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.

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Key information

Conditions

Acute Respiratory Distress Syndrome Congenital Heart Disease in Children Lung Diseases Pneumonia in Children Respiration Disorders Respiratory Distress Syndrome Respiratory Failure (Pediatric Patients) Respiratory Insufficiency Respiratory Tract Diseases

Age range

1 month–18 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Who can participate

Healthy volunteers accepted: Yes

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

Inclusion criteria

PICU patients aged 1 month to 18 years.
Receiving invasive mechanical ventilation, expected to last ≥ 24 hours.
Informed consent signed before enrollment.

Exclusion criteria

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)
Currently participating in other ventilation intervention trials
Guardian refusal to participate

Treatment and study plan

AI-generated recommendations for ventilator parameters.

Other

In the AI-Guided Group, physicians will receive real-time, AI-generated recommendations for ventilator parameters to inform clinical adjustments.

Primary outcomes

Number of ventilator-free days within 28 days

Time frame: From the start of tracheal intubation until 28 days after tracheal intubation.

Days survived and free from invasive ventilation

Secondary outcomes

Mechanical Ventilation-Related Complications

Time frame: From the start of tracheal intubation to Day 28

Cumulative duration of mechanical ventilation, reintubation rate (within 48 hours of extubation), ventilator-associated pneumonia (VAP), barotrauma.
Length of Hospital Stay

Time frame: The duration from the time of admission to discharge for pediatric patients-up to a maximum of three months.

PICU Length of Stay, Total Hospital Length of Stay
Artificial Intelligence System Evaluation

Time frame: From the start of tracheal intubation to Day 28

Rate of physician adoption of AI recommendations

Sponsors and collaborators

Lead sponsor

Wu Rongzhou

Other

Registry information

Official study title

Randomized Controlled Study on Intelligent Optimization of Ventilator Parameters for Pediatric Patients Undergoing Mechanical Ventilation Based on Large Language Models

Important dates

Study start: 2026
Primary completion: 2027
Study completion: 2027
First posted: Jul 27, 2026
Registry last updated: Jul 27, 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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Completed