A brief observation to screen autism in toddlers and predict developmental trajectory

Article Article scientifique Article A brief observation to screen autism in toddlers and predict developmental trajectory eng 2025-09-01 2025-12 author Journal Fiona 0009-0001-8269-3765 869794 Département de psychiatrie (PSYAT) author Chataing Thibaut Camille Nathan 0009-0008-0868-9400 404739 Département de psychiatrie (PSYAT) author Godel Michel 0000-0002-9789-3540 778283 Département de psychiatrie (PSYAT) author Kojovic Nada 0000-0003-0116-2485 776933 Section de psychologie (PSICO) author Latreche Kenza 0000-0003-0264-4048 906678 Département de psychiatrie (PSYAT) author Schneider Maude 0000-0001-7147-8915 594384 Section de psychologie (PSICO) author Schaer Marie 0000-0001-8479-6365 510515 Département de psychiatrie (PSYAT) 200176 10.1016/j.jpedcp.2025.200176 41498061 2950-5410 PMC12766091 https://www.sciencedirect.com/science/article/pii/S2950541025000389 Objective: Autism spectrum disorder (ASD) affects approximately 1 in 31 children. Early diagnosis is crucial for optimizing outcomes through early interventions, and primary care settings need efficient tools to identify children presenting autistic features. This study explores the potential of early socio-communicative behaviors, measured by the Early Social Communication Scales, to screen for ASD in children younger than 3 years old, and predict their future cognitive development using machine learning models. Study design: This study analyzed longitudinal data from 113 children with ASD and 59 with typical development (TD), aged from 1 to 3 at baseline. Twenty-three ESCS variables were used to screen for ASD and predict cognitive development. The C5.0 decision tree algorithm was used to classify ASD vs TD, while linear regression and K-means clustering identified cognitive development patterns among autistic children. K-fold cross-validation, permutation testing, and undersampling were used for validation. Results: We distinguished between ASD and TD children with 95% accuracy, 96% sensitivity and 92% specificity. Nine behaviors contributed to distinguish ASD from TD. Behaviors that contributed most are the child's ability to initiate a turn taking and to point at desired objects. A separate model stratified children into groups with different cognitive outcome with 97% accuracy. Behavioral requests variables contributed in distinguishing extreme cognitive trajectories in autistic children. Conclusions: We provide an original decision-algorithm focusing on early socio-communicative behaviors to guide pediatricians through autism screening and cognitive development prediction. Autism Decision tree Early diagnosis Machine learning Predictors Screening tool Dewey 616.89 Dewey 150 Swiss National Science Foundation NCCR 'SYNAPSY - The synaptic bases of mental diseases' (phase III) 185897 CH Swiss National Science Foundation Measuring trajectories of cerebral development associated with autism in the first years of life 163859 CH Swiss National Science Foundation Measuring trajectories of cerebral development associated with autism in the first years of life 190084 CH Swiss National Science Foundation Digital Phenotyping of Autism Spectrum Disorders in Children 202235 CH Swiss National Science Foundation Exploring common mechanisms for social and non-social autism symptoms: a longitudinal study in the Geneva Autism Cohort 212653 CH 60 Département de psychiatrie 225 108 Section de psychologie 71 false 1360 Autism Brain and Behavior Lab 1033 1302 Unité de psychologie clinique des situations de handicap 1284 NCCR Synapsy Journal of pediatrics. Clinical practice 18 cbe7ff52-610b-4073-b5f8-a7dff90d505b Article (Published version) Public Journal_of_Pediatrics.pdf 2285670 application/pdf CC BY-4.0 a1ecdc01bcd77e8d24e755c120603dfda4cb84226d3273f7cfa8e180be63d169 313c4dec-b9e1-429c-b943-3dfc0990955e Supplemental data Public 1-s2.0-S2950541025000389-mmc1.docx 453249 application/vnd.openxmlformats-officedocument.wordprocessingml.document 0a82bf46c042e81a53f7358951c972c0845ad7f066db4e9e6779c559c1931ad4 532597b4-23c8-4181-be29-f14933b74d1c Supplemental data Public 1-s2.0-S2950541025000389-mmc2.docx 13379 application/vnd.openxmlformats-officedocument.wordprocessingml.document a47748de53bc4c30efb04a3631a6ed33349555f0c309cb2c080bd50ace976afe openAccess Faculté de médecine / Section de médecine clinique / Département de psychiatrie Faculté de psychologie et des sciences de l'éducation / Section de psychologie

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A brief observation to screen autism in toddlers and predict developmental trajectory	Journal of pediatrics. Clinical practice			2025	27	45

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Chataing, Thibaut

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