When Autistic Behavior Suggests a Disease Other than Classic Autism

Association between Autism Spectrum Disorder (ASD) and vision problems. A systematic review and meta-analysis

AIM

To conduct a systematic review and meta-analysis assessing whether vision and/or eye disorders are associated with Autism Spectrum Disorder (ASD).

METHOD

Based on a pre-registered protocol (PROSPERO: CRD42022328485), we searched PubMed, Web of Knowledge/Science, Ovid Medline, Embase and APA PsycINFO up to 5th February 2022, with no language/type of document restrictions. We included observational studies 1) reporting at least one measure of vision in people of any age with a diagnosis of ASD based on DSM or ICD criteria, or ADOS; or 2) reporting the prevalence of ASD in people with and without vision disorders. Study quality was assessed with the Appraisal tool for Cross-Sectional Studies (AXIS). Random-effects meta-analyses were used for data synthesis.

RESULTS

We included 49 studies in the narrative synthesis and 46 studies in the meta-analyses (15,629,159 individuals distributed across multiple different measures). We found meta-analytic evidence of increased prevalence of strabismus (OR = 4.72 [95% CI: 4.60, 4.85]) in people with versus those without ASD (non-significant heterogeneity: Q = 1.0545, p = 0.7881). We also found evidence of increased accommodation deficits (Hedge's g = 0.68 [CI: 0.28, 1.08]) (non-significant heterogeneity: Q = 6.9331, p = 0.0741), reduced peripheral vision (-0.82 [CI: -1.32, -0.33]) (non-significant heterogeneity: Q = 4.8075, p = 0.4398), reduced stereoacuity (0.73 [CI: -1.14, -0.31]) (non-significant heterogeneity: Q = 0.8974, p = 0.3435), increased color discrimination difficulties (0.69 [CI: 0.27,1.10]) (non-significant heterogeneity: Q = 9.9928, p = 0.1890), reduced contrast sensitivity (0.45 [CI: -0.60, -0.30]) (non-significant heterogeneity: Q = 9.9928, p = 0.1890) and increased retinal thickness (=0.29 [CI: 0.07, 0.51]) (non-significant heterogeneity: Q = 0.8113, p = 0.9918) in ASD.

DISCUSSION

ASD is associated with some self-reported and objectively measured functional vision problems, and structural alterations of the eye, even though we observed several methodological limitations in the individual studies included in our meta-analyses. Further research should clarify the causal relationship, if any, between ASD and problems of vision during early life.

PROSPERO REGISTRATION

CRD42022328485.

Reliability and validity of the Autism Screen for Kids and Youth

LAY ABSTRACT

It is important that autistic children be diagnosed as early as possible so their needs can be met and their families can gain important insights into their behavior and interact with them appropriately. However, very few autism screening instruments are appropriate for children who have outgrown early childhood. The Autism Screen for Kids and Youth (ASKY) presents parents of children aged 4-18 years with 30 items that relate to autistic behaviors as defined by the current clinical diagnostic criteria for autism spectrum disorder (DSM-5 ASD). We evaluated the Hebrew instrument's performance on 167 autistic and non-autistic children and adolescents. We found that the ASKY algorithm correctly identified 92% of the autistic individuals as "probable ASD" and correctly identified 72% of the non-autistic individuals as "probable non-ASD," with these classifications showing excellent stability over time. Using total questionnaire score instead of the algorithm improved the ASKY's ability to correctly identify autistic individuals as "probable ASD" and non-autistic individuals as "probable non-ASD" to 93% and 78%, respectively. Overall, the ASKY is a promising instrument for ASD screening of older children.

Selective Mutism in Children With and Without an Autism Spectrum Disorder: The Role of Sensory Avoidance in Mediating Symptoms of Social Anxiety

The present study addressed the different contributors to social anxiety in children with Selective Mutism (SM), with and without co-occurring Autism Spectrum Disorder (ASD) (SM + ASD). Seventy-five parents completed an online composite questionnaire consisting of the symptoms of SM and ASD, anxiety and sensory measures. The results found the SM + ASD group showed significantly higher levels of social anxiety and sensory avoidance compared to the SM only group. However, a simple mediation model revealed sensory avoidance to be a mediator of this relationship between the diagnosis and social anxiety.. Therefore, higher levels of sensory avoidance may help to differentiate social anxiety between the groups and may also be a sign of ASD in children with SM who have and/or are yet to receive an ASD diagnosis.

Differentiation of autism spectrum disorder and mood or anxiety disorder

LAY ABSTRACT

Symptoms of mood and anxiety disorders overlap with symptoms of autism spectrum disorder, making the diagnostic process challenging. This study found that a combination of communicational deficits and unusual and/or inappropriate social overtures facilitates differentiation between autism spectrum disorder and mood and anxiety disorders. Furthermore, the results confirm the essential need of a behavioral observation with the Autism Diagnostic Observation Schedule in combination with a full Autism Diagnostic Interview-Revised to support diagnostic decisions.

Selective Mutism and Its Relations to Social Anxiety Disorder and Autism Spectrum Disorder

In current classification systems, selective mutism (SM) is included in the broad anxiety disorders category. Indeed, there is abundant evidence showing that anxiety, and social anxiety in particular, is a prominent feature of SM. In this article, we point out that autism spectrum problems in addition to anxiety problems are sometimes also implicated in SM. To build our case, we summarize evidence showing that SM, social anxiety disorder (SAD), and autism spectrum disorder (ASD) are allied clinical conditions and share communalities in the realm of social difficulties. Following this, we address the role of a prototypical class of ASD symptoms, restricted and repetitive behaviors and interests (RRBIs), which are hypothesized to play a special role in the preservation and exacerbation of social difficulties. We then substantiate our point that SM is sometimes more than an anxiety disorder by addressing its special link with ASD in more detail. Finally, we close by noting that the possible involvement of ASD in SM has a number of consequences for clinical practice with regard to its classification, assessment, and treatment of children with SM and highlight a number of directions for future research.

Special educational support in children and adolescents with Autism Spectrum Disorder in Germany: Results from a parent survey

OBJECTIVE

Children and adolescents with Autism Spectrum Disorder (ASD) often receive special educational support (SES). This study aimed to evaluate SES prevalence in children and adolescents with ASD in Germany.

METHODS

A mail survey was distributed to the caregivers of 637 children and adolescents recruited at three German ASD outpatient clinics.

RESULTS

Among the 211 respondents (response: 33.1 %), 82.5 % were provided with a special educational needs statement, and 63.9 % received special education, most of them attending a public special school (57.9 %). The most frequently indicated additional support was a classroom assistant (69.0 %), followed by smaller learning groups (31.7 %). Special education was less frequently provided to individuals with Asperger syndrome than to those with childhood or atypical autism (36.0 %, 76.1 %, and 63.4 %, respectively). Using logistic regression analysis, receiving special education was significantly associated with lower IQ (<85) (Odds Ratio (OR): 8.72; 95 % confidence interval (CI): 3.41-22.32) and younger age (≤11 years, OR: 2.87; 95 % CI: 1.11-7.38), but not with ASD symptom severity.

CONCLUSIONS

The majority of children and adolescents with ASD received SES, indicating a satisfactory supply of such services in Germany. The finding that lower IQ but not ASD symptom severity predicted access to SES raises questions about the specificity of the used selection criteria.

One-Year Follow-Up Diagnostic Stability of Autism Spectrum Disorder Diagnosis in a Clinical Sample of Children and Toddlers

Some studies show that the diagnosis of Autism Spectrum Disorder could be considered reliable and stable in children aged 18 to 24 months. Nevertheless, the diagnostic stability of early ASD diagnosis has not yet been fully demonstrated. This observational study examines the one-year diagnostic stability of autism spectrum disorder diagnosis in a clinical sample of 147 children diagnosed between 18 and 48 months of age. The ADOS-2 scores were used in order to stratify children in three levels of symptom severity: Autism (AD; comparison score 5–7), Autism Spectrum Disorder (ASD; comparison score 3–4), and Sub-Threshold Symptoms; (STS; comparison score 1–2). Results: Overall, the largest part of children and toddlers diagnosed with autism spectrum disorder between 18 and 48 months continued to show autistic symptoms at one-year follow-up evaluation. Nevertheless, a significant percentage of children with higher ADOS severity scores exhibited a reduction of symptom severity and, therefore, moved towards a milder severity class one year later. Conversely, the number of subjects of the STS group meaningfully increased. Therefore, at one-year follow-up a statistically significant (χ²(2) = 181.46, p < 0.0001) percentage of subjects (25.2% of the total) who had received a categorical diagnosis of Autistic Disorder or Autism Spectrum Disorder in baseline no longer met the criteria for a categorical diagnosis. Furthermore, children who no longer met the criteria for autism spectrum disorder continue to show delays in one or more neurodevelopmental areas, possibly related to the emergence of other neurodevelopmental/neuropsychiatric disorders. Overall, the comprehensive results of the study account for a high sensibility but a moderate stability of ASD early diagnosis.

The Development of a Practical Artificial Intelligence Tool for Diagnosing and Evaluating Autism Spectrum Disorder: Multicenter Study

Background

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with an unknown etiology. Early diagnosis and intervention are key to improving outcomes for patients with ASD. Structural magnetic resonance imaging (sMRI) has been widely used in clinics to facilitate the diagnosis of brain diseases such as brain tumors. However, sMRI is less frequently used to investigate neurological and psychiatric disorders, such as ASD, owing to the subtle, if any, anatomical changes of the brain.

Objective

This study aimed to investigate the possibility of identifying structural patterns in the brain of patients with ASD as potential biomarkers in the diagnosis and evaluation of ASD in clinics.

Methods

We developed a novel 2-level histogram-based morphometry (HBM) classification framework in which an algorithm based on a 3D version of the histogram of oriented gradients (HOG) was used to extract features from sMRI data. We applied this framework to distinguish patients with ASD from healthy controls using 4 datasets from the second edition of the Autism Brain Imaging Data Exchange, including the ETH Zürich (ETH), NYU Langone Medical Center: Sample 1, Oregon Health and Science University, and Stanford University (SU) sites. We used a stratified 10-fold cross-validation method to evaluate the model performance, and we applied the Naive Bayes approach to identify the predictive ASD-related brain regions based on classification contributions of each HOG feature.

Results

On the basis of the 3D HOG feature extraction method, our proposed HBM framework achieved an area under the curve (AUC) of >0.75 in each dataset, with the highest AUC of 0.849 in the ETH site. We compared the 3D HOG algorithm with the original 2D HOG algorithm, which showed an accuracy improvement of >4% in each dataset, with the highest improvement of 14% (6/42) in the SU site. A comparison of the 3D HOG algorithm with the scale-invariant feature transform algorithm showed an AUC improvement of >18% in each dataset. Furthermore, we identified ASD-related brain regions based on the sMRI images. Some of these regions (eg, frontal gyrus, temporal gyrus, cingulate gyrus, postcentral gyrus, precuneus, caudate, and hippocampus) are known to be implicated in ASD in prior neuroimaging literature. We also identified less well-known regions that may play unrecognized roles in ASD and be worth further investigation.

Conclusions

Our research suggested that it is possible to identify neuroimaging biomarkers that can distinguish patients with ASD from healthy controls based on the more cost-effective sMRI images of the brain. We also demonstrated the potential of applying data-driven artificial intelligence technology in the clinical setting of neurological and psychiatric disorders, which usually harbor subtle anatomical changes in the brain that are often invisible to the human eye.

Segen oder Fluch? Das Internet als Informationsquelle über Autismus und Asperger-Syndrom

Zusammenfassung. Fragestellung: Sehr viele Menschen informieren sich heutzutage über gesundheitsrelevante Themen im Internet, wobei die Qualität dieser Informationen fraglich ist. In der vorliegenden Studie soll beispielhaft für ein psychisches Störungsbild (Autismus-Spektrum-Störung) die Qualität der Informationsquelle Internet sowie die sich daraus ergebenden Implikationen diskutiert werden. Methodik: Es wurde eine systematische Auswertung von 96 deutschsprachigen Internetseiten durchgeführt mit dem Ziel, neben konkreten Charakteristika der Internetseiten auch die Zuverlässigkeit der Publikationen, die Informationsdarstellung sowie die Gesamtqualität der Internetseiten zu bewerten und die sich aus der Darstellung ergebenden klinischen Implikationen zu analysieren. Ergebnisse: Nur bei 39 % der Internetseiten ließen sich Referenzen für wissenschaftlich fundierte Informationen feststellen, Werbung war hingegen auf 53 % der Internetseiten vorhanden. Die meisten falschen Informationen wurden im Bereich der „Behandlung“ (17 %) verbreitet. Bei 75 % der Internetseiten traf die Vollständigkeit nicht zu. Lediglich 10 % der Internetseiten thematisierte die Beeinträchtigung bzw. Belastung der Familien. Die Qualität der Seiten wurde bei 30 % als ungenügend, bei 41 % als mangelhaft und nur bei 6 % als gut beurteilt. Schlussfolgerungen: Ähnlich wie durch die bereits vorliegenden Analysen zu englischsprachigen Internetseiten festgestellt, können für viele der deutschsprachigen Seiten deutliche Qualitätsmängel konstatiert werden. Die Implikationen in Bezug auf Bestätigungsfehler, Stigmatisierung, Überidentifikation, Ingroup-Outgroup-Effekte, Kontrast- und Schneeballeffekte werden diskutiert.

Transitions, Suicidality, and Underappreciated Autism Spectrum Disorder in a High School Student

Alex is a 14-year-old Portuguese-American boy with a psychiatric history starting at age 5 who presents to your primary care practice after an insurance change.He was delivered prematurely at 32 weeks and diagnosed with congenital hypothyroidism at the age of 6 weeks and growth hormone deficiency at the age of 2 years; he is in active treatment for both. He otherwise met developmental milestones on time yet continues to have significant fatigue despite adequate sleep and vitamin D supplementation.His family history is remarkable for maternal anxiety, depression, suicidal thoughts, and previous attempted suicide, as well as anxiety, alcoholism, depression, and attention-deficit/hyperactivity disorder (ADHD) in the extended family.Alex has had multiple psychiatric diagnoses by sequential providers. He was diagnosed with generalized anxiety disorder and ADHD by 5 years of age, major depressive disorder by 11 years of age, persistent depressive disorder by 12 years of age, and ultimately disruptive mood dysregulation disorder because of severe and persistent temper outbursts associated with negative mood and behavioral dysregulation, leading to recurrent crisis evaluations. He has been psychiatrically hospitalized twice, in the fifth and seventh grade, for suicidal ideation (SI) and elopement from home, respectively. He recently completed a 2-week acute residential placement, during which no medication changes were made. Current medications include escitalopram 20 mg daily, guanfacine 1 mg 3 times daily, sustained release bupropion 100 mg twice daily, levothyroxine, vitamin D, and a weekly somatropin injection. He has not been able to tolerate psychostimulants or nonstimulant agents because of treatment-emergent SI.Now in the ninth grade, he continues to be easily distracted by peers, with impulsive behaviors and reduced self-regulation. Despite receiving special education services since the fifth grade, his academic performance has been poor, and he has limited motivation. Previous testing indicated average in an intelligence quotient test, with relative deficits in working memory compared with above average strength in fluid reasoning. He dislikes school and has few friends. He has always been noted to be "immature." He displays temper tantrums at home and school around transitions and behavioral expectations and has complained of feeling "different" and misunderstood by peers in addition to having difficulty reading social cues. His interests include acting and playing Fortnite and other video/computer games. His screen time is limited to 1 to 2 hr/d by the family.As the new clinician, you raise the possibility of undiagnosed autism spectrum disorder as a unifying/underlying diagnosis with his mother, who disagrees and does not consent to additional workup despite your recommendations. How would you proceed with next steps to best support your patient and his family in obtaining further clarifying evaluation?

An Interprofessional Team Approach to the Differential Diagnosis of Children with Language Disorders

The ability to communicate effectively with others is central to children's development. Delays or disruptions due to isolated expressive language delay, articulation errors, multiple sound production errors with motor planning deficits, or mixed expressive and receptive language delay, often bring widespread consequences. Physical anomalies, neurologic and genetic disorder, cognitive and intellectual disabilities, and emotional disturbances may affect speech and language development. Communication disorders may be misdiagnosed as intellectual impairment or autism. Interdisciplinary evaluation should include speech and language assessment, physical and neurologic status, cognitive and emotional profile, and family and social history. This article describes assessment and reviews common pediatric communication disorders.