Acute Lung Injury/Acute Respiratory Distress Syndrome (ARDS)
Conditions
Keywords
Acute Lung Injury/Acute Respiratory Distress Syndrome (ARDS), Sub-phenotypes, Treatment strategies
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.
Interventions
PROCEDURECollect peripheral blood and bronchoalveolar lavage fluid
Peripheral venous blood will be collected and stored from the study participants at a total of five time points: Day 0, Day 1, Day 2, Day 3 after admission to the ICU, and the day of ICU discharge/death. The collection will be conducted after assessing the patients' eligibility for ARDS diagnosis. Each time point will involve the collection of one tube of peripheral venous blood, totaling 5 mL per sample. Within 24 hours after patients' admission to the ICU and meeting the assessment criteria for ARDS diagnosis, bronchoalveolar lavage fluid (BALF) will be collected and retained, totaling 10 mL.
Sponsors
China-Japan Friendship Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| ICU mortality | up to 12 weeks | In ICU mortality |
| hospital mortality | up to 24 weeks | In hospital mortality |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| 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 |
Countries
China
Contacts
Primary ContactJingen Xia, M.D
Outcome results
None listed