ALI/ARDS Clinical Sub-phenotyping Study

Recruiting

• Conditions: Acute Lung Injury/Acute Respiratory Distress Syndrome (ARDS)

• Registration Number: NCT06123962
• Lead Sponsor: China-Japan Friendship Hospital

Brief Summary

1. Construct a structured clinical data and biosample information platform for Chinese patients with acute lung injury/ acute respiratory distress syndrome.

2. By deciphering the heterogeneity of patients with acute lung injury/ acute respiratory distress syndrome, achieve clinical, longitudinal physiological, and biological sub-phenotyping to guide individualized precision treatment and improve prognosis.

Detailed Description

Acute lung injury/ acute respiratory distress syndrome is one of the most common and complex critical illnesses in clinical practice, with a high mortality rate of 45% to 50%. Currently, effective therapeutic strategies for this condition are still lacking. Increasing evidence suggests that the significant heterogeneity of this disease plays a crucial role in the poor treatment outcomes and high mortality rates observed in patients. Therefore, this study aims to analyze the heterogeneity of acute lung injury/ acute respiratory distress syndrome patients and establish a clinical classification system for acute lung and extrapulmonary organ injuries.

The objectives of this study include establishing a nationwide clinical database and biobank for acute lung injury / acute respiratory distress syndrome by collecting clinical data and biological samples from various provinces. By overcoming the barriers posed by diverse and heterogeneous data sources, mathematical and machine learning models will be utilized to construct clinical, physiological, and biological classification systems for acute lung and extrapulmonary organ injuries. The proposed classification model will be validated multiple times using international public databases and prospective acute lung injury/acute respiratory distress syndrome cohorts to ensure its stability and generalizability. The mapping relationship between different classifications and patient prognosis as well as treatment responsiveness will be explored.

Moreover, a machine learning-based supervised technique will be applied to develop a bedside simplified model (Point-of-Care model) and establish a bedside clinical classification decision system. Ultimately, this research aims to provide a foundation for standardized and precision-guided clinical diagnostic and therapeutic pathways, promoting improved treatment outcomes and overall prognosis in acute lung injury/ acute respiratory distress syndrome.

Study Timeline

• Study First Submitted: 2023-08-29
• Study First Submitted QC: 2023-11-08
• Study First Posted: 2023-11-09
• Study Start: 2023-12-14
• Status Verified: 2025-02
• Last Update Submitted: 2025-02-10
• Last Update Posted: 2025-02-12
• Primary Completion: 2025-12-31
• Study Completion: 2025-12-31

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 1500

Inclusion Criteria

• Meet the diagnostic criteria for Acute Respiratory Distress Syndrome (ARDS) according to the updated global definition in 2023.
• The patient or their legal representative signs an informed consent form.

Exclusion Criteria

• Individuals aged less than 18 years old.
• Those who refuse to participate in the study.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
ICU mortality	up to 12 weeks	In ICU mortality
hospital mortality	up to 24 weeks	In hospital mortality

Secondary Outcome Measures

Name	Time	Method
28 days without mechanical ventilation	up to 28 days	28 days without mechanical ventilation
length of stay in the ICU	up to 12 weeks	length of stay in the ICU
Total length of hospital stay	up to 24 weeks	Total length of hospital stay
Mortality at 1 year after discharge	through study completion, an average of 1 year	Mortality at 1 year after discharge

Trial Locations

Locations (1)

Jingen Xia; 🇨🇳 Beijing, China