Autism Spectrum Disorder In Infants Research Articles

Early autism diagnosis based on path signature and Siamese unsupervised feature compressor.

Autism spectrum disorder has been emerging as a growing public health threat. Early diagnosis of autism spectrum disorder is crucial for timely, effective intervention and treatment. However, conventional diagnosis methods based on communications and behavioral patterns are unreliable for children younger than 2 years of age. Given evidences of neurodevelopmental abnormalities in autism spectrum disorder infants, we resort to a novel deep learning-based method to extract key features from the inherently scarce, class-imbalanced, and heterogeneous structural MR images for early autism diagnosis. Specifically, we propose a Siamese verification framework to extend the scarce data, and an unsupervised compressor to alleviate data imbalance by extracting key features. We also proposed weight constraints to cope with sample heterogeneity by giving different samples different voting weights during validation, and used Path Signature to unravel meaningful developmental features from the two-time point data longitudinally. We further extracted machine learning focused brain regions for autism diagnosis. Extensive experiments have shown that our method performed well under practical scenarios, transcending existing machine learning methods and providing anatomical insights for autism early diagnosis.

Enigma of the Developmental Causes in Individuals with Autism Spectrum Disorder (ASD)

Autism Spectrum Disorder (ASD) is a neurobiological developmental condition that can impact communication, sensory processing, and social interaction. ASD) is a developmental disability that can cause significant social, communication and behavioral challenges. For a long time now, the scientific community has been grappling with the enigma of what causes the developmental deficits in people on the autism spectrum, the causes of the ASD symptoms, and the timing of the manifestation of ASD in infants that occurs on or after 6 months. Several research studies show that the main cause of autism appears on account of the enlargement of the brain, specifically the amygdala, which could lead to communication and physical deficits, as well as sensory and light sensitivity. The research on the causes for ASD is still at the nascent stage as there are still many unanswered questions including about the causes of ASD. It appears that few if any ASD Research studies have a representative sampling for gender and the majority of research focuses on male individuals with ASD. This literature review reveals that more research is required to bridge the gaps in our understanding of ASD . The enigma of the developmental causes in individuals with Autism Spectrum Disorder continues to be of interest to the scientific community and there is potential for further research regarding factors for pre-onset of ASD.

Prediction of autistic tendencies at 18 months of age via markerless video analysis of spontaneous body movements in 4-month-old infants

Early intervention is now considered the core treatment strategy for autism spectrum disorders (ASD). Thus, it is of significant clinical importance to establish a screening tool for the early detection of ASD in infants. To achieve this goal, in a longitudinal design, we analyzed spontaneous bodily movements of 4-month-old infants from general population and assessed their ASD-like behaviors at 18 months of age. A total of 26 movement features were calculated from video-recorded bodily movements of infants at 4 months of age. Their risk of ASD was assessed at 18 months of age with the Modified Checklist for Autism in Toddlerhood, a widely used screening questionnaire. Infants at high risk for ASD at 18 months of age exhibited less rhythmic and weaker bodily movement patterns at 4 months of age than low-risk infants. When the observed bodily movement patterns were submitted to a machine learning-based analysis, linear and non-linear classifiers successfully predicted ASD-like behavior at 18 months of age based on the bodily movement patterns at 4 months of age, at the level acceptable for practical use. This study analyzed the relationship between spontaneous bodily movements at 4 months of age and the ASD risk at 18 months of age. Experimental results suggested the utility of the proposed method for the early screening of infants at risk for ASD. We revealed that the signs of ASD risk could be detected as early as 4 months after birth, by focusing on the infant’s spontaneous bodily movements.

Influencing factors and intervention therapy of the Autism Spectrum Disorder (ASD)

Autism spectrum disorder (ASD) is a kind of the disorder which is characterized by continuous social interaction and communication disorders, narrow interests and repetitive stereotyped behaviors are the main core symptoms of neurodevelopmental disorders. At the same time, the incidence of the disease increases rapidly and is extremely harmful, which brings huge economic burden to families and society. Therefore, early identification and early intervention are urgently needed. At present, the pathogenesis of ASD is not clear, and there is no perfect diagnostic tools and methods. So far, scholars are still exploring the etiology and pathogenesis of ASD. In the past, researchers have paid attention to the study of twins and found that the prevalence of monozygotic twins is higher than that of dizygotic twins, so as to try to explain the ASD from a genetic perspective.Academic circles generally believe that ASD is caused by the joint action of genetics and environment. In order to find the objective indicators of early recognition of ASD individuals, researchers have actively carried out research on ASD infants, such as twins, the overall processing of isolated faces,event-related potentials (ERP) and other monitoring methods. Traditional ASD psychotherapy mostly focuses on behavioral rehabilitation training, supplemented by some drug treatment.Advanced spatial information technology has certain advantages and potentials for the treatment of autism spectrum disorders.However, at present, the research in this field is relatively scattered and cannot be popularized.

Incidence and risk factors for autism spectrum disorder among infants born

This study was aimed to assess the incidence of and risk factors for autism spectrum disorder (ASD) among preterm infants born <29 weeks' gestational age (GA). A retrospective cohort study of infants born <29 weeks' GA admitted to two tertiary neonatal intensive care units (2009 to 2017) and followed ≥18 months corrected age (CA) at a neonatal follow-up clinic. The primary outcome was ASD, diagnosed using standardized testing or provisional diagnosis at ≥18 months CA. Patient data and 18-month CA developmental outcomes were obtained from the local Canadian Neonatal Follow Up Network database and chart review. Stepwise logistic regression assessed factors associated with ASD. Among 300 eligible infants, 26 (8.7%) were diagnosed with confirmed and 21 (7.0%) with provisional ASD for a combined incidence of 15.7% (95% confidence interval [CI] 11.7 to 20.3). The mean follow-up duration was 3.9 ± 1.4 years and the mean age of diagnosis was 3.7 ± 1.5 years. Male sex (adjusted odds ratio [aOR] 4.63, 95% CI 2.12 to 10.10), small for gestational age status (aOR 3.03, 95% CI 1.02 to 9.01), maternal age ≥35 years at delivery (aOR 2.22, 95% CI 1.08 to 4.57) and smoking during pregnancy (aOR 5.67, 95% CI 1.86 to 17.29) were significantly associated with ASD. Among ASD infants with a complete 18-month CA developmental assessment, 46% (19/41) had no neurodevelopmental impairment (Bayley-III<70, deafness, blindness, or cerebral palsy). ASD is common among infants born <29 weeks' GA and possibly associated with identified risk factors. Such findings emphasize the importance of ASD evaluation among infants <29 weeks' GA and for continued reporting of developmental outcomes beyond 18-months of corrected age.

Association of physical activity and sleep habits during pregnancy with autistic spectrum disorder in 3-year-old infants

Background:We hypothesized that maternal lifestyle factors, such as physical activity and sleep habits, may be associated with autism spectrum disorder (ASD) in infants. This study aimed to investigate the association between maternal physical activity and sleep before and during pregnancy with infant ASD diagnosed by the age of 3 years.Methods:We used the data from the Japan Environment and Children’s Study between 2011 and 2014. The study included 103,060 pregnant women, among which, 69,969 women were analyzed. Participants were asked about their physical activity and sleep before and during pregnancy using questionnaires during pregnancy. Maternal physical activity was estimated using the international physical activity questionnaire. Based on the levels of physical activity before or during pregnancy, the participants were divided into five groups. Maternal sleep was analyzed based on sleep duration and bedtime. The outcome was diagnosis of ASD in 3-year-old infants.Results:In mothers with higher physical activity levels during pregnancy, the risk ratios (RR) for ASD in their 3-year-old infants were lower (RR = 0.61, 95% confidence interval (CI) = 0.42–0.90). In contrast, too short (<6 h) and too long (>10 h) sleep durations during pregnancy were associated with higher risk ratios for ASD than 7–8 h sleep duration (too short: RR = 1.87, 95% CI = 1.21–2.90; too long: RR = 1.56, 95% CI = 1.00–2.48). These associations were not observed before pregnancy.Conclusion:Maternal physical activity and sleep duration during pregnancy may be associated with ASD in infants.

The Vocabulary of Infants with an Elevated Likelihood and Diagnosis of Autism Spectrum Disorder: A Systematic Review and Meta-Analysis of Infant Language Studies Using the CDI and MSEL.

Diagnoses of autism spectrum disorder (ASD) are typically accompanied by atypical language development, which can be noticeable even before diagnosis. The siblings of children diagnosed with ASD are at elevated likelihood for ASD diagnosis and have been shown to have higher prevalence rates than the general population. In this paper, we systematically reviewed studies looking at the vocabulary size and development of infants with autism. One inclusion criterion was that infants were grouped either pre-diagnostically as elevated or typical likelihood or post-diagnostically as ASD or without ASD. This review focused on studies that tested infants up to 24 months of age and that assessed vocabulary either via the parent-completed MacArthur–Bates Communicative Developmental Inventory (CDI) or the clinician-administered Mullen Scales of Early Learning (MSEL). Our systematic search yielded 76 studies. A meta-analysis was performed on these studies that compared the vocabulary scores of EL and TL infants pre-diagnostically and the scores of ASD and non-ASD infants post-diagnostically. Both pre- and post-diagnostically, it was found that the EL and ASD infants had smaller vocabularies than their TL and non-ASD peers, respectively. The effect sizes across studies were heterogenous, prompting additional moderator analyses of age and sub-group analyses of the language measure used (CDI or MSEL) as potential moderators of the effect size. Age was found to be a moderator both in the pre- and post-diagnostical groups, however, language measure was not a moderator in either diagnostic group. Interpretations and future research directions are discussed based on these findings.

What are you looking at? Gaze following with and without target objects in ASD and typical development.

Children with autism spectrum disorder (ASD) display difficulties with response to joint attention in natural settings but often perform comparably to typically developing (TD) children in experimental studies of gaze following. Previous work comparing infants at elevated likelihood for ASD versus TD infants has manipulated aspects of the gaze cueing stimulus (e.g. eyes only versus head and eyes together), but the role the peripheral object being attended to is not known. In this study of infants at elevated likelihood of ASD (N = 97) and TD infants (N = 29), we manipulated whether or not a target object was present in the cued area. Performance was assessed at 10, 14, and 18 months, and diagnostic assessment was conducted at age 3 years. The results showed that although infants with later ASD followed gaze to the same extent as TD infants in all conditions, they displayed faster latencies back to the model’s face when (and only when) a peripheral object was absent. These subtle atypicalities in the gaze behaviors directly after gaze following may implicate a different appreciation of the communicative situation in infants with later ASD, despite their ostensively typical gaze following ability.Lay abstractDuring the first year of life, infants start to align their attention with that of other people. This ability is called joint attention and facilitates social learning and language development. Although children with autism spectrum disorder (ASD) are known to engage less in joint attention compared to other children, several experimental studies have shown that they follow other’s gaze (a requirement for visual joint attention) to the same extent as other children. In this study, infants’ eye movements were measured at age 10, 14, and 18 months while watching another person look in a certain direction. A target object was either present or absent in the direction of the other person’s gaze. Some of the infants were at elevated likelihood of ASD, due to having an older autistic sibling. At age 3 years, infants were assessed for a diagnosis of ASD. Results showed that infants who met diagnostic criteria at 3 years followed gaze to the same extent as other infants. However, they then looked back at the model faster than typically developing infants when no target object was present. When a target object was present, there was no difference between groups. These results may be in line with the view that directly after gaze following, infants with later ASD are less influenced by other people’s gaze when processing the common attentional focus. The study adds to our understanding of both the similarities and differences in looking behaviors between infants who later receive an ASD diagnosis and other infants.

Расстройства аутистического спектра у детей раннего возраста: эволюция взглядов и возможности диагностики (часть 2)

В статье на основе анализа современной научной литературы представлены данные об этиологии, патогенезе, клинических особенностях расстройств аутистического спектра (РАС) у детей раннего возраста. Приведен исторический экскурс относительно эволюции взглядов на РАС от древнейших времен до современности. Первые описания лиц, которые, вероятно, имели клинические проявления РАС, приводятся в средневековых церковных хрониках, житиях святых, а также православных юродивых и биографиях так называемых детей из леса. В отечественной психиатрии проблему аутистических нарушений контакта у детей разрабатывала Г.Е. Сухарева в начале ХХ века. Современные научные представления о РАС заложены в работах Лео Каннера, Ганса Аспергера и Лорны Винг, которые впервые разработали диагностические критерии различных форм расстройства. РАС на сегодня рассматривается как результат взаимодействия генетических факторов с факторами окружающей среды. Влияние факторов окружающей среды может приводить к серьезным нарушениям развития головного мозга, в частности негативно влиять на дифференциацию нейронов, синаптогенез и аксональную миелинизацию. На данном этапе развития научных взглядов на РАС у детей бесспорным является связь расстройств с эпилептическими энцефалопатиями, которые в основном имеют генетическую этиологию. Ввиду наличия общих генетических мутаций, вызывающих РАС и эпилептические энцефалопатии, всем детям с РАС с неустановленной этиологией расстройства показано генетическое тестирование с применением метода секвенирования нового поколения (NGS) на панели генов, связанных с эпилептическими энцефалопатиями, а также проведение ЭЭГ-мониторинга во время ночного сна. Разработанные схемы диагностики позволяют своевременно установить диагноз эпилептической энцефалопатии у детей с расстройствами аутистического спектра и назначить патогенетическое лечение с использованием препаратов нейрометаболического и нейропротекторного действия, а также антиконвульсантов.

Расстройства аутистического спектра у детей раннего возраста: эволюция взглядов и возможности диагностики (часть 1)

В статье на основе анализа современной научной литературы представлены данные об этиологии, патогенезе, клинических особенностях расстройств аутистического спектра (РАС) у детей раннего возраста. Приведен исторический экскурс относительно эволюции взглядов на РАС от древнейших времен до современности. Первые описания лиц, которые, вероятно, имели клинические проявления РАС, приводятся в средневековых церковных хрониках, житиях святых, а также православных юродивых и биографиях так называемых детей из леса. В отечественной психиатрии проблему аутистических нарушений контакта у детей разрабатывала Г.Е. Сухарева в начале ХХ века. Современные научные представления о РАС заложены в работах Лео Каннера, Ганса Аспергера и Лорны Винг, которые впервые разработали диагностические критерии различных форм расстройства. РАС на сегодня рассматривается как результат взаимодействия генетических факторов с факторами окружающей среды. Влияние факторов окружающей среды может приводить к серьезным нарушениям развития головного мозга, в частности негативно влиять на дифференциацию нейронов, синаптогенез и аксональную миелинизацию. На данном этапе развития научных взглядов на РАС у детей бесспорным является связь расстройств с эпилептическими энцефалопатиями, которые в основном имеют генетическую этиологию. Ввиду наличия общих генетических мутаций, вызывающих РАС и эпилептические энцефалопатии, всем детям с РАС с неустановленной этиологией расстройства показано генетическое тестирование с применением метода секвенирования нового поколения (NGS) на панели генов, связанных с эпилептическими энцефалопатиями, а также проведение ЭЭГ-мониторинга во время ночного сна. Разработанные схемы диагностики позволяют своевременно установить диагноз эпилептической энцефалопатии у детей с расстройствами аутистического спектра и назначить патогенетическое лечение с использованием препаратов нейрометаболического и нейропротекторного действия, а также антиконвульсантов.

Food for Thought: Machine Learning in Autism Spectrum Disorder Screening of Infants.

Diagnoses of autism spectrum disorders (ASD) are typically made after toddlerhood by examining behavioural patterns. Earlier identification of ASD enables earlier intervention and better outcomes. Machine learning provides a data-driven approach of diagnosing autism at an earlier age. This review aims to summarize recent studies and technologies utilizing machine learning based strategies to screen infants and children under the age of 18 months for ASD, and identify gaps that can be addressed in the future. We reviewed nine studies based on our search criteria, which includes primary studies and technologies conducted within the last 10 years that examine children with ASD or at high risk of ASD with a mean age of less than 18 months old. The studies must use machine learning analysis of behavioural features of ASD as major methodology. A total of nine studies were reviewed, of which the sensitivity ranges from 60.7% to 95.6%, the specificity ranges from 50% to 100%, and the accuracy ranges from 60.9% to 97.7%. Factors that contribute to the inconsistent findings include the varied presentation of ASD among patients and study design differences. Previous studies have shown moderate accuracy, sensitivity and specificity in the differentiation of ASD and non-ASD individuals under the age of 18 months. The application of machine learning and artificial intelligence in the screening of ASD in infants is still in its infancy, as observed by the granularity of data available for review. As such, much work needs to be done before the aforementioned technologies can be applied into clinical practice to facilitate early screening of ASD.

Diagnosis of Autism Spectrum Disorders in Infants: A Review on Predictors, Early Markers, and Diagnostic Tests

Background: According to estimates by the World Health Organization and the CDC’s Autism and Developmental Disabilities Monitoring (ADDM) Network, the prevalence of Autistic Spectrum Disorder (ASD) has increased significantly in recent decades, reaching today approximately 1 in every 68 children. Objective: The aim of this study was to identify the state of knowledge regarding markers, predictors, and early diagnosis of ASD (0-23 months of age). Method: A search was conducted for articles published in the PubMed Central: PMC scientific literature database, using the “autism spectrum disorder” and “early diagnosis” search algorithms. The following inclusion criteria were observed: articles describing predictors and early markers, and methods of diagnosis of ASD in infants. Results: A total of 65 documents were considered eligible and submitted to the full text review, of which 42 met the inclusion criteria: 16 with predictors, 9 with early markers and 16 with diagnostic tests for ASD. Conclusion: There is still a need to strengthen evidence for the clinical practice of ASD diagnosis by two years of age. The findings of this study regarding predictors, early markers and diagnostic tests are intended to facilitate the detection and early intervention in these patients by health professionals.

Autism risk in neonatal intensive care unit patients associated with novel heart rate patterns.

Background:Neonatal Intensive Care Unit (NICU) patients are at increased risk for autism spectrum disorder (ASD). Autonomic nervous system aberrancy has been described in children with ASD, and we aimed to identify heart rate (HR) patterns in NICU patients associated with eventual ASD diagnosis.Methods:This retrospective cohort study included NICU patients from 2009-2016 with archived HR data and follow-up beyond age 3 years. Medical records provided clinical variables and ASD diagnosis. HR data were compared in infants with and without ASD.Results:Of 2371 patients, 88 had ASD, and 689,016 hours of data were analyzed. HR skewness (HRskw) was significantly different between ASD and control infants. Preterm infants at early postmenstrual ages (PMA) had negative HRskw reflecting decelerations, which increased with maturation. From 34-42 weeks PMA, positive HRskw toward accelerations was higher in males with ASD. In 931 males with at least 4 days of HR data, overall ASD prevalence was 5%, whereas 11% in the top 5th HRskw percentile had ASD.Conclusion:High HRskw in NICU males, perhaps representing autonomic imbalance, was associated with increased ASD risk. Further study is needed to determine whether HR analysis identifies highest risk infants who might benefit from earlier screening and therapies.

Psychometric evaluation of an Arabic Red Flag Screening Checklist of autism spectrum disorders in infants and toddlers

BackgroundAlthough autism spectrum disorder (ASD) is increasing around the world, the interest in developing and validating screening instruments in the Arab countries is still in the initial stage. The current study examined psychometric properties of a unidimensional 14-item screening tool that was developed in Qatar to identify ASD infants and toddlers between the ages of 15 and 33 months. MethodsRash analysis was carried out on a sample of 22,307 records of children who were screened by this instrument. The analysis was done for two age groups: 15–24 months, and 25–33 months, and across two administration modes: paper and pencil, and electronic modes. ResultsThe findings of the current study showed mixed results: some scale properties were good, whereas others were poor. Almost all 12 items retained for the final form showed acceptable values for the infit and outfit statistics and fulfilled the assumptions of local independence and unidimensionality for the two groups of children and across the two administration modes. However, reliability and separation for persons and items, and targeting of items to children along the autistic trait were not acceptable. Moreover, low sensitivity and specificity asserted that ASD was not accurately identified in children. ConclusionsThe findings of the current study identified weaknesses in three areas: the small number of items used to measure the autistic trait, the small number of response categories within each item, and the low sensitivity and specificity of the instrument. Suggestions were provided to address these weaknesses.

Autism spectrum disorders in extremely preterm infants and placental pathology findings: a matched case-control study.

The prevalence of autism spectrum disorders (ASD) is 5-fold higher in preterm (PT) infants born ≤28 weeks gestational age (GA) as compared to the general population. The relationship between placental pathologic lesions and ASD in PT infants has not been studied. The objective of this study was to determine the association of placental pathology with the occurrence of ASD in PT infants born ≤28 weeks GA. A matched case-control study to identify confirmed ASD cases (n = 16) and matched controls (n = 48) born at Parkland Hospital between January 2012 and December 2015. Patients were matched using known variables associated with increased risk of ASD in PT infants. Placental histology from all births was reviewed. Children with ASD had 2-fold greater incidence of multiple placental pathologic lesions vs. matched controls [11/16 (69%) vs.16/48 (33%), respectively; P = 0.01]. In contrast, single placental pathologic lesions were not associated with ASD [5/16 (31%) vs. 21/48 (43%), respectively; P = 0.1]. In this study, we have demonstrated an association between the increasing complexity of histologic placental lesions and the later risk for ASD in infants born ≤28 weeks GA. Thus, placental pathology findings may be valuable in further understanding the prenatal pathologic processes underlying ASD in PT infants. PT infants with ASD have a 2-fold greater incidence of multiple placental pathologies. This is the first study to report an association between the complexity of histologic placental lesions and later risk of ASD in infant born extremely PT (i.e., ≤28 weeks GA). This study reiterates the importance of examining placental pathologic lesions, since placental evidence of antenatal insults correlates with postnatal morbidities and mortality in PT infants.

Application of the Still-Face Paradigm in Early Screening for High-Risk Autism Spectrum Disorder in Infants and Toddlers.

Background: Although autism spectrum disorder (ASD) can currently be diagnosed at the age of 2 years, age at ASD diagnosis is still 40 months or even later. In order to early screening for ASD with more objective method, behavioral videos were used in a number of studies in recent years.Method: The still-face paradigm (SFP) was adopted to measure the frequency and duration of non-social smiling, protest behavior, eye contact, social smiling, and active social engagement in high-risk ASD group (HR) and typical development group (TD) (HR: n = 45; TD: n = 43). The HR group was follow-up until they were 2 years old to confirm final diagnosis. Machine learning methods were used to establish models for early screening of ASD.Results: During the face-to-face interaction (FF) episode of the SFP, there were statistically significant differences in the duration and frequency of eye contact, social smiling, and active social engagement between the two groups. During the still-face (SF) episode, there were statistically significant differences in the duration and frequency of eye contact and active social engagement between the two groups. The 45 children in the HR group were reclassified into two groups after follow-up: five children in the N-ASD group who were not meet the criterion of ASD and 40 children in the ASD group. The results showed that the accuracy of Support Vector Machine (SVM) classification was 83.35% for the SF episode.Conclusion: The use of the social behavior indicator of the SFP for a child with HR before 2 years old can effectively predict the clinical diagnosis of the child at the age of 2 years. The screening model constructed using SVM based on the SF episode of the SFP was the best. This also proves that the SFP has certain value in high-risk autism spectrum disorder screening. In addition, because of its convenient, it can provide a self-screening mode for use at home.Trial registration: Chinese Clinical Trial Registry, ChiCTR-OPC-17011995.

Development and Validity of Behavior Development Screening for Toddlers-Questionnaire/Parents(BeDevel-Q/P)

본 연구는 9~47개월 영유아를 대상으로 자폐스펙트럼장애 위험군을 선별하기 위한 부모 보고용 설문 검사인 걸음마기 아동 행동 발달 선별 척도-부모용 설문지(BeDevel-Q/P:Behavior Development Screening for Toddlers-Questionnaire/ Parents)를 개발하고 타당화하였다. 국내외 문헌 연구와 국내 자폐스펙트럼장애 영유아 및 부모 대상 자료를 토대로 예비 문항 505개를 개발하였다. 자폐스펙트럼장애 관련 다학제 전문가의 내용타당도 검증, 영유아 자폐스펙트럼장애 자녀를 둔 부모 대상 안면타당도 검증과 예비 조사를 거쳐 51개 예비 문항을 추출하였다. 이후 예비 조사(총 289명, 이 중 일반발달 196명, 자폐스펙트럼장애 43명, 발달지연 51명)와 본 조사(총 2,273명, 이 중 일반발달 1,918명, 자폐스펙트럼장애 221명, 발달지연 134명)를 실시하였다. 그 결과 월령대가 9∼11개월, 12∼23개월, 24∼35개월, 36∼47개월로 구분되고, 월령별로 10∼28개 문항이 개발되었으며, 3개의 하위요인이 도출되었다. BeDevel-Q/P와 M-CHAT, Q-CHAT-10, ADOS-2, K-CARS, CBCL 1.5-5의 전반적 발달문제 척도, BITSEA의 자폐증 선별에 민감한 문항, K-DST의 사회성 영역과의 상관분석 및 자폐스펙트럼장애 집단, 발달지연 집단, 일반발달 집단간 차이 분석을 활용하여 BeDevel-Q/P의 타당도를 검증하였고, 본 척도는 받아들일 만한 수준(acceptable level)의 타당도를 보였다. BeDevel-Q/P의 민감도(78.5∼84.0%), 특이도(81.0∼82.0%), 문항 내적 일치도(Cronbach’s α=.85∼.88), 검사-재검사신뢰도(r=.712∼.980)에서도 높은 수준의 결과를 나타냈다. 끝으로 본 연구의 의의와 제한점 및 후속 연구 방향을 기술하였다.This study developed and validified the Behavior Development Screening for Toddlers-Questionnaire/ Parents (BeDevel-Q/P), an autism spectrum disorder (ASD) screening instrument. This assessment serves the purpose of parental reports for early screening of ASD on infants aged 9-47 months. 565 preliminary questionnaires were generated based on prior studies of ASD infants and parents. After Context Validity tests of interdisciplinary ASD experts, Face Validity tests of parents with ASD children, and preliminary research, 51 questionnaires were created. Pilot tests were conducted on a total of 289 people (N = 196 typical development, N = 43 ASD, N = 51 developmentally delayed). A total of 2273 participants were tested N = 1918 typical development, N = 221 ASD, N = 134 developmentally delayed). The results showed a line between age ranges of 9-11 months, 12-23 months, 24-35 months and 36-47 months. Each age ranges consisted of 10-28 questionnaires and 3 subfactors. BeDevel-Q/P validity was tested by the general developmental criterion of BeDevel-Q/P, M-CHAT, Q-CHAT-10, ADOS-2, K-CARS and CBCL 1.5-5 DSM pervasive developmental problems. Autism items from BITSEA were also employed and correlation analysis was performed on sociability items from K-DST, and general differentiation factors between ASD, developmental delayed, and normal groups were also considered. Results showed a reasonable level of acceptability. BeDevel-Q/P showed high sensitivity (78.5-84.0%), specificity (81.0-82.0%), high internal consistency (Cronbach’s α=0.85-88) as well as high test-retest reliability (r=0.712-980). Lastly, the significance and limitations of this study and directions for future research is suggested.

Predicting Autism Spectrum Disorder in Infants Using Machine Learning

Machine Learning techniques have played an important role in identifying patterns, grouping similar objects together and modelling data. These techniques learn from the given data and are capable of making prediction of outcomes for new datasets. In applications where the data is too large and cannot be manually analysed, applying machine learning techniques has helped in automation of many process. This has but, not been done often and hardly ever been done for ASD and developing a decision support system that helps physicians with the detection of ASD, has scarcely been done, that is tried by the shortage of literature on the utilization of it.

Early Clinical Predictors of Autism Spectrum Disorder in Infants with Tuberous Sclerosis Complex: Results from the EPISTOP Study.

Autism spectrum disorder (ASD) is highly prevalent in subjects with Tuberous Sclerosis Complex (TSC), but we are not still able to reliably predict which infants will develop ASD. This study aimed to identify the early clinical markers of ASD and/or developmental delay (DD) in infants with an early diagnosis of TSC. We prospectively evaluated 82 infants with TSC (6–24 months of age), using a detailed neuropsychological assessment (Bayley Scales of Infant Development—BSID, and Autism Diagnostic Observation Schedule—ADOS), in the context of the EPISTOP (Long-term, prospective study evaluating clinical and molecular biomarkers of EPIleptogenesiS in a genetic model of epilepsy—Tuberous SclerOsis ComPlex) project (NCT02098759). Normal cognitive developmental quotient at 12 months excluded subsequent ASD (negative predictive value 100%). The total score of ADOS at 12 months clearly differentiated children with a future diagnosis of ASD from children without (p = 0.012). Atypical socio-communication behaviors (p < 0.001) were more frequently observed than stereotyped/repetitive behaviors in children with ASD at 24 months. The combined use of BSID and ADOS can reliably identify infants with TSC with a higher risk for ASD at age 6–12 months, allowing for clinicians to target the earliest symptoms of abnormal neurodevelopment with tailored intervention strategies.

Application of response to name in early identification of infants with autism spectrum disorders

Objective To explore the behavioral characteristics of response to name in 16-30 months old infants with autism spectrum disorders (ASD), in order to provide a theoretical basis for the early identification and early diagnosis. Methods Two professionals, according to the scoring criteria and using video analysis methods, evaluated the response score (RS), reaction time (RT), duration time (DT) and the rate (RR) of response to their names among ASD infants (ASD group, 61 cases), who were diagnosed at Child Developmental and Behavioral Center, the Third Affiliated Hospital of Sun Yat-Sen University from April to December 2017.Then they were compared with infants with developmental delays (DD group, 32 cases) and neuro-typical (NT group, 33 cases) infants.Finally, researchers predicted the diagnosis for ASD infants according to the behavioral indicators, which had significant diffe-rences compared with other groups. Results Compared with DD group [RS 2(1) score, RT 1.32(4.65) s, DT 2.69(1.84) s] and NT group[RS 2(1) score, RT 1.37(4.37) s, DT 2.90(2.23) s], RS was significantly lower[1(1) score], RT was significantly longer [5.87(4.64) s], and DT was significantly shorter [0.77 (1.88) s]in ASD group, and the differences were statistically significant(H=-4.91, -5.94; 5.36, 5.41; -4.47, -5.78; all P 0.05). The RR was significantly lower in ASD group [0.25(0.50)]and DD group[0.50(0.25)], compared with NT group[0.75(0.50)], and the differences were statistically significant(H=-6.39, -4.45, all P 0.05). When detecting ASD from ASD and NT infants, the area under the receiver operating characteristic curve (AUC) was 0.889 (P<0.01); when detecting ASD from ASD and DD infants, AUC was 0.924 (P<0.01); when detecting ASD from all infants, AUC was 0.868 (P<0.01), according to all indicators of response to name. Conclusions There are significant differences between ASD infants and DD and NT infants in response to name domain.Behavioral characteristics in the procedure of response to name can predict ASD well.Response to name as an early social behavioral indicator, being tested at 2 years old, is still of importance for the early identification and early diagnosis of ASD. Key words: Autism spectrum disorder; Developmental delay; Response to name; Early identification; Video analysis