Algorithm for expert rehabilitation assessment of autism syndrome in children
- Authors: Chistyakova N.P.1,2, Litvintsev S.V.1, Travnikova N.G.1
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Affiliations:
- Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation named after G.A. Albrecht
- The Main Bureau of Medical and Social Expertise for Saint Petersburg
- Issue: Vol 26, No 2 (2023)
- Pages: 65-73
- Section: ORIGINAL STUDY ARTICLE
- URL: https://journal-vniispk.ru/1560-9537/article/view/232118
- DOI: https://doi.org/10.17816/MSER472075
- ID: 232118
Cite item
Abstract
BACKGROUND: Despite the long-applied international classifications of diseases and disorders, in our country, no approved methodology has been approved for a comprehensive assessment of autism syndrome, considering categorical and dimensional approaches, age of the child, and polymorphism of symptomatology, which creates significant difficulties in diagnosis, determining the complex of rehabilitation measures, and assessing their effectiveness.
AIMS: To develop an algorithm for the expert rehabilitation diagnosis of autism spectrum disorders (ASDs) in children with disabilities according to the domains of the International Classification of Functioning, Disability, and Health (ICF).
MATERIALS AND METHODS: The study enrolled children recognized to have a disability for the first time due to autism in the St. Petersburg and Voronezh regions for 2016–2021. Data sources included state statistical reporting forms 7-D (sobes), acts and protocols of examinations, statistical maps, and data obtained from the Federal State Information System “Unified Automated Vertical Integrated Information and Analytical System”. The study is longitudinal and continuous. Analytical, documentary, data excavation, questionnaires, interviewing, statistical methods of research were employed. The methodology of the World Health Organization was used to study the functional profile according to the basic set for children with autism.
RESULTS: Data on functioning and life activity limitations of children with autism-related disability were analyzed taking into account the clinical form of autism, age of the child (0–3, 4–7, 8–14, and 15–17 years), and presence of comorbid symptomatology according to the ICD-10 criteria (1992) and IFC domains (2001). The main predictors of the severity of autism manifestations were identified depending on the age of the child: 0–3 years, rates of psychomotor and speech development in epicrisis terms; 4–17 years, degree of deficit of social communication/social interaction; and assessment of limited stereotypical forms of behavior. In children aged >3 years, comorbid symptomatology was also assessed, taking into account the use of psychometric scales and research methods approved in the Russian Federation. Predictors of autism severity were translated into expertly significant domains of the basic set of the ICF for ASDs. Quantitative assessment was performed in a unified format using ICF qualifiers comparable to the system of quantitative assessment adopted in medical and social expertise.
CONCLUSIONS: The results of the study allowed us to converge international and domestic standards of assessment of impaired functions and limitations of life activity in autism using the order of the Ministry of Labor of Russia № 585n as a ranking tool to translate the data on the functioning and life activity limitations of children with disability into the ICF determinants. The developed algorithm for expert rehabilitation diagnostics of autism syndrome is an important criterion for expert diagnostics, determining complex rehabilitation measures and evaluating the effectiveness of rehabilitation measures.
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##article.viewOnOriginalSite##About the authors
Natalia P. Chistyakova
Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation named after G.A. Albrecht; The Main Bureau of Medical and Social Expertise for Saint Petersburg
Author for correspondence.
Email: npch74@mail.ru
ORCID iD: 0000-0002-7841-0953
assistant professor
Russian Federation, Saint Petersburg; Saint PetersburgSergey V. Litvintsev
Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation named after G.A. Albrecht
Email: sergejlitvincev@yandex.ru
ORCID iD: 0000-0002-1046-287X
md, dr. sci. (med.), professor
Russian Federation, St. PetersburgNika G. Travnikova
Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation named after G.A. Albrecht
Email: travnika@yandex.ru
ORCID iD: 0000-0001-8410-6360
cand. sci. (psychol.), assistant professor
Russian Federation, St. PetersburgReferences
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