Problems managed and medications prescribed during encounters with people with autism spectrum disorder in Australian general practice

Autism ◽  
2017 ◽  
Vol 22 (8) ◽  
pp. 995-1004 ◽  
Author(s):  
Rachael C Birch ◽  
Kitty-Rose Foley ◽  
Allan Pollack ◽  
Helena Britt ◽  
Nicholas Lennox ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Healthcare Providers ◽  
The United States ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Physical And Mental Health ◽  
Prescribing Practices ◽  
Medication Prescription ◽  
Prescription Rates ◽  
Health Programme

Autism spectrum disorder is associated with high rates of co-occurring health conditions. While elevated prescription rates of psychotropic medications have been reported in the United Kingdom and the United States, there is a paucity of research investigating clinical and prescribing practices in Australia. This study describes the problems managed and medications prescribed by general practitioners in Australia during encounters where an autism spectrum disorder was recorded. Information was collected from 2000 to 2014 as part of the Bettering the Evaluation and Care of Health programme. Encounters where patients were aged less than 25 years and autism spectrum disorder was recorded as one of the reasons for encounter and/or problems managed ( n = 579) were compared to all other Bettering the Evaluation and Care of Health programme encounters with patients aged less than 25 years ( n = 281,473). At ‘autism spectrum disorder’ encounters, there was a significantly higher management rate of psychological problems, and significantly lower management rates of skin, respiratory and general/unspecified problems, than at ‘non-autism spectrum disorder’ encounters. The rate of psychological medication prescription was significantly higher at ‘autism spectrum disorder’ encounters than at ‘non-autism spectrum disorder’ encounters. The most common medications prescribed at ‘autism spectrum disorder’ encounters were antipsychotics and antidepressants. Primary healthcare providers need adequate support and training to identify and manage physical and mental health concerns among individuals with autism spectrum disorder.

scholarly journals Genotype-Based Deep Learning in Autism Spectrum Disorder: Diagnostic Classification and Prognostic Prediction Using Common Genetic Variants (Preprint)

2020 ◽  
Author(s):  
Haishuai Wang ◽  
Paul Avillach
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorder ◽  
Deep Learning ◽  
The United States ◽  
Autism Spectrum ◽  
Repetitive Behaviors ◽  
Spectrum Disorder ◽  
Screening Tools ◽  
Common Variants ◽  
Autism Screening

BACKGROUND In the United States, about 3 million people have autism spectrum disorder (ASD), and around 1 out of 59 children are diagnosed with ASD. People with ASD have characteristic social communication deficits and repetitive behaviors. The causes of this disorder remain unknown; however, in up to 25% of cases, a genetic cause can be identified. Detecting ASD as early as possible is desirable because early detection of ASD enables timely interventions in children with ASD. Identification of ASD based on objective pathogenic mutation screening is the major first step toward early intervention and effective treatment of affected children. OBJECTIVE Recent investigation interrogated genomics data for detecting and treating autism disorders, in addition to the conventional clinical interview as a diagnostic test. Since deep neural networks perform better than shallow machine learning models on complex and high-dimensional data, in this study, we sought to apply deep learning to genetic data obtained across thousands of simplex families at risk for ASD to identify contributory mutations and to create an advanced diagnostic classifier for autism screening. METHODS After preprocessing the genomics data from the Simons Simplex Collection, we extracted top ranking common variants that may be protective or pathogenic for autism based on a chi-square test. A convolutional neural network–based diagnostic classifier was then designed using the identified significant common variants to predict autism. The performance was then compared with shallow machine learning–based classifiers and randomly selected common variants. RESULTS The selected contributory common variants were significantly enriched in chromosome X while chromosome Y was also discriminatory in determining the identification of autistic from nonautistic individuals. The ARSD, MAGEB16, and MXRA5 genes had the largest effect in the contributory variants. Thus, screening algorithms were adapted to include these common variants. The deep learning model yielded an area under the receiver operating characteristic curve of 0.955 and an accuracy of 88% for identifying autistic from nonautistic individuals. Our classifier demonstrated a significant improvement over standard autism screening tools by average 13% in terms of classification accuracy. CONCLUSIONS Common variants are informative for autism identification. Our findings also suggest that the deep learning process is a reliable method for distinguishing the diseased group from the control group based on the common variants of autism.

Parental Perceptions of Autism Spectrum Disorder in Latinx and Black Sociocultural Contexts: A Systematic Review

2022 ◽  
Vol 127 (1) ◽  
pp. 42-63
Author(s):  
Karla Rivera-Figueroa ◽  
Nana Yaa A. Marfo ◽  
Inge-Marie Eigsti
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Minority Groups ◽  
Healthcare Providers ◽  
Autism Spectrum ◽  
Parental Perceptions ◽  
Spectrum Disorder ◽  
White Families ◽  
Treatment Services ◽  
Related Stigma

Abstract Parents of children with autism spectrum disorder (ASD) face challenges in accessing diagnostic and treatment services; these challenges vary by race, ethnicity, and culture. This systematic review examines parental perceptions of ASD within Latinx and Black American communities. Findings indicate that interconnections with family and religious groups promoted positive coping and describe positive impacts of having a child with ASD. Relative to White families, community members reported reduced access to information and more inaccurate beliefs about ASD, higher levels of ASD-related stigma, and more negative experiences with healthcare providers, which serve to exacerbate healthcare disparities. Conclusions are limited by an underrepresentation of minority groups in research. We call for efforts to address the specific needs of racial and ethnic minorities.

scholarly journals Pregnant Mothers’ Medical Claims and Associated Risk of Their Children being Diagnosed with Autism Spectrum Disorder

2021 ◽  
Vol 11 (10) ◽  
pp. 950
Author(s):  
Genevieve Grivas ◽  
Richard Frye ◽  
Juergen Hahn
Keyword(s):  
Autism Spectrum Disorder ◽  
First Trimester ◽  
The United States ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Administrative Claims ◽  
Medical Claims ◽  
Increased Risk ◽  
Geographical Regions ◽  
Tract Infections

A retrospective analysis of administrative claims containing a diverse mixture of ages, ethnicities, and geographical regions across the United States was conducted in order to identify medical events that occur during pregnancy and are associated with autism spectrum disorder (ASD). The dataset used in this study is comprised of 123,824 pregnancies of which 1265 resulted in the child being diagnosed with ASD during the first five years of life. Logistic regression analysis revealed significant relationships between several maternal medical claims, made during her pregnancy and segmented by trimester, and the child’s diagnosis of ASD. Having a biological sibling with ASD, maternal use of antidepressant medication and psychiatry services as well as non-pregnancy related claims such hospital visits, surgical procedures, and radiology exposure were related to an increased risk of ASD regardless of trimester. Urinary tract infections during the first trimester and preterm delivery during the second trimester were also related to an increased risk of ASD. Preventative and obstetrical care were associated with a decreased risk for ASD. A better understanding of the medical factors that increase the risk of having a child with ASD can lead to strategies to decrease risk or identify those children who require increased surveillance for the development of ASD to promote early diagnosis and intervention.

scholarly journals Prevalence and Treatment Patterns of Autism Spectrum Disorder in the United States, 2016

2019 ◽  
Vol 173 (2) ◽  
pp. 153 ◽  
Author(s):  
Guifeng Xu ◽  
Lane Strathearn ◽  
Buyun Liu ◽  
Matthew O’Brien ◽  
Todd G. Kopelman ◽  
...  
Keyword(s):  
United States ◽  
Autism Spectrum Disorder ◽  
The United States ◽  
Autism Spectrum ◽  
Treatment Patterns ◽  
Spectrum Disorder

scholarly journals To raise a child with autism spectrum disorder: A qualitative, comparative study of parental experiences in the United States and Senegal

2020 ◽  
pp. 136346152095334
Author(s):  
Adair Cardon ◽  
Tara Marshall
Keyword(s):  
Autism Spectrum Disorder ◽  
Community Support ◽  
The United States ◽  
Autism Spectrum ◽  
Cross Cultural ◽  
Spectrum Disorder ◽  
Cultural Perspective ◽  
Structured Interviews ◽  
Parental Experiences ◽  
American Families

Raising a child with Autism Spectrum Disorder (ASD) can often be a difficult and stressful process for families and caregivers. Though research on ASDs in Africa is burgeoning, very little is known about autism in francophone West Africa. Furthermore, no known ASD studies have explored parental experiences in particular from a cross-cultural perspective. This research used Interpretative Phenomenological Analysis to analyze in-depth, semi-structured interviews with seven Senegalese and seven American families to investigate parental experiences within the Senegalese community with further illustration by cross-cultural comparison. Comparative analysis of data across the two countries was undertaken to identify cultural variables previously unreported, especially those that may affect Senegalese family experience. Analysis of interviews revealed thematic differences in social and community support. Although access to effective treatment services was low among Senegalese families compared to the American families, traditional Senegalese household structures and community relations were hypothesized to serve as protective factors against the high social isolation and resulting logistical struggles reported in the U.S. sample. Further targeted research within the Senegalese environment is recommended, particularly to explore social stigma and its possible effects on families with autism, causal beliefs and treatment practices, and parental mental health and wellbeing.

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