The goal of this observational study is to integrate existing clinical cohorts from the research team to establish dedicated cohorts for ARDS and high-risk ARDS patients (primarily SCAP patients), then systematically collect comprehensive clinical data and multi-omics biological samples to construct a high-quality multimodal ARDS database. Building upon this foundation, the research will develop an ARDS-specific large-scale disease model to assist clinical decision-making in early warning, diagnosis, and prognosis prediction. The main question it seeks to address is: Can the establishment of specialized ARDS cohorts and multimodal databases, combined with the development of an ARDS-specific large-scale disease model, effectively improve ARDS prediction rates, diagnostic accuracy, and reduce mortality rates, thereby enhancing overall clinical management standards?
ARDS is a common critical illness in ICUs with high mortality rates. Its prognostic factors are complex and multifaceted, including challenges in precise early warning, lack of early diagnostic biomarkers due to complicated pathogenesis, and difficulties in personalized precision treatment owing to high heterogeneity. Interventions targeting any single aspect are unlikely to improve overall outcomes. Only through systematic interventions addressing key aspects of ARDS - including assessment, early warning, diagnosis, phenotyping and treatment - can its mortality be significantly reduced. This study is a multicenter, retrospective and prospective observational cohort study with the following objectives: 1. To integrate existing ARDS-related cohorts from the research team (comprising 5,000 patients enrolled between January 1, 2014 and September 1, 2024) and prospectively recruit an additional 1,500 ARDS patients and ARDS high-risk individuals. This will establish a comprehensive cohort of no fewer than 6,500 cases, primarily including patient populations with conditions such as severe community-acquired pneumonia (SCAP) and other ARDS-associated disorders; 2. To collect comprehensive clinical data and multi-omics biological samples from these patients, constructing a high-quality multimodal ARDS database through rigorous data governance; 3. Based on this foundation, to develop and clinically validate an ARDS-specific large-scale disease model to assist in clinical decision-making for early warning, diagnosis, and prognosis prediction, thereby improving the overall standard of ARDS management.
Study Type
OBSERVATIONAL
Enrollment
6,500
Clinical Data Collection: Case report forms were utilized to systematically capture multimodal clinical data, including: demographic characteristics, clinical symptoms and physical signs, laboratory test results, chest imaging data, organ support parameters, pharmacological interventions , complications and clinical outcomes. Biospecimen Collection: ARDS patients underwent biospecimen collection at days 1, 4, and 7 post-diagnosis. High-risk ARDS cohorts provided specimens within 24 hours of ICU admission. Specimens included: peripheral blood, Sputum/BALF, stool and urine.
ICU mortality
Time frame: From the time of patient enrollment until ICU discharge(For example: If a patient is enrolled in the study and remains in the ICU for 20 days before discharge, then the time frame would be 20 days.)
Hospital mortality
Time frame: From the time of patient enrollment until hospital discharge(For example: If a patient is enrolled in the study and remains in the hospital for 20 days before discharge, then the observation time frame would be 20 days.)
ICU length of stay
Time frame: From the time of patient enrollment until ICU discharge(For example: If a patient is enrolled in the study and remains in the ICU for 20 days before discharge, then the observation time frame would be 20 days.)
Hospital length of stay
Time frame: From enrollment to hospital discharge(For example: If a patient is enrolled in the study and remains in the hospital for 20 days before discharge, then the observation time frame would be 20 days.)
Mortality rates at 28 days post-enrollment
Time frame: From patient enrollment until 28 days post-enrollment
Mortality rates at 60 days post-enrollment
Time frame: From patient enrollment until 60 days post-enrollment
Mortality rates at 90 days post-enrollment
Time frame: From patient enrollment until 90 days post-enrollment
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