Understanding patient characteristics and medication prescriptions in children with mental health and neurodevelopmental disorders referred to a sleep clinic-A quality improvement/quality assurance analysis.

Introduction: Motivated by challenges faced in outpatient sleep services for mental health and neurodevelopmental disorders (MHNDD) during the COVID-19 clinical shutdown, a pan-Canadian/international working group of clinicians and social scientists developed a concept for capturing challenging sleep and wake behaviours already at the referral stage in the community setting. Methods: In a quality improvement/quality assurance (QIQA) project, a visual logic model was the framework for identifying the multiple causes and possible interventions for sleep disturbances. Intake forms informed clinicians about situational experiences, goals/concerns, in addition to the questions from the Sleep Disturbances Scale for Children (SDSC), the ADHD Rating Scale-IV and medication history. Descriptive statistics were used to describe the sample. Results: 66% of the pilot study patients (n = 41) scored in the SDSC red domains (highest scoring) with highest sub-scores for insomnia (falling asleep 73%; staying asleep: 51%) and daytime somnolence (27%). A total of 90% of patients were taking at least one medication; 59% sleep initiation/sleep medications, 41% in combination with further non-stimulant medications, 9% with stimulants, 27% with antidepressants and 18% with antipsychotics. Polypharmacy was observed in 62% of all patients and in 73% of the ones medicated for sleep disturbances. Qualitative information supported individualisation of assessments. Conclusion: Our intake process enabled a comprehensive understanding of patients' sleep and wake profiles prior to assessment, at the referral stage. The high prevalence of insomnia in patients, combined with polypharmacy, requires special attention in the triaging process at the community level.

Iron deficiency and common neurodevelopmental disorders-A scoping review.

BACKGROUND: A wealth of human and experimental studies document a causal and aggravating role of iron deficiency in neurodevelopmental disorders. While pre-, peri-, and early postnatal iron deficiency sets the stage for the risk of developing neurodevelopmental disorders, iron deficiency acquired at later ages aggravates pre-existing neurodevelopmental disorders. Yet, the association of iron deficiency and neurodevelopmental disorders in childhood and adolescence has not yet been explored comprehensively. In this scoping review, we investigate 1) the association of iron deficiency in children and adolescents with the most frequent neurodevelopmental disorders, ADHD, ASD, and FASD, and 2) whether iron supplementation improves outcomes in these disorders. METHOD: Scoping review of studies published between 1994 and 2021 using "iron deficiency / iron deficiency anemia" AND "ADHD" OR "autism" OR "FASD" in four biomedical databases. The main inclusion criterion was that articles needed to have quantitative determination of iron status at any postnatal age with primary iron markers such as serum ferritin being reported in association with ADHD, ASD, or FASD. RESULTS: For ADHD, 22/30 studies and 4/4 systematic reviews showed an association of ADHD occurrence or severity with iron deficiency; 6/6 treatment studies including 2 randomized controlled trials demonstrated positive effects of iron supplementation. For ASD, 3/6 studies showed an association with iron deficiency, while 3/6 and 1/1 systematic literature review did not; 4 studies showed a variety of prevalence rates of iron deficiency in ASD populations; 1 randomized controlled trial found no positive effect of iron supplementation on behavioural symptoms of ASD. For FASD, 2/2 studies showed an association of iron deficiency with growth retardation in infants and children with prenatal alcohol exposure. CONCLUSION: Evidence in favor of screening for iron deficiency and using iron supplementation for pediatric neurodevelopmental disorders comes primarily from ADHD studies and needs to be further investigated for ASD and FASD. Further analysis of study methodologies employed and populations investigated is needed to compare studies against each other and further substantiate the evidence created.

Sleep as an outcome measure in ADHD randomized controlled trials: A scoping review.

Sleep disturbances are highly prevalent among children with ADHD. Yet, diagnostic and treatment regimens are primarily focused on daytime symptomatology. The goals of this scoping review are to 1) identify interventional ADHD RCTs that have used sleep as an outcome measure, 2) describe and assess the validity of tools utilized to measure sleep-specific outcomes. 40/71 RCTs used sleep as a primary outcome. Actigraphy (n = 18) and sleep log/diary (n = 16) were the most common tools to measure sleep, followed by Children's Sleep Habits Questionnaire (n = 13), and polysomnography (n = 10). Sleep was a secondary outcome in 31 RCTs. Polysomnography and actigraphy used a heterogeneous spectrum of sleep-related variables and technical algorithms, respectively. 19/23 sleep questionnaires were validated covering a spectrum of sleep-related domains. Despite the intrinsic nature of sleep disturbances in ADHD, the number of RCTs measuring sleep-specific outcomes is limited and tools to measure outcomes are not standardized. Given the potential adverse effects of ADHD medications on sleep, sleep should be included as a core outcome measure in future clinical trials.

Fidgety Philip and the Suggested Clinical Immobilization Test: Annotation data for developing a machine learning algorithm.

The cartoon Fidgety Philip, the banner of Western-ADHD diagnosis, depicts a 'restless' child exhibiting hyperactive-behaviors with hyper-arousability and/or hypermotor-restlessness (H-behaviors) during sitting. To overcome the gaps between differential diagnostic considerations and modern computing methodologies, we have developed a non-interpretative, neutral pictogram-guided phenotyping language (PG-PL) for describing body-segment movements during sitting (Journal of Psychiatric Research). To develop the PG-PL, seven research assistants annotated three original Fidgety Philip cartoons. Their annotations were analyzed with descriptive statistics. To review the PG-PL's performance, the same seven research assistants annotated 12 snapshots with free hand annotations, followed by using the PG-PL, each time in randomized sequence and on two separate occasions. After achieving satisfactory inter-observer agreements, the PG-PL annotation software was used for reviewing videos where the same seven research assistants annotated 12 one-minute long video clips. The video clip annotations were finally used to develop a machine learning algorithm for automated movement detection (Journal of Psychiatric Research). These data together demonstrate the value of the PG-PL for manually annotating human movement patterns. Researchers are able to reuse the data and the first version of the machine learning algorithm to further develop and refine the algorithm for differentiating movement patterns.

Is Fidgety Philip's ground truth also ours? The creation and application of a machine learning algorithm.

BACKGROUND: Behavioral observations support clinical in-depth phenotyping but phenotyping and pattern recognition are affected by training background. As Attention Deficit Hyperactivity Disorder, Restless Legs syndrome/Willis Ekbom disease and medication induced activation syndromes (including increased irritability and/or akathisia), present with hyperactive-behaviors with hyper-arousability and/or hypermotor-restlessness (H-behaviors), we first developed a non-interpretative, neutral pictogram-guided phenotyping language (PG-PL) for describing body-segment movements during sitting. METHODOLOGY & RESULTS: The PG-PL was applied for annotating 12 1-min sitting-videos (inter-observer agreements >85%->97%) and these manual annotations were used as a ground truth to develop an automated algorithm using OpenPose, which locates skeletal landmarks in 2D video. We evaluated the algorithm's performance against the ground truth by computing the area under the receiver operator curve (>0.79 for the legs, arms, and feet, but 0.65 for the head). While our pixel displacement algorithm performed well for the legs, arms, and feet, it predicted head motion less well, indicating the need for further investigations. CONCLUSION: This first automated analysis algorithm allows to start the discussion about distinct phenotypical characteristics of H-behaviors during structured behavioral observations and may support differential diagnostic considerations via in-depth phenotyping of sitting behaviors and, in consequence, of better treatment concepts.

Iron deficiency and sleep - A scoping review.

Iron deficiency (ID) is associated with sleep disorders, but standardized assessment of iron status in the diagnostic work-up and iron supplementation as treatment have not been considered in clinical practice. We investigated associations of ID with type and severity of sleep disorders and whether iron supplementation improves sleep-related symptoms. In 2017, we conducted a scoping review for the period 1972-2016 using the terms "iron deficiency anemia" and "sleep" on biomedical database search engines, and in 2019, we updated our review with an ad-hoc search. Among the 93 articles meeting our inclusion criteria, 74/93 studies investigated restless legs syndrome (RLS), 8/93 periodic limb movements in sleep (PLMs), 3/93 sleep disordered breathing (SDB), 6/93 general sleep disturbances (GSD), and 2/93 attention-deficit/ hyperactivity disorder related sleep disorders (ADHD-SDs). A statistically supported positive association with ID was found in 22/42 RLS, 3/8 PLMs, 1/2 SDB, 3/4 GSD, and 1/2 ADHD-SDs association studies. The ad-hoc literature search revealed eight additional association studies with a statistically supported positive association in 2/5 RLS, 1/1 SDB, 1/1 ADHD-SDs, and 1/1 restless sleep disorder (RSD) studies. Iron supplementation was beneficial in 29/30 RLS (including five randomized controlled trials [RCTs]), 1/1 SDB, and 2/2 GSD treatment studies. Iron supplementation was also beneficial in 2/2 RLS (including two RCTs), 1/1 GSD (RCT), and 1/1 RSD studies identified in the ad-hoc search. In pediatric populations, 1/1 RLS, 1/1 SDB, 2/5 PLMs, 2/3 GSD and 1/2 ADHD-SDs studies found positive associations, and 6/6 RLS and 2/2 GSD studies demonstrated a benefit with iron supplementation. In conclusion, iron investigation and supplementation should be considered in patients presenting with sleep disorders. To investigate the role of ID in sleep in the future, a harmonization of study designs, including outcome measures and standardized iron and inflammation status is necessary.