Screening for Autism Spectrum Disorder in Toddlers During the 18- and 24-Month Well-Child Visits - Zhang, Ying; Zhou, Zhaoe; Xu, Qiong; Li, Huiping; Lv, Yujing; Zhu, Guowei; Dong, Ping; Li, Dongyun; Wang, Yi; Tang, Xinrui; Xu, Xiu (Frontiers in Psychiatry, 2022)
Objective: Early screening contributes to the early detection of children with autism spectrum disorder (ASD). We conducted a longitudinal ASD screening study in a large community setting. The study was designed to investigate the diagnostic rate of ASD screening and determine the effectiveness of ASD screening model in a community-based sample. Methods: We enrolled children who attended 18- and 24-month well-child care visits in Shanghai Xuhui District. Modified Checklist for Autism in Toddlers, Revised with Follow-up（M-CHAT-R/F）and Binomial Observation Test (BOT) were selected as screening instruments. Screen-positive children were referred to a tertiary diagnostic center for comprehensive ASD diagnostic evaluation. Screen-negative children received well-child checkups and follow-up every 3-6 months until age three and were referred if they were suspected of having ASD. Results: A total of 11,190 toddlers were screened. 36 screen-positive toddlers were diagnosed with ASD. The mean age at diagnosis for these children was 23.1 ± 4.55 months, diagnosed 20 months earlier than ASD children not screened. The diagnostic rate of ASD was 0.32% (95% CI: 0.23%–0.45%) in this community-based sample. In addition, 12 screen-negative children were diagnosed with ASD during subsequent well-child visit and follow-up. The average diagnostic rate of ASD rose to 0.43% (95% CI: 0.32%–0.57%) when toddlers were followed up to three years old. The positive predictive values (PPVs) of M-CHAT-R/F, M-CHAT-R high risk, and BOT for ASD were 0.31, 0.43 and 0.38 respectively. Conclusion: Our findings provide reliable data for estimating the rate of ASD detection and identifying the validity of community-based screening model. M-CHAT-R/F combined with BOT can be an effective tool for early detection of ASD. This community-based screening model is worth replicating.