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.
PICU patients aged 1 month to 18 years.
Receiving invasive mechanical ventilation, expected to last ≥ 24 hours.
Informed consent signed before enrollment.
Expected survival < 24 hours
Irreversible brain injury (GCS = 3 + absence of brainstem reflexes)
Severe congenital cardiopulmonary malformations affecting ventilation assessment
Pregnancy (must be ruled out in adolescent girls)
Wu Rongzhou
Lead sponsor
Wenzhou Medical University
Sponsor institution