P-382: Feasibility and implementation of T1D screening in pediatric primary care
C de Almagro, M Milla, E Delgado, J Verme, A Granados, A Carrillo-IreguiAbstract
Introduction
Type 1 diabetes (T1D) is an autoimmune disease with ∼40% of U.S. youth presenting in diabetic ketoacidosis (DKA) at diagnosis, leading to poorer glycemic outcomes. Islet autoantibody screening identifies presymptomatic T1D, yet implementation in primary care remains limited.
Objectives
To assess feasibility, acceptability, and preliminary yield of T1D autoantibody (AAb) screening in a pilot primary-care program at a freestanding children’s hospital.
Methods
Implementation included education to primary care providers and workflow development based on site logistics. Eligible participants included children aged 2-15 years without a prior diagnosis of diabetes seen at a well-child visit. Screening was offered and specimens were collected via dried blood spot and tested for AAb (anti-GAD65, anti-IA2, and anti-insulin). Results were returned via phone call with referral for the positive AAb to Early-Stage Clinic for confirmatory testing, follow-up, and staged risk assessment. Outcomes included feasibility (reach/uptake, completion, sample adequacy, turnaround time, staff time/cost), implementation (acceptability, adoption, sustainability indicators), and clinical yield (screen positive and confirmed positive rates), guided by RE-AIM framework.
Results
From Feb–Apr 2026, 151 children were offered screening and 106 completed testing (70.2%); mean age was 9.3±3.6 years. Non-completion was primarily due to time constraints, low trust in preventive testing, and fear of pain. Sample adequacy was 100%. One child screened positive (0.9%) and was referred for follow-up. Clinician acceptability was 100%. Estimated time per patient was ∼10 minutes (2, 3, 5 minutes for recruitment, consent, and collection respectively).
Conclusions
Universal T1D AAb screening during well-child visits was feasible with high uptake, minimal staff time, and reliable dried blood spot processing. This pilot demonstrated the ability to identify an at-risk child and link to early-stage diabetes follow-up.