Predictive Value of Early Autism Detection Models Based on Electronic Health Record Data Collected Before Age 1 Year.

ABSTRACT:

Importance

Autism detection early in childhood is critical to ensure that autistic children and their families have access to early behavioral support. Early correlates of autism documented in electronic health records (EHRs) during routine care could allow passive, predictive model-based monitoring to improve the accuracy of early detection.

Objective

To quantify the predictive value of early autism detection models based on EHR data collected before age 1 year.

Design, setting, and participants

This retrospective diagnostic study used EHR data from children seen within the Duke University Health System before age 30 days between January 2006 and December 2020. These data were used to train and evaluate L2-regularized Cox proportional hazards models predicting later

SUBMITTER: Engelhard MM 

PROVIDER: S-EPMC9896305 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature