Faculty Bibliography

BACKGROUND:Attention Deficit/Hyperactivity Disorder (ADHD), if severe, is usually treated with stimulant or non-stimulant medication. However, users prefer non-drug treatments due to side effects. Alternative non-medication treatments have so far only shown modest effects. External trigeminal nerve stimulation (eTNS) is a minimal risk, non-invasive neuromodulation device, targeting the trigeminal system. It was approved for ADHD in 2019 by the USA Food and Drug administration (FDA) based on a small proof of concept randomised controlled trial (RCT) in 62 children with ADHD showing improvement of ADHD symptoms after 4 weeks of nightly real versus sham eTNS with minimal side effects. We present here the protocol of a larger confirmatory phase IIb study testing efficacy, longer-term persistency of effects and underlying mechanisms of action. METHODS:A confirmatory, sham-controlled, double-blind, parallel-arm, multi-centre phase IIb RCT of 4 weeks of eTNS in 150 youth with ADHD, recruited in London, Portsmouth, and Southampton, UK. Youth with ADHD will be randomized to either real or sham eTNS, applied nightly for 4 weeks. Primary outcome is the change in the investigator-administered parent rated ADHD rating scale. Secondary outcomes are other clinical and cognitive measures, objective hyperactivity and pupillometry measures, side effects, and maintenance of effects over 6 months. The mechanisms of action will be tested in a subgroup of 56 participants using magnetic resonance imaging (MRI) before and after the 4-week treatment. DISCUSSION/CONCLUSIONS:This multi-centre phase IIb RCT will confirm whether eTNS is effective in a larger age range of children and adolescents with ADHD, whether it improves cognition and other clinical measures, whether efficacy persists at 6 months and it will test underlying brain mechanisms. The results will establish whether eTNS is effective and safe as a novel non-pharmacological treatment for ADHD. TRIAL REGISTRATION/BACKGROUND:ISRCTN82129325 on 02/08/2021, https://doi.org/10.1186/ISRCTN82129325 .

OBJECTIVE/UNASSIGNED:To investigate shared and specific neural correlates of cognitive functions in attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), the authors performed a comprehensive meta-analysis and considered a balanced set of neuropsychological tasks across the two disorders. METHODS/UNASSIGNED:A broad set of electronic databases was searched up to December 4, 2022, for task-based functional MRI studies investigating differences between individuals with ADHD or ASD and typically developing control subjects. Spatial coordinates of brain loci differing significantly between case and control subjects were extracted. To avoid potential diagnosis-driven selection bias of cognitive tasks, the tasks were grouped according to the Research Domain Criteria framework, and stratified sampling was used to match cognitive component profiles. Activation likelihood estimation was used for the meta-analysis. RESULTS/UNASSIGNED:After screening 20,756 potentially relevant references, a meta-analysis of 243 studies was performed, which included 3,084 participants with ADHD (676 females), 2,654 participants with ASD (292 females), and 6,795 control subjects (1,909 females). ASD and ADHD showed shared greater activations in the lingual and rectal gyri and shared lower activations in regions including the middle frontal gyrus, the parahippocampal gyrus, and the insula. By contrast, there were ASD-specific greater and lower activations in regions including the left middle temporal gyrus and the left middle frontal gyrus, respectively, and ADHD-specific greater and lower activations in the amygdala and the global pallidus, respectively. CONCLUSIONS/UNASSIGNED:Although ASD and ADHD showed both shared and disorder-specific standardized neural activations, disorder-specific activations were more prominent than shared ones. Functional brain differences between ADHD and ASD are more likely to reflect diagnosis-related pathophysiology than bias from the selection of specific neuropsychological tasks.

IMPORTANCE/UNASSIGNED:Noninvasive brain stimulation (NIBS) interventions have been shown to be efficacious in several mental disorders, but the optimal dose stimulation parameters for each disorder are unknown. OBJECTIVE/UNASSIGNED:To define NIBS dose stimulation parameters associated with the greatest efficacy in symptom improvement across mental disorders. DATA SOURCES/UNASSIGNED:Studies were drawn from an updated (to April 30, 2023) previous systematic review based on a search of PubMed, OVID, and Web of Knowledge. STUDY SELECTION/UNASSIGNED:Randomized clinical trials were selected that tested transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS) for any mental disorder in adults aged 18 years or older. DATA EXTRACTION AND SYNTHESIS/UNASSIGNED:Two authors independently extracted the data. A 1-stage dose-response meta-analysis using a random-effects model was performed. Sensitivity analyses were conducted to test robustness of the findings. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The main outcome was the near-maximal effective doses of total pulses received for TMS and total current dose in coulombs for tDCS. RESULTS/UNASSIGNED:A total of 110 studies with 4820 participants (2659 men [61.4%]; mean [SD] age, 42.3 [8.8] years) were included. The following significant dose-response associations emerged with bell-shaped curves: (1) in schizophrenia, high-frequency (HF) TMS on the left dorsolateral prefrontal cortex (LDLPFC) for negative symptoms (χ2 = 9.35; df = 2; P = .009) and TMS on the left temporoparietal junction for resistant hallucinations (χ2 = 36.52; df = 2; P < .001); (2) in depression, HF-DLPFC TMS (χ2 = 14.49; df = 2; P < .001); (3) in treatment-resistant depression, LDLPFC tDCS (χ2 = 14.56; df = 2; P < .001); and (4) in substance use disorder, LDLPFC tDCS (χ2 = 33.63; df = 2; P < .001). The following significant dose-response associations emerged with plateaued or ascending curves: (1) in depression, low-frequency (LF) TMS on the right DLPFC (RDLPFC) with ascending curve (χ2 = 25.67; df = 2; P = .001); (2) for treatment-resistant depression, LF TMS on the bilateral DLPFC with ascending curve (χ2 = 5.86; df = 2; P = .004); (3) in obsessive-compulsive disorder, LF-RDLPFC TMS with ascending curve (χ2 = 20.65; df = 2; P < .001) and LF TMS on the orbitofrontal cortex with a plateaued curve (χ2 = 15.19; df = 2; P < .001); and (4) in posttraumatic stress disorder, LF-RDLPFC TMS with ascending curve (χ2 = 54.15; df = 2; P < .001). Sensitivity analyses confirmed the main findings. CONCLUSIONS AND RELEVANCE/UNASSIGNED:The study findings suggest that NIBS yields specific outcomes based on dose parameters across various mental disorders and brain regions. Clinicians should consider these dose parameters when prescribing NIBS. Additional research is needed to prospectively validate the findings in randomized, sham-controlled trials and explore how other parameters contribute to the observed dose-response association.

In this narrative, comprehensive, and updated review of the literature, we summarize evidence about the effectiveness of interventions aimed at reducing emotion dysregulation and improving emotion regulation in children, adolescents, and adults. After introducing emotion dysregulation and emotion regulation from a theoretical standpoint, we discuss the factors commonly associated with emotion regulation, including neurobiological and neuropsychological mechanisms, and the role of childhood adverse experiences and psycho-social factors in the onset of emotion dysregulation. We then present evidence about pharmacological and non-pharmacological interventions aiming at improving emotion dysregulation and promoting emotion regulation across the lifespan. Although our review was not intended as a traditional systematic review, and the search was only restricted to systematic reviews and meta-analyses, we highlighted important implications and provided recommendations for clinical practice and future research in this field.

OBJECTIVE:To investigate the potential association between prenatal opioid exposure and the risk of neuropsychiatric disorders in children. DESIGN:Nationwide birth cohort study. SETTING:From 1 January 2009 to 31 December 2020, birth cohort data of pregnant women in South Korea linked to their liveborn infants from the National Health Insurance Service of South Korea were collected. PARTICIPANTS:All 3 251 594 infants (paired mothers, n=2 369 322; age 32.1 years (standard deviation 4.2)) in South Korea from the start of 2010 to the end of 2017, with follow-up from the date of birth until the date of death or 31 December 2020, were included. MAIN OUTCOME MEASURES:Diagnosis of neuropsychiatric disorders in liveborn infants with mental and behaviour disorders (International Classification of Diseases 10th edition codes F00-99). Follow-up continued until the first diagnosis of neuropsychiatric disorder, 31 December 2020 (end of the study period), or the date of death, whichever occurred first. Eight cohorts were created: three cohorts (full unmatched, propensity score matched, and child screening cohorts) were formed, all of which were paired with sibling comparison cohorts, in addition to two more propensity score groups. Multiple subgroup analyses were performed. RESULTS:Of the 3 128 571 infants included (from 2 299 664 mothers), we identified 2 912 559 (51.3% male, 48.7% female) infants with no prenatal opioid exposure and 216 012 (51.2% male, 48.8% female) infants with prenatal opioid exposure. The risk of neuropsychiatric disorders in the child with prenatal opioid exposure was 1.07 (95% confidence interval 1.05 to 1.10) for fully adjusted hazard ratio in the matched cohort, but no significant association was noted in the sibling comparison cohort (hazard ratio 1.00 (0.93 to 1.07)). Prenatal opioid exposure during the first trimester (1.11 (1.07 to 1.15)), higher opioid doses (1.15 (1.09 to 1.21)), and long term opioid use of 60 days or more (1.95 (1.24 to 3.06)) were associated with an increased risk of neuropsychiatric disorders in the child. Prenatal opioid exposure modestly increased the risk of severe neuropsychiatric disorders (1.30 (1.15 to 1.46)), mood disorders, attention deficit hyperactivity disorder, and intellectual disability in the child. CONCLUSIONS:Opioid use during pregnancy was not associated with a substantial increase in the risk of neuropsychiatric disorders in the offspring. A slightly increased risk of neuropsychiatric disorders was observed, but this should not be considered clinically meaningful given the observational nature of the study, and limited to high opioid dose, more than one opioid used, longer duration of exposure, opioid exposure during early pregnancy, and only to some neuropsychiatric disorders.

BACKGROUND:Several computerised cognitive tests (e.g. continuous performance test) have been developed to support the clinical assessment of attention-deficit/hyperactivity disorder (ADHD). Here, we appraised the evidence-base underpinning the use of one of these tests - the QbTest - in clinical practice, by conducting a systematic review and meta-analysis investigating its accuracy and clinical utility. METHODS:Based on a preregistered protocol (CRD42022377671), we searched PubMed, Medline, Ovid Embase, APA PsycINFO and Web of Science on 15th August 2022, with no language/type of document restrictions. We included studies reporting accuracy measures (e.g. sensitivity, specificity, or Area under the Receiver Operating Characteristics Curve, AUC) for QbTest in discriminating between people with and without DSM/ICD ADHD diagnosis. Risk of bias was assessed with the Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2). A generic inverse variance meta-analysis was conducted on AUC scores. Pooled sensitivity and specificity were calculated using a random-effects bivariate model in R. RESULTS:We included 15 studies (2,058 participants; 48.6% with ADHD). QbTest Total scores showed acceptable, rather than good, sensitivity (0.78 [95% confidence interval: 0.69; 0.85]) and specificity (0.70 [0.57; 0.81]), while subscales showed low-to-moderate sensitivity (ranging from 0.48 [0.35; 0.61] to 0.65 [0.52; 0.75]) and moderate-to-good specificity (from 0.65 [0.48; 0.78] to 0.83 [0.60; 0.94]). Pooled AUC scores suggested moderate-to-acceptable discriminative ability (Q-Total: 0.72 [0.57; 0.87]; Q-Activity: 0.67 [0.58; 0.77); Q-Inattention: 0.66 [0.59; 0.72]; Q-Impulsivity: 0.59 [0.53; 0.64]). CONCLUSIONS:When used on their own, QbTest scores available to clinicians are not sufficiently accurate in discriminating between ADHD and non-ADHD clinical cases. Therefore, the QbTest should not be used as stand-alone screening or diagnostic tool, or as a triage system for accepting individuals on the waiting-list for clinical services. However, when used as an adjunct to support a full clinical assessment, QbTest can produce efficiencies in the assessment pathway and reduce the time to diagnosis.

INTRODUCTION/UNASSIGNED:Sleep disorders represent an important comorbidity in individuals with ADHD. While the links between ADHD and sleep disturbances have been extensively investigated, research on the management of sleep disorders in individuals with ADHD is relatively limited, albeit expanding. AREAS COVERED/UNASSIGNED:The authors searched PubMed, Medline, PsycInfo, Embase+Embase Classic, Web of Sciences databases, and clinicaltrials.gov up to 4 January 2024, for randomized controlled trials (RCTs) of any intervention for sleep disorders associated with ADHD. They retained 16 RCTs (eight on pharmacological and eight on non-pharmacological interventions), supporting behavioral intervention and melatonin, and nine ongoing RCTs registered on clinicaltrials.gov. EXPERT OPINION/UNASSIGNED:The pool of RCTs testing interventions for sleep disorders in individuals with ADHD is expanding. However, to inform clinical guidelines, there is a need for additional research in several areas, including 1) RCTs based on a precise phenotyping of sleep disorders; 2) pragmatic RCTs recruiting neurodevelopmental populations representative of those seen in clinical services; 3) trials testing alternative interventions (e.g. suvorexant or light therapy) or ways to deliver them (e.g. online); 4) sequential and longer-term RCTs; 5) studies testing the impact of sleep interventions on outcomes other than sleep; 6) and implementation of advanced evidence synthesis and precision medicine approaches.

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 models. We did a PRISMA/CHARMS/TRIPOD-compliant systematic review (PROSPERO: CRD42023387502), searching, until 20/12/2023, studies reporting internally and/or externally validated diagnostic/prognostic/treatment-response prediction models in ADHD. Using meta-regressions, we explored the impact of factors affecting the area under the curve (AUC) of the models. We assessed the study risk of bias with the Prediction Model Risk of Bias Assessment Tool (PROBAST). From 7764 identified records, 100 prediction models were included (88% diagnostic, 5% prognostic, and 7% treatment-response). Of these, 96% and 7% were internally and externally validated, respectively. None was implemented in clinical practice. Only 8% of the models were deemed at low risk of bias; 67% were considered at high risk of bias. Clinical, neuroimaging, and cognitive predictors were used in 35%, 31%, and 27% of the studies, respectively. The performance of ADHD prediction models was increased in those models including, compared to those models not including, clinical predictors (β = 6.54, p = 0.007). Type of validation, age range, type of model, number of predictors, study quality, and other type of predictors did not alter the AUC. Several prediction models have been developed to support the diagnosis of ADHD. However, efforts to predict outcomes or treatment response have been limited, and none of the available models is ready for implementation into clinical practice. The use of clinical predictors, which may be combined with other type of predictors, seems to improve the performance of the models. A new generation of research should address these gaps by conducting high quality, replicable, and externally validated models, followed by implementation research.

IMPORTANCE:Attention-deficit/hyperactivity disorder (ADHD) is associated with increased risks of adverse health outcomes including premature death, but it is unclear whether ADHD pharmacotherapy influences the mortality risk. OBJECTIVE:To investigate whether initiation of ADHD pharmacotherapy was associated with reduced mortality risk in individuals with ADHD. DESIGN, SETTING, AND PARTICIPANTS:In an observational nationwide cohort study in Sweden applying the target trial emulation framework, we identified individuals aged 6 through 64 years with an incident diagnosis of ADHD from 2007 through 2018 and no ADHD medication dispensation prior to diagnosis. Follow-up started from ADHD diagnosis until death, emigration, 2 years after ADHD diagnosis, or December 31, 2020, whichever came first. EXPOSURES:ADHD medication initiation was defined as dispensing of medication within 3 months of diagnosis. MAIN OUTCOMES AND MEASURES:We assessed all-cause mortality within 2 years of ADHD diagnosis, as well as natural-cause (eg, physical conditions) and unnatural-cause mortality (eg, unintentional injuries, suicide, and accidental poisonings). RESULTS:Of 148 578 individuals with ADHD (61 356 females [41.3%]), 84 204 (56.7%) initiated ADHD medication. The median age at diagnosis was 17.4 years (IQR, 11.6-29.1 years). The 2-year mortality risk was lower in the initiation treatment strategy group (39.1 per 10 000 individuals) than in the noninitiation treatment strategy group (48.1 per 10 000 individuals), with a risk difference of -8.9 per 10 000 individuals (95% CI, -17.3 to -0.6). ADHD medication initiation was associated with significantly lower rate of all-cause mortality (hazard ratio [HR], 0.79; 95% CI, 0.70 to 0.88) and unnatural-cause mortality (2-year mortality risk, 25.9 per 10 000 individuals vs 33.3 per 10 000 individuals; risk difference, -7.4 per 10 000 individuals; 95% CI, -14.2 to -0.5; HR, 0.75; 95% CI, 0.66 to 0.86), but not natural-cause mortality (2-year mortality risk, 13.1 per 10 000 individuals vs 14.7 per 10 000 individuals; risk difference, -1.6 per 10 000 individuals; 95% CI, -6.4 to 3.2; HR, 0.86; 95% CI, 0.71 to 1.05). CONCLUSIONS AND RELEVANCE:Among individuals diagnosed with ADHD, medication initiation was associated with significantly lower all-cause mortality, particularly for death due to unnatural causes.