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Not yet recruiting NCT07728136

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

No phase Interventional Acute Respiratory Distress Syndrome Pneumonia in Children Respiratory Failure (Pediatric Patients) Congenital Heart Disease in Children

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: AI-generated recommendations for ventilator parameters..
Who it may be relevant to
Registry conditions: Acute Respiratory Distress Syndrome, Pneumonia in Children, Respiratory Failure (Pediatric Patients), Congenital Heart Disease in Children. Basic parameters: 1 months — 18 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Center list to be confirmed — check the primary protocol.
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

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Official title

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

Overview

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.

Interventions

  • Other 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.

Primary outcome measures

  • Number of ventilator-free days within 28 days [Time frame: From the start of tracheal intubation until 28 days after tracheal intubation.]
Secondary outcome measures (3)
  • Mechanical Ventilation-Related Complications [Time frame: From the start of tracheal intubation to Day 28]
  • 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.]
  • Artificial Intelligence System Evaluation [Time frame: From the start of tracheal intubation to Day 28]

Eligibility criteria

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

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Allocation
Randomized
Model
Parallel assignment
Masking
Open label
Primary purpose
Health services research

Study locations

Center list to be confirmed — check the primary protocol.

Identifiers

NCT: NCT07728136 · 2026-K-301-01

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗