AI-Guided Mechanical Ventilation in Children: A Randomized Controlled Trial

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.

Inclusion Criteria: 1. PICU patients aged 1 month to 18 years. 2. Receiving invasive mechanical ventilation, expected to last ≥ 24 hours. 3. Informed consent signed before enrollment. Exclusion Criteria: 1. Expected survival \< 24 hours 2. Irreversible brain injury (GCS = 3 + absence of brainstem reflexes) 3. Severe congenital cardiopulmonary malformations affecting ventilation assessment 4. Pregnancy (must be ruled out in adolescent girls) 5. Currently participating in other ventilation intervention trials 6. Guardian refusal to participate