protocolSection identificationModule nctId: NCT06383208, orgStudyIdInfo id: 2024-ZF-13, briefTitle: Cardiovascular-Renal Adverse Prognosis Assessment System for Coronary Heart Disease With Chronic Kidney Disease Based on Metabolomics, acronym: CRUISE-MET, statusModule overallStatus: RECRUITING, startDateStruct date: 2024-04-01, primaryCompletionDateStruct date: 2027-03-31, completionDateStruct date: 2027-03-31, studyFirstPostDateStruct date: 2024-04-25, lastUpdatePostDateStruct date: 2024-04-25, sponsorCollaboratorsModule leadSponsor name: China-Japan Friendship Hospital, class: OTHER, descriptionModule briefSummary: Coronary heart disease (CHD) combined with chronic kidney disease (CKD) affects a substantial portion of the population and carries a significant disease burden, often leading to poor outcomes. Despite efforts to strictly control traditional risk factors, the efficacy in improving outcomes for patients with both CHD and CKD has been limited. Recent advancements in lipid metabolism research have identified new lipid metabolites associated with the occurrence and prognosis of CHD and CKD. Our preliminary trial has shown that levels of certain lipid metabolites, such as Cer(18:1/16:0), HexCer(18:1/16:0), and PI(18:0/18:1), are notably elevated in patients with CHD and reduced kidney function compared to those with relatively normal kidney function. This suggests that dysregulation of these non-traditional lipid metabolites may contribute to residual risk for adverse outcomes in these patients.Furthermore, the emerging concept of "cardiovascular-kidney-metabolic syndrome" and the availability of new treatment options highlight the urgent need for a risk stratification tool tailored to modern management strategies and treatment goals to guide preventive measures effectively. To address this, we propose to conduct a prospective cohort study focusing on CHD combined with CKD. This study aims to comprehensively understand the clinical characteristics, diagnosis, treatment status, and cardiovascular-kidney prognosis in these patients. Through advanced metabolomics analysis, we seek to identify lipid metabolism profiles and non-traditional lipid metabolites associated with the progression of coronary artery disease in CHD-CKD patients. Leveraging clinical databases and metabolomics data, we will develop a robust risk prediction model for adverse cardiovascular-kidney outcomes, providing valuable guidance for clinical diagnosis, treatment decisions, and ultimately improving patient prognosis., conditionsModule conditions: Chronic Kidney Diseases, conditions: Coronary Heart Disease, conditions: Lipid Metabolism Disorders, designModule studyType: OBSERVATIONAL, designInfo observationalModel: COHORT, timePerspective: PROSPECTIVE, enrollmentInfo count: 470, type: ESTIMATED, armsInterventionsModule interventions name: lipid metabolomics, outcomesModule primaryOutcomes measure: Incidence of cardiovascular adverse events, primaryOutcomes measure: Incidence of Renal composite endpoint event, secondaryOutcomes measure: Incidence of All-cause mortality, secondaryOutcomes measure: Incidence of Repeat revascularization, secondaryOutcomes measure: Incidence of bleeding, eligibilityModule sex: ALL, minimumAge: 18 Years, maximumAge: 80 Years, stdAges: ADULT, stdAges: OLDER_ADULT, contactsLocationsModule locations facility: China-Japan Friendship Hospital, status: RECRUITING, city: Beijing, state: Beijing, country: China, contacts name: Chen Qiang, MD, role: CONTACT, phone: +86 13882712184, email: dawangchen@163.com, geoPoint lat: 39.9075, lon: 116.39723, hasResults: False