Acute Respiratory Distress SyndromeNCT07728136
AI-Guided Mechanical Ventilation in Children: A Randomized Controlled Trial
A study testing AI-generated recommendations for ventilator parameters. in people with Acute Respiratory Distress Syndrome and Pneumonia in Children, run by Wu Rongzhou.
Trial 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. Read more about this study
- Who is it for?
- Ages 1 month to 18 yearsHealthy volunteers can take part
- Conditions the study is for
- Acute Respiratory Distress Syndrome, Pneumonia in Children, Respiratory Failure (Pediatric Patients)
- What is being tested?
- AI-generated recommendations for ventilator parameters.
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 200 participants
- Where
- No sites listed yet
- Study dates
- 1 Sep 2026to 31 Dec 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 1 month to 18 years
- All sexes
- Healthy volunteers accepted
- Child, Adult
Who may be able to join
- PICU patients aged 1 month to 18 years.
- Receiving invasive mechanical ventilation, expected to last ≥ 24 hours.
- Informed consent signed before enrollment.
Who cannot join
- 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
About this study
Official title: Randomized Controlled Study on Intelligent Optimization of Ventilator Parameters for Pediatric Patients Undergoing Mechanical Ventilation Based on Large Language Models
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.
- Conditions
- Acute Respiratory Distress Syndrome, Pneumonia in Children, Respiratory Failure (Pediatric Patients), Congenital Heart Disease in Children
- Being tested
- AI-generated recommendations for ventilator parameters.
- Medical subject headings
- Respiratory Distress Syndrome, Respiratory Insufficiency
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
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.
| Study group | Role | What they receive |
|---|---|---|
| AI-Guided Group | Experimental | Not described Receives: Other: AI-generated recommendations for ventilator parameters. |
| Control Group | No intervention | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of ventilator-free days within 28 days
Days survived and free from invasive ventilation
Measured: From the start of tracheal intubation until 28 days after tracheal intubation.
Secondary outcomes (3)
Mechanical Ventilation-Related Complications
Cumulative duration of mechanical ventilation, reintubation rate (within 48 hours of extubation), ventilator-associated pneumonia (VAP), barotrauma.
Measured: From the start of tracheal intubation to Day 28
Length of Hospital Stay
PICU Length of Stay, Total Hospital Length of Stay
Measured: The duration from the time of admission to discharge for pediatric patients-up to a maximum of three months.
Artificial Intelligence System Evaluation
Rate of physician adoption of AI recommendations
Measured: From the start of tracheal intubation to Day 28
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Jul 2026
- Study start1 Sep 2026 (estimated)
- Primary completion31 Dec 2027 (estimated)
- Study completion31 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Acute Respiratory Distress SyndromeStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- 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.
- Masking
- None (open label)
- Enrolment
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Wu Rongzhou
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Wu Rongzhou, Wenzhou Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07728136
- Sponsor's protocol ID
- 2026-K-301-01
- Status last verified
- Jul 2026
- First submitted
- 22 Jul 2026
- Last updated
- 27 Jul 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 27 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Randomized Controlled Study on Intelligent Optimization of Ventilator Parameters for Pediatric Patients Undergoing Mechanical Ventilation Based on Large Language Models
- ClinicalTrials.gov ID
- NCT07728136
- Acronym / sponsor ID
- 2026-K-301-01
- Conditions
- Acute Respiratory Distress Syndrome, Pneumonia in Children, Respiratory Failure (Pediatric Patients), Congenital Heart Disease in Children
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- Wu RongzhouUniversity, hospital or other
- Study start
- 1 Sep 2026 (estimated)
- Primary completion
- 31 Dec 2027 (estimated)
- Study completion
- 31 Dec 2027 (estimated)
- First posted
- 27 Jul 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- 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.
| Arm | Type | Receives |
|---|---|---|
| AI-Guided Group | Experimental | Other: AI-generated recommendations for ventilator parameters. |
| Control Group | No intervention | – |
Who may qualify
- Ages
- 1 month to 18 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult
Key inclusion criteria (3 listed)
- PICU patients aged 1 month to 18 years.
- Receiving invasive mechanical ventilation, expected to last ≥ 24 hours.
- Informed consent signed before enrollment.
Key exclusion criteria (6 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| 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. | Other | AI-Guided Group |
Primary outcome
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
3 secondary outcomes
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
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 27 Jul 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
A study testing AI-generated recommendations for ventilator parameters. in people with Acute Respiratory Distress Syndrome and Pneumonia in Children, run by Wu Rongzhou.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 27 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of ventilator-free days within 28 days (time frame: From the start of tracheal intubation until 28 days after tracheal intubation.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 27 Jul 2026; AzTrials last refreshed its copy on 31 Oct 2026.