Could a computer algorithm predict childhood asthma before symptoms start?

NCT ID NCT05826561

Terminated Diagnosis Sponsor: Indiana University Source: ClinicalTrials.gov ↗

First seen Jul 21, 2026 · Last updated Jul 22, 2026 · Updated 1 time

Summary

This study tests a new digital tool that uses information already in a child's electronic health records to estimate their risk of developing asthma. The tool is designed for pediatricians to use during checkups for preschool-aged children, where asthma is often missed. Researchers are evaluating whether doctors find the tool useful, easy to use, and whether it helps them make more accurate predictions.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance: a machine-learning algorithm that analyzes electronic health records to predict childhood asthma risk
What this could lead to: If successful, this tool could help pediatricians catch asthma earlier in young children, leading to better treatment and fewer emergencies.
What could go wrong: This is a small, early-stage study focused on usability and acceptance, not on long-term health outcomes. The tool may not improve care in real-world settings.

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Conditions

The condition(s) this trial relates to.

childhood onset asthma

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

PEDIATRIC ASTHMA

Contacts and locations

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Locations

Indiana University

Indianapolis, Indiana, 46202, United States

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