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Multimodal Database and Large Language Model for ARDS
Sponsor: China-Japan Friendship Hospital
Summary
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?
Official title: Construction of ARDS Clinical Multimodal Database and ARDS-Specific Large Language Model
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
6500
Start Date
2025-05-07
Completion Date
2028-03-31
Last Updated
2025-05-15
Healthy Volunteers
No
Interventions
Clinical data and biospecimen collection
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.