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NCT Number: NCT07370623

Development of an AI Assessment System for Pediatric Respiratory Distress : A Prospective Study

This is a multicenter, prospective observational study designed to collect clinical data for the development of a vision-language model-based artificial intelligence system for automated assessment of pediatric respiratory patterns.

The study enrolls pediatric patients aged 0 to 12 years who present to the pediatric emergency departments of participating institutions. Clinical and visual respiratory data are collected along with baseline clinical characteristics, including sex, age, body weight, height, presenting symptoms recorded at emergency department arrival, initial vital signs (body temperature, pulse rate, respiratory rate, blood pressure, and oxygen saturation), severity at presentation assessed by the Korean Triage and Acuity Scale (KTAS), emergency department management and outcomes such as hospital admission or discharge, and other relevant clinical information.

These data are used for cohort characterization and for the development and evaluation of an AI-based system that aims to automatically analyze pediatric respiratory patterns and support objective respiratory assessment in pediatric emergency care.

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Key information

Conditions

Pediatric Respiratory Distress

Age range

0 year–12 year

Sex eligibility

All sexes

Study type

Observational

Primary location

CHA Bundang Medical Center, CHA University, 9, Yatap-ro, Bundang-gu, Seongnam-si, Gyeonggi-do, South Korea

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Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Pediatric patients aged 0 to 12 years who present to participating pediatric emergency departments.
  • Patients for whom clinical data, including basic demographic characteristics (e.g., age, body weight), severity at presentation (e.g., KTAS level), vital signs, emergency department management and outcomes, as well as visual respiratory data, are available during emergency care.

Exclusion criteria

  • Patients outside the specified age range.
  • Patients with insufficient or poor-quality clinical or visual respiratory data.
  • Patients whose data cannot be used due to withdrawal of consent or regulatory restrictions.

Treatment and study plan

Primary outcomes

  1. Accuracy of automated respiratory pattern assessment

    Time frame: From study start through study completion (up to December 2027)

    Performance of a vision-language model-based system in assessing pediatric respiratory patterns using clinical and visual respiratory data collected in pediatric emergency departments.

Sponsors and collaborators

Lead sponsor

Samsung Medical Center

Other

Registry information

Important dates

Study start
2025
Primary completion
2027
Study completion
2027
First posted
Jan 27, 2026
Registry last updated
Mar 20, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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