...
Individuals with attention‐deficit/hyperactivity disorder (ADHD) exhibit varied responses to pharmacological treatments (e.g. stimulants and non‐stimulants). Accurately and promptly detecting treatment‐related improvements, response failure, or deterioration poses significant challenges, as current monitoring primarily relies on subjective ratings. In this commentary, we critically evaluate the evidence supporting the use of QbTest for objectively monitoring ADHD treatment response in clinical practice. We also offer recommendations for future research, advocating for rigorous clinical trials and longitudinal studies to further explore the potential utilisation of QbTest and other tools for monitoring treatment responses in individuals with ADHD.
... Diagnosis currently depends solely on clinical assessment without objective tests. [16] Fortunately, the application of EEG offers a glimmer of hope for this dilemma. An increasing number of researchers are engaging in the study of EEG biomarkers related to ADHD, hoping to discover an objective and reliable diagnostic indicator, thereby providing a more scientific basis for the diagnosis and treatment of ADHD. ...
Attention deficit hyperactivity disorder (ADHD) is a profound neurodevelopmental disorder. Currently, the diagnosis of ADHD relies on clinical assessments and lacks objective testing. Research in electroencephalography (EEG) offers new hope for the diagnosis of ADHD, with researchers actively seeking objective EEG biomarkers. This study conducts a bibliometric analysis of the application of EEG in ADHD, aiming to provide a brief overview of the characteristics, main research areas, development paths, and trends in this field. The Web of Science Core Collection was queried on June 10, 2024, to gather relevant scholarly works from the period of 2004 to 2023. Analysis was conducted using CiteSpace, VOSviewer, and Microsoft Excel 2019. In the past 20 years, 1162 documents qualified, with a swift rise in annual publications. The USA, University of London, and Barry RJ led in productivity and impact, while the Clinical Neurophysiology topped in publication volume and citations. High-frequency terms include “ADHD,” “EEG,” “event-related potentials (ERP),” “children,” and “neurofeedback.” Clustering key terms such as “cognitive control,” “theta waves,” “epilepsy,” “graph theory,” “machine learning,” and “neurofeedback” form the cornerstone of the current core research areas. At the same time, a series of emerging research frontiers are gradually emerging, including “theta/beta ratio (TBR),” “P300 wave,” “neurofeedback,” and “deep learning.” Over the past 2 decades, research on the application of EEG in ADHD has been burgeoning, with themes becoming increasingly profound. These insights provide key guidance on current trends, development trajectories, and future challenges in the field.
Stimulant drugs that boost dopamine, like methylphenidate (MP), enhance attention and are effective treatments for attention-deficit hyperactivity disorder (ADHD). Yet there is large individual variation in attentional capacity and response to MP. It is unclear whether this variation is driven by individual differences in relative density of dopamine receptor subtypes, magnitude of dopamine increases induced by MP, or both. Here, we extensively characterized the brain dopamine system with positron emission tomography (PET) imaging (including striatal dopamine D1 and D2/3 receptor availability and MP-induced dopamine increases) and measured attention task-evoked fMRI brain activity in two separate sessions (placebo and 60 mg oral MP; single-blind, counterbalanced) in 37 healthy adults. A network of lateral frontoparietal and visual cortices was sensitive to increasing attentional (and working memory) load, whose activity positively correlated with performance across individuals (partial r = 0.474, P = 0.008; controlling for age). MP-induced change in activity within this network correlated with MP-induced change in performance (partial r = 0.686, P < 0.001). The ratio of D1-to-D2/3 receptors in dorsomedial caudate positively correlated with baseline attentional network activity and negatively correlated with MP-induced changes in activity (all pFWE < 0.02). MP-induced changes in attentional load network activity mediated the association between D1-to-D2/3 ratio and MP-induced improvements in performance (mediation estimate = 23.20 [95%CI: −153.67 −81.79], P = 0.004). MP attention-boosting effects were not linked to the magnitude of striatal dopamine increases, but rather showed dependence on an individual’s baseline receptor density. Individuals with lower D1-to-D2/3 ratios tended to have lower frontoparietal activity during sustained attention and experienced greater improvement in brain function and task performance with MP.
Objectives: Randomized controlled trials (RCTs) have shown that attention-deficit/hyperactivity disorder (ADHD) medications significantly reduce symptomatology at a group level, but individual response to ADHD medication is variable. Thus, developing prediction models to stratify treatment according to individual baseline clinicodemographic characteristics is crucial to support clinical practice. A potential valuable source of data to develop accurate prediction models is real-world clinical data extracted from electronic healthcare records (EHRs). Yet, systematic information regarding EHR data on ADHD is lacking. Methods: We conducted a comprehensive review of studies that included EHR reporting data regarding individuals with ADHD, with a specific focus on treatment-related data. Relevant studies were identified from PubMed, Ovid, and Web of Science databases up to February 24, 2024. Results: We identified 103 studies reporting EHR data for individuals with ADHD. Among these, 83 studies provided information on the type of prescribed medication. However, dosage, duration of treatment, and ADHD symptom ratings before and after treatment initiation were only reported by a minority of studies. Conclusion: This review supports the potential use of EHRs to develop treatment response prediction models but emphasizes the need for more comprehensive reporting of treatment-related data, such as changes in ADHD symptom ratings and other possible baseline clinical predictors of treatment response.
