Dr. Joseph Biederman's Enduring Legacy: Illuminating the Path to Addressing Autistic Traits in Attention Deficit Hyperactivity Disorder With Transcranial Photobiomodulation.

OBJECTIVE: To review the existing literature on transcranial photobiomodulation (tPBM) treatment effects on Autism Spectrum Disorder (ASD), in search for an effective treatment of a symptom cluster identified largely by contributions from late Dr. Biederman who asserted that they frequently present with Attention Deficit Hyperactivity Disorder (ADHD). METHOD: A survey of two databases, PubMed and PsycINFO, for clinical trials reporting on tPBM treatment in ASD was performed. Identified manuscripts that met eligibility criteria were then reviewed. RESULTS: Three original manuscripts reporting findings on a heterogenous group of study methods met the eligibility criteria. Despite the heterogenous nature of study designs, findings from all three studies reported tPBM treatment to be associated with improvements in ASD symptoms. No serious or treatment limiting adverse events were reported. CONCLUSIONS: A nascent body of research suggests further clinical studies investigating efficacy of tPBM in treatment of ASD symptoms should be supported.

ADHD in Adults: Does Age at Diagnosis Matter?

OBJECTIVE: To provide additional information about clinical features associated with adult ADHD in patients diagnosed in childhood compared to those first diagnosed in adulthood. METHOD: We stratified a sample of adults with ADHD into patients diagnosed in childhood versus adulthood and compared demographic and clinical characteristics. RESULTS: We found similar clinical features in adults diagnosed in childhood and adults diagnosed in adulthood. Among those diagnosed in adulthood, 95% reported symptom onset in youth. Our results do not support the hypothesis that ADHD diagnosed in adulthood is due to misinterpreting symptoms of other disorders as ADHD. They also suggest incorporating behavioral signs of executive dysfunction into diagnostic criteria for ADHD in adults may increase diagnostic sensitivity. CONCLUSION: These results support the validity of ADHD diagnoses in adulthood, as these adults show similar clinical profiles to those diagnosed in youth. Our results also suggest that if adult-onset ADHD exists, it is rare.

Stimulant Treatment and Potential Adverse Outcomes in Pediatric Populations With Bipolar Disorder: A Systematic Review of the Literature.

OBJECTIVE: To explore outcomes of stimulant treatment for ADHD in pediatric populations with particular attention to bipolar disorder (BPD). METHOD: We conducted a literature search of PubMed articles published prior to August 25, 2022 that focused on BPD, mania, and psychosis prior to, or as result of, stimulant treatment. We excluded studies: (1) unrelated to stimulants, (2) general stimulant research, (3) articles older than 40 years, (4) study protocols, or (5) case reports. RESULTS: A total of 11 articles met all inclusion/exclusion criteria. Some reports found stimulant treatment safe and well-tolerated in children with comorbid BPD and ADHD. Others found evidence of treatment-emergent mania (TEM), discontinuation, and other adverse events with stimulant treatment. CONCLUSION: Poor outcomes associated with stimulant treatment in pediatric populations with BPD necessitate work to identify patients at risk of serious stimulant-related adverse events. Our results were limited by automated search filters and a pediatric, primarily male sample.

Growth Trajectories in Stimulant Treated Children and Adolescents: A Qualitative Review of the Literature from Comprehensive Datasets and Registries.

Objective: Attention-deficit/hyperactivity disorder (ADHD) treatment with stimulant products has been shown to be safe and effective; however, there are remaining concerns about their possible adverse effects on growth trajectories. We conducted a systematic review of the extant literature derived from ecologically valid databases and registries to assess the body of knowledge about the effects of stimulants on growth trajectories in naturalistic samples. Methods: Using PubMed and PsycINFO, we searched for articles published before February 8, 2023 that focused on growth findings associated with stimulant treatment in pediatric ADHD from comprehensive datasets derived from naturalistic population studies. Results: Of the 1070 articles initially identified, 12 met all inclusion criteria. Sample sizes ranged from 157 to 163,820 youths. Seven of 10 articles examining height found significant decreases in height associated with chronic stimulant treatment that normalized over time in 2 studies. Three articles found no significant association between stimulant treatment and height. No clear associations were identified between cumulative duration and dose of stimulant treatment and adult height. All articles examining weight and six of eight articles examining body mass index (BMI) found significant initial decreases that tended to normalize then increase over time. Longer duration of stimulant medication use was predominantly associated with significant weight and BMI reductions. The effects of stimulant dose on weight and BMI were mostly weak and clinically insignificant. Most studies found no significant association between age at start of stimulant treatment and change in height, weight, or BMI. Most studies did not find significant sex effects in relation to growth parameters. Conclusions: This review of ecologically informative samples revealed that the effects of stimulant treatment on growth trajectories are mainly small and transient. These effects seem to be clinically insignificant for most youth with ADHD who receive stimulant treatment from childhood onto adolescence and adulthood.

Growth Trajectories in Stimulant-Treated Children Ages 6 to 12: An Electronic Medical Record Analysis.

OBJECTIVE: The aim of this study was to evaluate growth trajectories in stimulant-exposed and stimulant-unexposed children using electronic medical record data from a large health care organization attending to moderating effects of the magnitude of exposure to stimulants, sex, and race. METHODS: Weight, height, body mass index (BMI), prescription, and sociodemographic information were extracted from the electronic medical records of a large health care organization. Included were children who were 6 to 12 years at the time they were receiving stimulants with a concurrent growth assessment (index assessment) plus 1 to 4 years of additional growth assessments thereafter. Non-attention-deficit/hyperactivity disorder (ADHD) children who were unexposed to stimulants were age and sex matched to those exposed. Stimulant exposure was examined as the total number of months with stimulant prescriptions, percentage of follow-up time exposed to stimulants, and cumulative stimulant dose. RESULTS: Our sample consisted of 323 children exposed to stimulants with available growth data and 1615 unexposed children. Small but significant decreases in height trajectories were found over time in exposed children compared with those unexposed. Weight and BMI trajectories decreased in the first year of follow-up with stabilization and increased thereafter. Growth trajectory effects were largest in girls (height, weight, and BMI), White children (weight), and children with more total stimulant exposure (weight). CONCLUSION: This comprehensive analysis of an ecologically informative sample attending to key covariates of the magnitude of exposure to stimulants, sex, and race extends previous findings, showing that effects on growth trajectories are small and do not appear to pose a significant clinical concern for most children with ADHD treated with stimulants from childhood onto adolescent years.

Toward Operationalizing Executive Function Deficits in Adults With ADHD Using the Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A).

Objective: Although group findings document that executive function deficits (EFDs) contribute to the morbidity associated with adult attention-deficit/hyperactivity disorder (ADHD), it is unclear whether easy-to-use assessment methods can aid in the identification of EFDs at the individual level. The aim of the present study was to assess whether the Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A), a well-standardized, self-report instrument that assesses behavioral concomitants of EFDs, can serve that purpose.Methods: 1,090 consecutively referred 18- to 55-year-old adults of both sexes who were clinically referred for the evaluation and treatment of ADHD between June 2016 and December 2021 completed a battery of scales assessing several non-overlapping domains of functioning. Because the BRIEF Global Executive Composite (GEC) offers a single point summary of all other BRIEF-A scales, we used receiver operator characteristic (ROC) curves to identify the optimal cutoff on the BRIEF-A GEC to categorize patients as having executive dysfunction.Results: We averaged the optimal BRIEF-A GEC cut-points from the ROC curve analyses to categorize patients with (N = 480; 44%) and without (N = 610; 56%) EFDs (BRIEF-A GEC score ≥ 70 or < 70, respectively). Adults with ADHD with EFDs had significantly more severe ADHD symptoms (ADHD Self-Report Scale scores ≥ 24: 94% vs 41%, P < .001); higher levels of psychopathology (Adult Self Report Total Problems T-scores ≥ 64: 75% vs 19%, P < .001), emotional dysregulation (69% vs 23%, P < .001), mind wandering (84% vs 48%, P < .001), and symptoms of autism (Social Responsiveness Scale T-scores ≥ 66: 24% vs 3%, P < .001); and worse quality of life (Quality of Life Enjoyment and Satisfaction Questionnaire mean scores: 44.4 ± 8.2 vs 51.9 ± 8.5, P = .001) compared to those without EFDs. There were no major differences in outcomes by age, sex, or race.Conclusions: The BRIEF-A helped identify a sizeable minority of adults with ADHD with behavioral concomitants of EFDs that added substantial morbidity and disability beyond that expected by having ADHD alone.

Can machine learning identify childhood characteristics that predict future development of bipolar disorder a decade later?

Early identification of bipolar disorder may provide appropriate support and treatment, however there is no current evidence for statistically predicting whether a child will develop bipolar disorder. Machine learning methods offer an opportunity for developing empirically-based predictors of bipolar disorder. This study examined whether bipolar disorder can be predicted using clinical data and machine learning algorithms. 492 children, ages 6-18 at baseline, were recruited from longitudinal case-control family studies. Participants were assessed at baseline, then followed-up after 10 years. In addition to sociodemographic data, children were assessed with psychometric scales, structured diagnostic interviews, and cognitive and social functioning assessments. Using the Balanced Random Forest algorithm, we examined whether the diagnostic outcome of full or subsyndromal bipolar disorder could be predicted from baseline data. 45 children (10%) developed bipolar disorder at follow-up. The model predicted subsequent bipolar disorder with 75% sensitivity, 76% specificity, and an Area Under the Receiver Operating Characteristics of 75%. Predictors best differentiating between children who did or did not develop bipolar disorder were the Child Behavioral Checklist Externalizing and Internalizing behaviors, the Child Behavioral Checklist Total t-score, problematic school functions indexed through the Child Behavioral Checklist School Competence scale, and the Child Behavioral Checklist Anxiety/Depression and Aggression scales. Our study provides the first quantitative model to predict bipolar disorder. Longitudinal prediction may help clinicians assess children with emergent psychopathology for future risk of bipolar disorder, an area of clinical and scientific importance. Machine learning algorithms could be implemented to alert clinicians to risk for bipolar disorder.