Cerebral palsy with autism and ADHD: time to pay attention

Exploring the quantity and quality of symptoms of attention deficit hyperactivity disorder and intelligence in children with cerebral palsy: a case-control study

To evaluate whether attention deficit hyperactivity disorder (ADHD) symptoms differ across cerebral palsy (CP) and the relationship of these symptoms to CP disease data. Each of the three groups (CP, ADHD, and control) included 22 volunteers, aged 6-18. The CP group was divided into two groups, with and without ADHD (CP + ADHD and CP-ADHD). The groups were compared in terms of clinical data, ADHD symptoms, and intelligence levels. ADHD was reported in 36.4% of the CP group and 9.1% of the control group (p = 0.031). The rate of moderate/severe motor disability was higher (p = 0.052), and the Wechsler Intelligence Scale for Children-Revised (WISC-R) (total, performance, verbal) scores were lower in the CP + ADHD group compared to the CP-ADHD group (p = 0.005, p = 0.005, p = 0.002). Cognitive problems/inattention scores were higher in the CP group compared to the control group (p = 0.015). WISC-R (total, performance, verbal) scores were lower in the CP group compared to the ADHD group (p = 0.008, p = 0.001, p = 0.047) and the control group (p < 0.001, p < 0.001, p = 0.001).

CONCLUSION

ADHD is more common in CP and may be seen in a predominantly inattentive presentation. It is related to a worse motor disability and intelligence level in CP.

WHAT IS KNOWN

• Compared to the general population, ADHD is reported to be more common in children with CP.

WHAT IS NEW

• ADHD may be seen in a predominantly inattentive presentation rather than the other presentations in children with CP. • ADHD is related to a worse motor disability and intelligence level in CP.

The time is ripe for the renaissance of autism treatments: evidence from clinical practitioners

Introduction

Recent changes in diagnostics criteria have contributed to the broadening of the autism spectrum disorders and left clinicians ill-equipped to treat the highly heterogeneous spectrum that now includes toddlers and children with sensory and motor issues.

Methods

To uncover the clinicians' critical needs in the autism space, we conducted surveys designed collaboratively with the clinicians themselves. Board Certified Behavioral Analysts (BCBAs) and developmental model (DM) clinicians obtained permission from their accrediting boards and designed surveys to assess needs and preferences in their corresponding fields.

Results

92.6% of BCBAs are open to diversified treatment combining aspects of multiple disciplines; 82.7% of DMs also favor this diversification with 21.8% valuing BCBA-input and 40.6% neurologists-input; 85.9% of BCBAs and 85.3% of DMs advocate the use of wearables to objectively track nuanced behaviors in social exchange; 76.9% of BCBAs and 57.0% DMs feel they would benefit from augmenting their knowledge about the nervous systems of Autism (neuroscience research) to enhance treatment and planning programs; 50.0% of BCBAs feel they can benefit for more training to teach parents.

Discussion

Two complementary philosophies are converging to a more collaborative, integrative approach favoring scalable digital technologies and neuroscience. Autism practitioners seem ready to embrace the Digital-Neuroscience Revolutions under a new cooperative model.

Precision Autism: Genomic Stratification of Disorders Making Up the Broad Spectrum May Demystify Its "Epidemic Rates"

In the last decade, Autism has broadened and often shifted its diagnostics criteria, allowing several neuropsychiatric and neurological disorders of known etiology. This has resulted in a highly heterogeneous spectrum with apparent exponential rates in prevalence. I ask if it is possible to leverage existing genetic information about those disorders making up Autism today and use it to stratify this spectrum. To that end, I combine genes linked to Autism in the SFARI database and genomic information from the DisGeNET portal on 25 diseases, inclusive of non-neurological ones. I use the GTEx data on genes’ expression on 54 human tissues and ask if there are overlapping genes across those associated to these diseases and those from SFARI-Autism. I find a compact set of genes across all brain-disorders which express highly in tissues fundamental for somatic-sensory-motor function, self-regulation, memory, and cognition. Then, I offer a new stratification that provides a distance-based orderly clustering into possible Autism subtypes, amenable to design personalized targeted therapies within the framework of Precision Medicine. I conclude that viewing Autism through this physiological (Precision) lens, rather than viewing it exclusively from a psychological behavioral construct, may make it a more manageable condition and dispel the Autism epidemic myth.