ALI/ARDS Clinical Sub-phenotyping Study

China-Japan Friendship Hospital

Status: Enrolling

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

Treatments: Procedure: Collect peripheral blood and bronchoalveolar lavage fluid

Study type: Observational

Funder types: Other

Identifiers

NCT06123962

2022YFC2504401

Details and patient eligibility

About

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.

Full 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.

Enrollment: 1,500 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

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.