Early Prediction of Autistic Spectrum Disorder Using Developmental Surveillance Data.

ABSTRACT:

Importance

With the continuous increase in the prevalence of autistic spectrum disorder (ASD), effective early screening is crucial for initiating timely interventions and improving outcomes.

Objective

To develop predictive models for ASD using routinely collected developmental surveillance data and to assess their performance in predicting ASD at different ages and in different clinical scenarios.

Design, setting, and participants

This retrospective cohort study used nationwide data of developmental assessments conducted between January 1, 2014, and January 17, 2023, with minimal follow-up of 4 years and outcome collection in March 2023. Data were from a national program of approximately 1000 maternal child health clinics that perform routine developmental surveillan

SUBMITTER: Amit G 

PROVIDER: S-EPMC12282497 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature