Actively Recruiting

Age: 18Years - 80Years
All Genders
Healthy Volunteers
NCT06383208

Cardiovascular-Renal Adverse Prognosis Assessment System for Coronary Heart Disease With Chronic Kidney Disease Based on Metabolomics

Led by China-Japan Friendship Hospital · Updated on 2024-04-25

470

Participants Needed

1

Research Sites

156 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

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.

CONDITIONS

Official Title

Cardiovascular-Renal Adverse Prognosis Assessment System for Coronary Heart Disease With Chronic Kidney Disease Based on Metabolomics

Who Can Participate

Age: 18Years - 80Years
All Genders
Healthy Volunteers

Eligibility Criteria

Eligible

You may qualify if you...

  • Age between 18 and 80 years old
  • Diagnosed with coronary heart disease during hospitalization by coronary angiography, including STEMI, NST-ACS, or stable angina
  • Known and clarified kidney function status
  • Chronic kidney disease defined as eGFR less than 60 ml/min/1.73 m² or eGFR greater or equal to 60 ml/min/1.73 m² with urinary albumin-to-creatinine ratio of 30 mg/g or higher, lasting more than 3 months
Not Eligible

You will not qualify if you...

  • Pregnancy or breastfeeding
  • Severe valve disease or mechanical complications needing surgery
  • Severe psychiatric illness or other issues preventing follow-up
  • Severe blood disorders or end-stage cancers
  • Previous kidney transplant or long-term dialysis
  • Severe liver disease (Child-Pugh class C)
  • Recent acute kidney failure dialysis treatment within 12 weeks before enrollment
  • Severe chronic lung disease needing long-term ventilation or awaiting lung transplant
  • Life expectancy less than 1 year

AI-Screening

AI-Powered Screening

Complete this quick 3-step screening to check your eligibility

1
2
3
+1

Trial Site Locations

Total: 1 location

1

China-Japan Friendship Hospital

Beijing, Beijing Municipality, China

Actively Recruiting

Loading map...

Research Team

C

Chen Qiang

CONTACT

How is the study designed?

Study Type

OBSERVATIONAL

Masking

N/A

Allocation

N/A

Model

N/A

Primary Purpose

N/A

Number of Arms

0

Not the Right Trial for You?

Explore thousands of other clinical trials that might be a better match.
Sign up to get personalized trial recommendations delivered to your inbox.

Already have an account? Log in here