Acute Respiratory FailureNCT07834671
Research on Respiratory Support Decision-Making for Mechanically Ventilated ICU Patients Based on a Physiological World Model
An observational study of Acute Respiratory Failure, run by Ruijin Hospital at 1 site in China.
Trial summary
Mechanical ventilation is essential for ICU patients with respiratory failure, yet ventilator adjustment and weaning decisions remain experience-dependent and highly variable. Current single-point metrics such as the oxygenation index cannot distinguish true recovery from support-dependent stability-the same… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Acute Respiratory Failure
- How many people
- 4,232 participants
- Where
- 1 siteChina
- Study dates
- 14 Sep 2026to 31 Dec 2029
- Phase
- Observational
- 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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Adult ICU patients (≥18 years) who received invasive mechanical ventilation at the Department of Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, between January 2016 and June 2026.
Who may be able to join
- age ≥ 18 years
- received invasive mechanical ventilation during ICU stay
- had complete 48hour baseline data and 96hour followup data.
Who cannot join
- age < 18 years
- duration of mechanical ventilation < 24 hours
- missing rate > 50% for key variables (FiO₂, PEEP, SpO₂, respiratory rate)
- received ECMO therapy.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site
Ruijin hospital
Shanghai, Shanghai Municipality, 200025
Jing Xu, +8618217732985, xj40952@rjh.com.cn
About this study
Mechanical ventilation is essential for ICU patients with respiratory failure, yet ventilator adjustment and weaning decisions remain experience-dependent and highly variable. Current single-point metrics such as the oxygenation index cannot distinguish true recovery from support-dependent stability-the same oxygenation level may reflect either. This study uses EHR data from 4,232 invasively ventilated ICU patients at Ruijin Hospital (2016-2026) to develop LAVENT, a deep learning-based physiological world model of respiratory dynamics. LAVENT learns the co-evolution of patient physiology and respiratory support, generates 96-hour multivariate trajectories under candidate FiO₂/PEEP settings, and compares alternative ventilation strategies within the same patient state. External validation uses the MIMIC-IV database (n = 29,899). This retrospective observational study uses only existing EHR data, with no prospective intervention or biospecimen collection.
Read the detailed description
Mechanical ventilation is the cornerstone of life support for critically ill patients with respiratory failure in the ICU. However, adjustments to ventilator settings and decisions regarding weaning remain highly dependent on clinical experience, resulting in substantial inter-clinician variability. A fundamental limitation of current practice is that commonly used single-point metrics-such as the oxygenation index-cannot reliably reflect a patient's true recovery state across different levels of respiratory support. The same oxygenation level may indicate genuine recovery in a patient on low support, or persistent respiratory failure masked by high ventilatory support. This conflation of "true recovery" with "support-dependent stability" is a major contributor to weaning failure and delayed extubation.
To address this challenge, this study will leverage electronic health record (EHR) data from ICU patients who received invasive mechanical ventilation at Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, between 2016 and 2026 (RuiICU-P1 cohort, n = 4,232), to develop a deep learning-based physiological world model of respiratory dynamics (LAVENT). The model is designed to: (1) learn the co-evolutionary dynamics between a patient's physiological state and respiratory support; (2) generate 96-hour multivariate clinical trajectories given the current patient state and candidate ventilator settings (FiO₂, PEEP); and (3) compare the differential clinical outcomes of alternative ventilator adjustment strategies within the same patient state. External validation will be performed using the public MIMIC-IV database (n = 29,899) to assess model transferability across healthcare systems.
This is a retrospective, observational study using only existing EHR data, without any prospective patient intervention, additional examinations, or biospecimen collection.
- Conditions
- Acute Respiratory Failure
- Keywords
- ventilator weaning, mechanical ventilation
What is being measured
The primary outcome is the main question the study is designed to answer.
success rate of ventilator weaning
The proportion of participants who successfully achieve liberation from invasive mechanical ventilation (weaning success), expressed as a percentage of all participants who undergo a weaning attempt
Measured: 28 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Sep 2026
- Study start14 Sep 2026 (estimated)
- Primary completion31 Dec 2028 (estimated)
- Study completion31 Dec 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Acute Respiratory FailureStudies of the same condition, open and under way.
- More trials run by Ruijin HospitalThe sponsor's other registered studies.
- 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
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 4,232 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Ruijin Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Jialin Liu, Ruijin Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07834671
- Sponsor's protocol ID
- RJ2026681
- Status last verified
- Sep 2026
- First submitted
- 10 Sep 2026
- Last updated
- 22 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Privacy and confidentiality constraints: The source data contain sensitive clinical information derived from electronic medical records. Although all data are de-identified before analysis, the combination of detailed longitudinal physiological variables, ventilator parameters, and clinical outcomes carries a residual risk of re-identification. Institutional privacy policies and the approved ethics protocol do not permit public deposition of individual-level data. Ethics approval and consent limitations: This study is approved with a waiver of informed consent for retrospective use of existing EHR data. The ethics approval covers secondary analysis for the specified research purpose only, and does not extend to unrestricted sharing or redistribution of individual-level records.
Study at a glance
From the registry record, last updated by the sponsor on 22 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Research on Respiratory Support Decision-Making for Mechanically Ventilated ICU Patients Based on a Physiological World Model
- ClinicalTrials.gov ID
- NCT07834671
- Acronym / sponsor ID
- RJ2026681
- Conditions
- Acute Respiratory Failure
- Keywords
- ventilator weaning, mechanical ventilation
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 4,232 participants (estimated)
- Lead sponsor
- Ruijin HospitalUniversity, hospital or other
- Study start
- 14 Sep 2026 (estimated)
- Primary completion
- 31 Dec 2028 (estimated)
- Study completion
- 31 Dec 2029 (estimated)
- First posted
- 22 Sep 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.
Mechanical ventilation is essential for ICU patients with respiratory failure, yet ventilator adjustment and weaning decisions remain experience-dependent and highly variable. Current single-point metrics such as the oxygenation index cannot distinguish true recovery from support-dependent stability-the same oxygenation level may reflect either. This study uses EHR data from 4,232 invasively ventilated ICU patients at Ruijin Hospital (2016-2026) to develop LAVENT, a deep learning-based physiological world model of respiratory dynamics. LAVENT learns the co-evolution of patient physiology and respiratory support, generates 96-hour multivariate trajectories under candidate FiO₂/PEEP settings, and compares alternative ventilation strategies within the same patient state. External validation uses the MIMIC-IV database (n = 29,899). This retrospective observational study uses only existing EHR data, with no prospective intervention or biospecimen collection.
Detailed description
Mechanical ventilation is the cornerstone of life support for critically ill patients with respiratory failure in the ICU. However, adjustments to ventilator settings and decisions regarding weaning remain highly dependent on clinical experience, resulting in substantial inter-clinician variability. A fundamental limitation of current practice is that commonly used single-point metrics-such as the oxygenation index-cannot reliably reflect a patient's true recovery state across different levels of respiratory support. The same oxygenation level may indicate genuine recovery in a patient on low support, or persistent respiratory failure masked by high ventilatory support. This conflation of "true recovery" with "support-dependent stability" is a major contributor to weaning failure and delayed extubation.
To address this challenge, this study will leverage electronic health record (EHR) data from ICU patients who received invasive mechanical ventilation at Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, between 2016 and 2026 (RuiICU-P1 cohort, n = 4,232), to develop a deep learning-based physiological world model of respiratory dynamics (LAVENT). The model is designed to: (1) learn the co-evolutionary dynamics between a patient's physiological state and respiratory support; (2) generate 96-hour multivariate clinical trajectories given the current patient state and candidate ventilator settings (FiO₂, PEEP); and (3) compare the differential clinical outcomes of alternative ventilator adjustment strategies within the same patient state. External validation will be performed using the public MIMIC-IV database (n = 29,899) to assess model transferability across healthcare systems.
This is a retrospective, observational study using only existing EHR data, without any prospective patient intervention, additional examinations, or biospecimen collection.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult ICU patients (≥18 years) who received invasive mechanical ventilation at the Department of Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, between January 2016 and June 2026.
Key inclusion criteria (3 listed)
- age ≥ 18 years
- received invasive mechanical ventilation during ICU stay
- had complete 48hour baseline data and 96hour followup data.
Key exclusion criteria (4 listed)
- age < 18 years
- duration of mechanical ventilation < 24 hours
- missing rate > 50% for key variables (FiO₂, PEEP, SpO₂, respiratory rate)
- received ECMO therapy.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
success rate of ventilator weaning
Time frame: 28 days
The proportion of participants who successfully achieve liberation from invasive mechanical ventilation (weaning success), expressed as a percentage of all participants who undergo a weaning attempt
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 22 Sep 2026.
- Individual participant dataSharing planned: No. Privacy and confidentiality constraints: The source data contain sensitive clinical information derived from electronic medical records. Although all data are de-identified before analysis, the combination of detailed longitudinal physiological variables, ventilator parameters, and clinical outcomes carries a residual risk of re-identification. Institutional privacy policies and the approved ethics protocol do not permit public deposition of individual-level data. Ethics approval and consent limitations: This study is approved with a waiver of informed consent for retrospective use of existing EHR data. The ethics approval covers secondary analysis for the specified research purpose only, and does not extend to unrestricted sharing or redistribution of individual-level records.
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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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Acute Respiratory Failure, run by Ruijin Hospital at 1 site in China.
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 4 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 22 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
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?
Contact Jing Xu (+8618217732985, xj40952@rjh.com.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
success rate of ventilator weaning (time frame: 28 days). 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 22 Sep 2026; AzTrials last refreshed its copy on 6 Nov 2026.