Research on Respiratory Support Decision-Making for Mechanically Ventilated ICU Patients Based on a Physiological World Model

September 16, 2026 updated by: Jialin Liu, Ruijin Hospital

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.

Study Overview

Status

Not yet recruiting

Conditions

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 Type

Observational

Enrollment (Estimated)

4232

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

    • Shanghai Municipality
      • Shanghai, Shanghai Municipality, China, 200025

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

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.

Description

Inclusion Criteria:

  • Inclusion criteria:
  • age ≥ 18 years
  • received invasive mechanical ventilation during ICU stay
  • had complete 48hour baseline data and 96hour followup data.

Exclusion Criteria:

  • age < 18 years
  • duration of mechanical ventilation < 24 hours
  • missing rate > 50% for key variables (FiO₂, PEEP, SpO₂, respiratory rate)
  • received ECMO therapy.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: COHORT
  • Time Perspectives: RETROSPECTIVE

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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

28 days

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

September 14, 2026

Primary Completion (Estimated)

December 31, 2028

Study Completion (Estimated)

December 31, 2029

Study Registration Dates

First Submitted

September 10, 2026

First Submitted That Met QC Criteria

September 16, 2026

First Posted (Actual)

September 22, 2026

Study Record Updates

Last Update Posted (Actual)

September 22, 2026

Last Update Submitted That Met QC Criteria

September 16, 2026

Last Verified

September 1, 2026

More Information

Terms related to this study

Other Study ID Numbers

  • RJ2026681

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

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.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.