Ignite Creation Date:
2025-12-24 @ 11:07 PM
Ignite Modification Date:
2025-12-25 @ 8:39 PM
Study NCT ID:
NCT05305469
Status:
RECRUITING
Last Update Posted:
2024-01-24
First Post:
2022-03-22
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Early Identification and Prognosis Prediction of Sepsis Through Multiomics
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D018805', 'term': 'Sepsis'}, {'id': 'D007249', 'term': 'Inflammation'}], 'ancestors': [{'id': 'D007239', 'term': 'Infections'}, {'id': 'D018746', 'term': 'Systemic Inflammatory Response Syndrome'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITH_DNA', 'description': 'Urine, and plasma'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 900}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2022-01-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-01', 'completionDateStruct': {'date': '2025-12-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2024-01-22', 'studyFirstSubmitDate': '2022-03-22', 'studyFirstSubmitQcDate': '2022-03-22', 'lastUpdatePostDateStruct': {'date': '2024-01-24', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-03-31', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-12-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Pathogen-specific patterns', 'timeFrame': 'March 2022 - December 2023', 'description': 'To elucidate the unique infection pathogen-specific molecular patterns in septic patients'}], 'secondaryOutcomes': [{'measure': 'Prognostic prediction models', 'timeFrame': 'March 2022 - December 2024', 'description': 'To establish the models using multi-omics data to predict the prognosis of sepsis'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Prognosis', 'Inflammation', 'Immune', 'Multiomics', 'Machine learning'], 'conditions': ['Sepsis']}, 'referencesModule': {'references': [{'pmid': '32290837', 'type': 'RESULT', 'citation': 'Wang J, Sun Y, Teng S, Li K. Prediction of sepsis mortality using metabolite biomarkers in the blood: a meta-analysis of death-related pathways and prospective validation. BMC Med. 2020 Apr 15;18(1):83. doi: 10.1186/s12916-020-01546-5.'}]}, 'descriptionModule': {'briefSummary': 'This study aims to integrate multi-omics data and clinical indicators to reveal pathogen-specific molecular patterns in patients with sepsis and establish prognostic prediction models through multiple machine learning algorithms.', 'detailedDescription': 'This study aims to quantify the plasma metabolome, single nucleotide polymorphisms (SNPs) of exons and immunocytokines of septic patients with different pathogen infections and prognostic outcomes. Multi-omics data, cytokines, and clinical indicators will be integrated through multiple machine learning algorithms to reveal pathogen-specific molecular patterns and multi-dimensional prognostic prediction models.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '85 Years', 'minimumAge': '18 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'The study cases are from the Department of Critical Care Medicine, a top-grade hospital in Yantai', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Patients with sepsis or septic shock who meet the diagnostic criteria (2016 sepsis 3.0 standard);\n* Age 18～85 years old.\n\nExclusion Criteria:\n\n* ICU stay of the subjects less than 72 hours;\n* Female subjects who are pregnant;\n* The subjects not sure if infected;\n* The subjects performed CPR;\n* The subjects suffer from chronic renal disease;\n* The subjects with incomplete clinical data.'}, 'identificationModule': {'nctId': 'NCT05305469', 'acronym': 'EIPPSM', 'briefTitle': 'Early Identification and Prognosis Prediction of Sepsis Through Multiomics', 'organization': {'class': 'OTHER', 'fullName': 'Yantai Yuhuangding Hospital'}, 'officialTitle': 'Early Identification and Prognosis Prediction of Sepsis Through Multiomics', 'orgStudyIdInfo': {'id': '2022-031'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'GN', 'description': 'Gram-negative bacteria infection group'}, {'label': 'GP', 'description': 'Gram-positive bacteria infection group'}, {'label': 'Fungal', 'description': 'Fungal infection group'}, {'label': 'Viral', 'description': 'Viral infection group'}, {'label': 'Control', 'description': 'Non-sepsis group'}]}, 'contactsLocationsModule': {'locations': [{'zip': '264000', 'city': 'Yantai', 'state': 'Shandong', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Jing Wang', 'role': 'CONTACT', 'email': 'wangjinghehe@sina.com'}], 'facility': 'Yantai Yuhuangding Hospital', 'geoPoint': {'lat': 37.47649, 'lon': 121.44081}}], 'centralContacts': [{'name': 'Jing Wang', 'role': 'CONTACT', 'email': 'wangjinghehe@sina.com', 'phone': '8605356691999', 'phoneExt': '83608'}], 'overallOfficials': [{'name': 'Jing Wang', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Yantai Yuhuangding Hospital'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Yantai Yuhuangding Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}