Machine Learning Prediction of Mortality After Prone Positioning in ARDS
A Machine Learning Model to Predict Mortality in Patients With Acute Respiratory Distress Syndrome After Prone Positioning
1 other identifier
observational
377
0 countries
N/A
Brief Summary
Acute respiratory distress syndrome (ARDS) is a life-threatening condition with high mortality. Prone position ventilation (PPV) is an evidence-based therapy that improves oxygenation and survival in patients with moderate to severe ARDS; however, outcomes remain heterogeneous. Early identification of patients at high risk of mortality after PPV may improve clinical decision-making and individualized management. This retrospective observational study aims to develop and validate a machine learning model to predict intensive care unit (ICU) mortality in ARDS patients receiving prone position ventilation. Clinical, laboratory, and treatment variables collected from ICU electronic medical records will be used to construct prediction models using multiple machine learning algorithms. The performance of these models will be evaluated and compared to identify the optimal model for mortality prediction.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Mar 2026
Shorter than P25 for all trials
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
February 24, 2026
CompletedStudy Start
First participant enrolled
March 1, 2026
CompletedFirst Posted
Study publicly available on registry
March 3, 2026
CompletedPrimary Completion
Last participant's last visit for primary outcome
April 1, 2026
CompletedStudy Completion
Last participant's last visit for all outcomes
May 1, 2026
CompletedMarch 3, 2026
March 1, 2026
1 month
February 24, 2026
March 1, 2026
Conditions
Outcome Measures
Primary Outcomes (1)
ICU Mortality
Death from any cause during the intensive care unit (ICU) stay among patients with acute respiratory distress syndrome receiving prone position ventilation.
Up to 90 days.
Other Outcomes (1)
ARDS subphenotype classification based on machine learning model.
Baseline (at initiation of prone position ventilation).
Study Arms (1)
ARDS Patients Receiving Prone Position Ventilation
Adult patients diagnosed with acute respiratory distress syndrome (ARDS) who received prone position ventilation during intensive care unit (ICU) admission. Clinical data from electronic medical records will be collected retrospectively for the development and validation of machine learning models to predict ICU mortality.
Interventions
Prone position ventilation applied as part of routine clinical care for patients with acute respiratory distress syndrome. No experimental intervention was assigned in this observational study.
Eligibility Criteria
Adult patients diagnosed with acute respiratory distress syndrome (ARDS) who received prone position ventilation in the intensive care unit at Zhongshan Hospital, Fudan University. Clinical data were collected retrospectively from electronic medical records.
You may qualify if:
- Diagnosis of ARDS according to the Berlin definition \[15\];
- Receipt of at least one session of prone position ventilation (PPV) during hospitalization;
- Requirement for mechanical ventilation.
You may not qualify if:
- Age \<18 years;
- PPV duration \<6 hours;
- ICU length of stay \<24 hours;
- Pregnancy;
- Missing key clinical data.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
February 24, 2026
First Posted
March 3, 2026
Study Start
March 1, 2026
Primary Completion
April 1, 2026
Study Completion
May 1, 2026
Last Updated
March 3, 2026
Record last verified: 2026-03
Data Sharing
- IPD Sharing
- Will not share
Individual participant data will not be publicly shared due to institutional and ethical restrictions.