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AI-Guided Mechanical Ventilation in Children: A Randomized Controlled Trial
Sponsor: Wu Rongzhou
Summary
This prospective, randomized controlled trial aims to evaluate whether an AI-driven decision support system can improve clinical outcomes for mechanically ventilated pediatric patients (aged 1 month to 18 years) in the PICU, compared to standard care. The primary question addressed is: Do patients whose ventilator parameter optimization decisions are guided by AI assistance achieve a greater number of ventilator-free days within 28 days compared to those managed with standard care by medical staff? Eligible pediatric patients requiring mechanical ventilation following tracheal intubation will be randomly assigned (1:1) to either the AI-guided intervention group or the standard care control group. In the intervention group, physicians will receive real-time, AI-generated recommendations for ventilator parameters to inform clinical adjustments. In contrast, the control group will be managed according to standard clinical protocols. This study seeks to assess whether AI-driven ventilator optimization can effectively improve clinical outcomes and shorten ventilation duration for pediatric patients in the PICU.
Official title: Randomized Controlled Study on Intelligent Optimization of Ventilator Parameters for Pediatric Patients Undergoing Mechanical Ventilation Based on Large Language Models
Key Details
Gender
All
Age Range
1 Month - 18 Years
Study Type
INTERVENTIONAL
Enrollment
200
Start Date
2026-09-01
Completion Date
2027-12-31
Last Updated
2026-07-27
Healthy Volunteers
Yes
Conditions
Interventions
AI-generated recommendations for ventilator parameters.
In the AI-Guided Group, physicians will receive real-time, AI-generated recommendations for ventilator parameters to inform clinical adjustments.