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

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT07370623

Enrollment

2200

Registered

2026-01-27

Start date

2025-10-28

Completion date

2027-12-01

Last updated

2026-03-20

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Pediatric Respiratory Distress

Brief summary

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.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

0 Years to 12 Years

Healthy volunteers

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.

Design outcomes

Primary

Measure	Time frame	Description
Accuracy of automated respiratory pattern assessment	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.

Countries

South Korea

Outcome results