[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"organ-damage\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:organ-damage":26},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,2,0,[8,45],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":13,"acronym":4,"eligibilityCriteria":14,"healthyVolunteers":11,"sex":15,"minAge":16,"maxAge":17,"enrollmentInfo":18,"targetDuration":21,"studyType":22,"phases":4,"briefSummary":23,"conditions":24,"keywords":27,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":33,"lastUpdatePostDateStruct":34,"startDateStruct":37,"completionDateStruct":39,"leadSponsor":41,"locationsCount":44},"100603014","construction-and-evaluation-of-tumor-immunotherapy-and-organ-damage-early-warning-system-based-on-multi-omics-100603014",false,"NCT07131007","Construction and Evaluation of Tumor Immunotherapy and Organ Damage Early Warning System Based on Multi-omics","Inclusion Criteria:\n\n· Patients with cancer who are receiving immune checkpoint inhibitor treatment.\n\nExclusion Criteria:\n\n* Active phase of severe autoimmune disease.\n* Severe organ dysfunction.\n* Presence of active infection.\n* Pregnancy or lactation.\n* Allergy to drug components.","ALL","18 Years","80 Years",{"count":19,"type":20},2000,"ESTIMATED","48 Months","OBSERVATIONAL","This project is based on the in-depth analysis and integration of multi-omics data, including but not limited to genomics, transcriptomics, proteomics, and metabolomics. It aims to construct a comprehensive early-warning system for organ function damage in immune-related adverse events (irAEs) associated with immune checkpoint inhibitors (ICIs) during tumor immunotherapy. The core objective of this system is to enhance the overall safety and efficacy of tumor immunotherapy.\n\nFirst, the project leverages a database to mine the differential omics data of tumor immunotherapy patients with combined organ dysfunction (including combined and non-combined severe infections) within the scope of this project. By integrating biochemical indicators and related hemodynamic data, it constructs a risk early-warning system for organ damage in patients undergoing tumor immunotherapy, while verifying its clinical value and guiding significance.\n\nThe specific contents mainly include: capturing specific molecules of organ damage in severe patients after tumor immunotherapy, screening genes, proteins, and metabolic products related to organ damage (including the heart, lungs, brain, liver, kidneys, gastrointestinal tract, etc.), and identifying new specific organ damage biomarkers under different pathogenic factors such as tumor immunotherapy, infections, and irAEs. It collects general clinical information, biochemical indicators, and hemodynamic indicators, and combines multi-omics data to establish an organ damage prediction model. Machine learning algorithms are used for optimization to construct an early-warning system.\n\nModel optimization within the system will be carried out, along with prospective clinical research and multi-dimensional verification. By evaluating the accuracy and cost-effectiveness of the model, it provides decision-making support for clinicians and promotes the development of personalized treatment.",[25,26],"Malignant Neoplasm","Organ Damage",[28,29,30,31],"Tumor immunotherapy","Immune checkpoint inhibitors","Immune - related adverse events","organ damage","RECRUITING","2026-03-19",{"date":35,"type":36},"2026-03-23","ACTUAL",{"date":38,"type":36},"2025-09-15",{"date":40,"type":20},"2029-01-01",{"name":42,"class":43},"Hebei Medical University Fourth Hospital","OTHER",1,{"id":46,"slug":47,"hasResults":11,"nctId":48,"briefTitle":49,"officialTitle":50,"acronym":4,"eligibilityCriteria":51,"healthyVolunteers":52,"sex":15,"minAge":16,"maxAge":4,"enrollmentInfo":53,"targetDuration":55,"studyType":22,"phases":4,"briefSummary":56,"conditions":57,"keywords":59,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":65,"lastUpdatePostDateStruct":66,"startDateStruct":68,"completionDateStruct":70,"leadSponsor":72,"locationsCount":44},"100569049","detection-of-sepsis-occurrence-by-using-blood-fluorescence-100569049","NCT06689189","Detection of Sepsis Occurrence by Using Blood Fluorescence","Metabolite Fluorescence Analysis in Critically Ill Patients' Blood and the Development of a Blood Fluorescence Analytical Platform","Inclusion Criteria:\n\n1. Healthy control group: Individuals who are physically healthy with no underlying diseases and have not been hospitalized within the past two years. Recruitment for healthy volunteers will be conducted through notices and online media.\n2. Sepsis Experimental Group: Patients with confirmed infections, having qSOFA ≥ 2 and SOFA ≥ 2, will be screened and confirmed by a physician to meet the inclusion criteria.\n3. Non-septic Severe Control Group: Patients with suspected or confirmed infections, having a SOFA score of 1, will be screened and confirmed by a physician to meet the inclusion criteria.\n\nExclusion Criteria: minors, pregnant, individuals with mental illnesses, and other vulnerable groups.",true,{"count":54,"type":20},800,"1 Month","This study adopted a case-control study method to explore a reagent-free, highly sensitive, and frequently screened blood fluorescence metabolite analyzer for sepsis, which can detect the emergence of inflammatory free radicals before organ damage and shorten the diagnosis time of sepsis.",[58,26],"Sepsis",[58,60,61,62,63,64],"Organ damage","Blood metabolite fluorescence","Machine learning","Deep learning","Fluorescence spectrum analytical platform","2024-11-12",{"date":67,"type":36},"2024-11-14",{"date":69,"type":36},"2024-01-24",{"date":71,"type":20},"2027-10-01",{"name":73,"class":74},"Ningbo Medical Center Lihuili Hospital","OTHER_GOV"]