[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100590923":3},{"organization":4,"outcomesModule":7,"designInfo":32,"detailedDescription":34,"studyPopulation":35,"armGroups":36,"interventions":46,"overallOfficials":11,"centralContacts":52,"locations":11,"responsibleParty":58,"collaborators":11,"id":62,"slug":11,"hasResults":63,"nctId":64,"briefTitle":65,"officialTitle":66,"acronym":11,"eligibilityCriteria":67,"healthyVolunteers":63,"sex":68,"minAge":69,"maxAge":11,"enrollmentInfo":70,"targetDuration":11,"studyType":73,"phases":11,"briefSummary":74,"conditions":75,"keywords":78,"overallStatus":80,"whyStopped":11,"lastUpdateSubmitDate":81,"lastUpdatePostDateStruct":82,"startDateStruct":85,"completionDateStruct":86,"leadSponsor":88,"locationsCount":11},{"fullName":5,"class":6},"China-Japan Friendship Hospital","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":16,"otherOutcomes":11},[9,13],{"measure":10,"description":11,"timeFrame":12},"ICU mortality",null,"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.)",{"measure":14,"description":11,"timeFrame":15},"Hospital mortality","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.)",[17,20,23,26,29],{"measure":18,"description":11,"timeFrame":19},"ICU length of stay","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.)",{"measure":21,"description":11,"timeFrame":22},"Hospital length of stay","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.)",{"measure":24,"description":11,"timeFrame":25},"Mortality rates at 28 days post-enrollment","From patient enrollment until 28 days post-enrollment",{"measure":27,"description":11,"timeFrame":28},"Mortality rates at 60 days post-enrollment","From patient enrollment until 60 days post-enrollment",{"measure":30,"description":11,"timeFrame":31},"Mortality rates at 90 days post-enrollment","From patient enrollment until 90 days post-enrollment",{"allocation":11,"interventionModel":11,"interventionModelDescription":11,"primaryPurpose":11,"observationalModel":33,"timePerspective":6,"maskingInfo":11},"COHORT","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.\n\nThis study is a multicenter, retrospective and prospective observational cohort study with the following objectives:\n\n1. 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;\n2. To collect comprehensive clinical data and multi-omics biological samples from these patients, constructing a high-quality multimodal ARDS database through rigorous data governance;\n3. 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.","1. ARDS ptients;\n2. ARDS high-risk patients",[37,42],{"label":38,"type":11,"description":39,"interventionNames":40},"ARDS","Patients meeting the 2024 global new definition of ARDS.",[41],"Behavioral: Clinical data and biospecimen collection",{"label":43,"type":11,"description":44,"interventionNames":45},"High-risk ARDS patients","Patients admitted to the ICU who do not meet ARDS diagnostic criteria but present with established ARDS risk factors, including: SCAP,, sepsis, high-risk trauma, post high-risk surgery, acute pancreatitis, shock, and aspiration.The primary etiology in this cohort is SCAP.",[41],[47],{"type":48,"name":49,"description":50,"armGroupLabels":51,"otherNames":11},"BEHAVIORAL","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.\n\nBiospecimen 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\u002FBALF, stool and urine.",[38,43],[53],{"name":54,"role":55,"phone":56,"phoneExt":11,"email":57},"Hangyong He","CONTACT","86+13693585722","yonghang2004@sina.com",{"type":59,"investigatorFullName":60,"investigatorTitle":61,"investigatorAffiliation":5,"oldNameTitle":11,"oldOrganization":11},"PRINCIPAL_INVESTIGATOR","Qingyuan Zhan","Director, Department of Respiratory and Critical Care Medicine","100590923",false,"NCT06973733","Multimodal Database and Large Language Model for ARDS","Construction of ARDS Clinical Multimodal Database and ARDS-Specific Large Language Model","Inclusion Criteria:\n\n1\\. ARDS Group: ( 1 ) Admitted to the ICU; ( 2 ) Age ≥18 years; ( 3 ) Meets the 2024 Global New Definition of ARDS (diagnosis confirmed by at least two experienced physicians; in case of disagreement, a third physician will adjudicate):Diagnostic Criteria:\n\n1. Risk Factors \\& Origin of Pulmonary Edema:Acute risk factors (e.g., pneumonia, non-pulmonary infection, trauma, transfusion, aspiration, shock).\n\n   Pulmonary edema not fully or primarily attributable to cardiogenic pulmonary edema\u002Ffluid overload.Hypoxemia\u002Fgas exchange abnormalities not primarily due to atelectasis.Exception: ARDS can still be diagnosed if predisposing risk factors exist, even with concurrent conditions.\n2. Timing:Acute onset or worsening of hypoxemic respiratory failure within 7 days of risk factor exposure or new\u002Fworsening respiratory symptoms.\n3. Chest Imaging (X-ray\u002FCT\u002FUS):Bilateral opacities (not fully explained by effusions, atelectasis, or nodules\u002Fmasses)；Ultrasound findings: Bilateral B-lines and\u002For consolidations.\n4. Oxygenation Status:\n\n   1. Non-intubated ARDS:PaO₂\u002FFiO₂ ≤300 mmHg OR SpO₂\u002FFiO₂ ≤315 (if SpO₂ ≤97%). High-flow nasal oxygen (HFNO) ≥30 L\u002Fmin or NIV\u002FCPAP ≥5 cm H₂O.\n   2. Intubated ARDS (all enrolled patients assessed via PaO₂\u002FFiO₂):\n\n      Mild: 200 \\\u003C PaO₂\u002FFiO₂ ≤300 OR 235 ≤ SpO₂\u002FFiO₂ ≤315 (if SpO₂ ≤97%). Moderate: 100 \\\u003C PaO₂\u002FFiO₂ ≤200 OR 148 \\\u003C SpO₂\u002FFiO₂ ≤235 (if SpO₂ ≤97%). Severe: PaO₂\u002FFiO₂ ≤100 OR SpO₂\u002FFiO₂ ≤148 (if SpO₂ ≤97%).\n   3. Resource-limited settings:No PEEP\u002Fminimum oxygen flow required; SpO₂\u002FFiO₂ ≤315 (if SpO₂ ≤97%).\n\n( 4 ) Signed informed consent.\n\n2\\. ARDS High-Risk Group: ( 1 ) Admitted to the ICU; ( 2 ) Age ≥18 years; ( 3 ) Does not meet ARDS criteria at ICU admission but has high-risk factors for ARDS development, including: SCAP, sepsis, high-risk trauma, post high-risk surgery, acute pancreatitis, shock, aspiration.The primary etiology in this cohort is SCAP.\n\nSCAP Diagnostic Criteria (≥1 major or ≥3 minor criteria):\n\n1. Major Criteria:\n\n   1. Requires mechanical ventilation (intubation).\n   2. Septic shock requiring vasopressors after fluid resuscitation.\n2. Minor Criteria:\n\n   1. Respiratory rate ≥30 breaths\u002Fmin.\n   2. PaO₂\u002FFiO₂ ≤250 mmHg.\n   3. Multilobar infiltrates.\n   4. Altered mental status\u002Fdisorientation.\n   5. BUN ≥20 mg\u002FdL (7.12 mmol\u002FL).\n   6. Leukopenia (WBC \\\u003C4×10⁹\u002FL).\n   7. Thrombocytopenia (platelets \\\u003C100×10⁹\u002FL).\n   8. Hypothermia (core temp \\\u003C36°C).\n   9. SBP \\\u003C90 mmHg requiring aggressive fluid resuscitation.\n\n( 4 ) Signed informed consent.\n\nExclusion Criteria:\n\n1. Patients without ARDS or ARDS high-risk factors.\n2. Age \\\u003C18 years.\n3. Incomplete clinical data.\n4. Refusal to sign informed consent.\n5. Long-term nursing home residents.\n6. Tracheostomy patients.\n7. Currently enrolled in another clinical trial.","ALL","18 Years",{"count":71,"type":72},6500,"ESTIMATED","OBSERVATIONAL","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?",[76,77],"Respiratory Distress Syndrome, Acute","Severe Community-Acquired Pneumonia",[79],"Acute Respiratory Distress Syndrome","NOT_YET_RECRUITING","2025-05-07",{"date":83,"type":84},"2025-05-15","ACTUAL",{"date":81,"type":72},{"date":87,"type":72},"2028-03-31",{"name":5,"class":6}]