scholarly journals Correction to: Systematic Review of the Effect of Modification of Antecedents in the Treatment of Sleep Problems Among Children on the Autism Spectrum

2021 ◽  
Author(s):  
Kate A. M. Ford ◽  
Laurie K. McLay ◽  
Karyn G. France ◽  
Neville M. Blampied ◽  
Rosina M. Gibbs
Keyword(s):  
Systematic Review ◽  
Sleep Problems ◽  
Autism Spectrum

scholarly journals Umbrella systematic review of systematic reviews and meta-analyses on comorbid physical conditions in people with autism spectrum disorder

2020 ◽  
Vol 218 (1) ◽  
pp. 10-19 ◽  
Author(s):  
Ewelina Rydzewska ◽  
Kirsty Dunn ◽  
Sally-Ann Cooper
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Systematic Reviews ◽  
Sleep Problems ◽  
Evidence Base ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Physical Conditions ◽  
Sensory Impairments ◽  
Meta Analyses

BackgroundComorbid physical conditions may be more common in people with autism spectrum disorder (ASD) than other people.AimsTo identify what is and what is not known about comorbid physical conditions in people with ASD.MethodWe undertook an umbrella systematic review of systematic reviews and meta-analyses on comorbid physical conditions in people with ASD. Five databases were searched. There were strict inclusion/exclusion criteria. We undertook double reviewing for eligibility, systematic data extraction and quality assessment. Prospective PROSPERO registration: CRD42015020896.ResultsIn total, 24 of 5552 retrieved articles were included, 15 on children, 1 on adults, and 8 both on children and adults. Although the quality of included reviews was good, most reported several limitations in the studies they included and considerable heterogeneity. Comorbid physical conditions are common, and some are more prevalent than in the general population: sleep problems, epilepsy, sensory impairments, atopy, autoimmune disorders and obesity. Asthma is not. However, there are substantial gaps in the evidence base. Fewer studies have been undertaken on other conditions and some findings are inconsistent.ConclusionsComorbid physical conditions occur more commonly in people with ASD, but the evidence base is slim and more research is needed. Some comorbidities compound care if clinicians are unaware, for example sensory impairments, given the communication needs of people with ASD. Others, such as obesity, can lead to an array of other conditions, disadvantages and early mortality. It is essential that potentially modifiable physical conditions are identified to ensure people with ASD achieve their best outcomes. Heightening clinicians’ awareness is important to aid in assessments and differential diagnoses, and to improve healthcare.

scholarly journals Cannabinoids for People with ASD: A Systematic Review of Published and Ongoing Studies

2020 ◽  
Vol 10 (9) ◽  
pp. 572
Author(s):  
Laura Fusar-Poli ◽  
Vito Cavone ◽  
Silvia Tinacci ◽  
Ilaria Concas ◽  
Antonino Petralia ◽  
...  
Keyword(s):  
Systematic Review ◽  
Problem Behaviors ◽  
Cannabis Sativa ◽  
Sleep Problems ◽  
Medical Condition ◽  
Emotional Responses ◽  
Autism Spectrum ◽  
Associated Symptoms ◽  
Common Medical Condition ◽  
Core Symptoms

The etiopathogenesis of autism spectrum disorder (ASD) remains largely unclear. Among other biological hypotheses, researchers have evidenced an imbalance in the endocannabinoid (eCB) system, which regulates some functions typically impaired in ASD, such as emotional responses and social interaction. Additionally, cannabidiol (CBD), the non-intoxicating component of Cannabis sativa, was recently approved for treatment-resistant epilepsy. Epilepsy represents a common medical condition in people with ASD. Additionally, the two conditions share some neuropathological mechanisms, particularly GABAergic dysfunctions. Hence, it was hypothesized that cannabinoids could be useful in improving ASD symptoms. Our systematic review was conducted according to the PRISMA guidelines and aimed to summarize the literature regarding the use of cannabinoids in ASD. After searching in Web of KnowledgeTM, PsycINFO, and Embase, we included ten studies (eight papers and two abstracts). Four ongoing trials were retrieved in ClinicalTrials.gov. The findings were promising, as cannabinoids appeared to improve some ASD-associated symptoms, such as problem behaviors, sleep problems, and hyperactivity, with limited cardiac and metabolic side effects. Conversely, the knowledge of their effects on ASD core symptoms is scarce. Interestingly, cannabinoids generally allowed to reduce the number of prescribed medications and decreased the frequency of seizures in patients with comorbid epilepsy. Mechanisms of action could be linked to the excitatory/inhibitory imbalance found in people with ASD. However, further trials with better characterization and homogenization of samples, and well-defined outcomes should be implemented.

scholarly journals Subjective and Electroencephalographic Sleep Parameters in Children and Adolescents with Autism Spectrum Disorder: A Systematic Review

2021 ◽  
Vol 10 (17) ◽  
pp. 3893
Author(s):  
Maria Giuseppina Petruzzelli ◽  
Emilia Matera ◽  
Donatella Giambersio ◽  
Lucia Marzulli ◽  
Alessandra Gabellone ◽  
...  
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Children And Adolescents ◽  
Sleep Problems ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Subjective Sleep ◽  
Adolescents With Autism ◽  
Sleep Parameters ◽  
Sleep Abnormalities

Background: Sleep problems have commonly manifested in children and adolescents with autism spectrum disorder (ASD) with a complex and multifactorial interaction between clinical and etiological components. These disorders are associated with functional impairment, and provoke significant physical and mental affliction. The purpose of this study is to update the existing literature about objective and subjective sleep parameters in children and adolescents with ASD, extrapolating information from polysomnography or sleep electroencephalography, and sleep related questionnaires. Methods: We have conducted a systematic review of case-control studies on this topic, performing a web-based search on PubMed, Scopus and the Web of Science databases according to the Preferred Reporting items for Systematic Review and Meta-analyses (PRISMA) guidelines. Results: Data collected from 20 survey result reports showed that children and adolescents with ASD experienced a higher rate of sleep abnormalities than in typically developing children. The macrostructural sleep parameters that were consistent with subjective parent reported measures unveil a greater percentage of nighttime signs of insomnia. Sleep microstructure patterns, in addition, pointed towards the bidirectional relationship between brain dysfunctions and sleep problems in children with ASD. Conclusions: Today’s literature acknowledges that objective and subjective sleep difficulties are more often recognized in individuals with ASD, so clinicians should assess sleep quality in the ASD clinical population, taking into consideration the potential implications on treatment strategies. It would be worthwhile in future studies to examine how factors, such as age, cognitive level or ASD severity could be related to ASD sleep abnormalities. Future research should directly assess whether sleep alterations could represent a specific marker for atypical brain development in ASD.

Parent Education in Studies With Nonverbal and Minimally Verbal Participants With Autism Spectrum Disorder: A Systematic Review

2020 ◽  
Vol 29 (2) ◽  
pp. 890-902
Author(s):  
Lynn Kern Koegel ◽  
Katherine M. Bryan ◽  
Pumpki Lei Su ◽  
Mohini Vaidya ◽  
Stephen Camarata
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Parent Education ◽  
Autism Spectrum ◽  
Verbal Communication ◽  
Fidelity Of Implementation ◽  
Spectrum Disorder ◽  
Education Programs ◽  
Minimally Verbal ◽  
Parent Education Programs

Purpose The purpose of this systematic review was to identify parent education procedures implemented in intervention studies focused on expressive verbal communication for nonverbal (NV) or minimally verbal (MV) children with autism spectrum disorder (ASD). Parent education has been shown to be an essential component in the habilitation of individuals with ASD. Parents of individuals with ASD who are NV or MV may particularly benefit from parent education in order to provide opportunities for communication and to support their children across the life span. Method ProQuest databases were searched between the years of 1960 and 2018 to identify articles that targeted verbal communication in MV and NV individuals with ASD. A total of 1,231 were evaluated to assess whether parent education was implemented. We found 36 studies that included a parent education component. These were reviewed with regard to (a) the number of participants and participants' ages, (b) the parent education program provided, (c) the format of the parent education, (d) the duration of the parent education, (e) the measurement of parent education, and (f) the parent fidelity of implementation scores. Results The results of this analysis showed that very few studies have included a parent education component, descriptions of the parent education programs are unclear in most studies, and few studies have scored the parents' implementation of the intervention. Conclusions Currently, there is great variability in parent education programs in regard to participant age, hours provided, fidelity of implementation, format of parent education, and type of treatment used. Suggestions are made to provide both a more comprehensive description and consistent measurement of parent education programs.

Herbal Medicine as an Alternative Treatment in Autism Spectrum Disorder: A Systematic Review

2018 ◽  
Vol 19 (5) ◽  
pp. 454-459 ◽  
Author(s):  
Francielly Mourao Gasparotto ◽  
Francislaine Aparecida dos Reis Lívero ◽  
Sara Emilia Lima Tolouei Menegati ◽  
Arquimedes Gasparotto Junior
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Herbal Medicine ◽  
Alternative Treatment ◽  
Autism Spectrum ◽  
Spectrum Disorder

Diagnostic test accuracy for use of machine learning in diagnosis of autism spectrum disorder: A Systematic Review and Meta-Analysis (Preprint)

2019 ◽  
Author(s):  
Sun Jae Moon ◽  
Jin Seub Hwang ◽  
Rajesh Kana ◽  
John Torous ◽  
Jung Won Kim
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Meta Analysis ◽  
Learning Algorithms ◽  
Structural Mri ◽  
Autism Spectrum ◽  
Machine Learning Algorithms ◽  
Spectrum Disorder ◽  
Test Accuracy

BACKGROUND Over the recent years, machine learning algorithms have been more widely and increasingly applied in biomedical fields. In particular, its application has been drawing more attention in the field of psychiatry, for instance, as diagnostic tests/tools for autism spectrum disorder. However, given its complexity and potential clinical implications, there is ongoing need for further research on its accuracy. OBJECTIVE The current study aims to summarize the evidence for the accuracy of use of machine learning algorithms in diagnosing autism spectrum disorder (ASD) through systematic review and meta-analysis. METHODS MEDLINE, Embase, CINAHL Complete (with OpenDissertations), PsyINFO and IEEE Xplore Digital Library databases were searched on November 28th, 2018. Studies, which used a machine learning algorithm partially or fully in classifying ASD from controls and provided accuracy measures, were included in our analysis. Bivariate random effects model was applied to the pooled data in meta-analysis. Subgroup analysis was used to investigate and resolve the source of heterogeneity between studies. True-positive, false-positive, false negative and true-negative values from individual studies were used to calculate the pooled sensitivity and specificity values, draw SROC curves, and obtain area under the curve (AUC) and partial AUC. RESULTS A total of 43 studies were included for the final analysis, of which meta-analysis was performed on 40 studies (53 samples with 12,128 participants). A structural MRI subgroup meta-analysis (12 samples with 1,776 participants) showed the sensitivity at 0.83 (95% CI-0.76 to 0.89), specificity at 0.84 (95% CI -0.74 to 0.91), and AUC/pAUC at 0.90/0.83. An fMRI/deep neural network (DNN) subgroup meta-analysis (five samples with 1,345 participants) showed the sensitivity at 0.69 (95% CI- 0.62 to 0.75), the specificity at 0.66 (95% CI -0.61 to 0.70), and AUC/pAUC at 0.71/0.67. CONCLUSIONS Machine learning algorithms that used structural MRI features in diagnosis of ASD were shown to have accuracy that is similar to currently used diagnostic tools.

Sign in / Sign up

Export Citation Format

Share Document