Prediction of UA/SOD Ratio as a Biomarker of Oxidative Stress in Atrial Fibrillation

Launched by YINGLONG HOU · Nov 1, 2023

Keywords

ClinConnect Summary

This clinical trial is looking to understand how certain substances in the body, specifically uric acid and superoxide dismutase, can help predict oxidative stress in patients with atrial fibrillation (AF), a type of irregular heartbeat. The goal is to improve the diagnosis and treatment of AF by using these substances as biomarkers, which are indicators that can provide valuable information about the condition. This research could lead to better prevention and management strategies for people who experience AF.

To participate in this study, individuals must be between the ages of 65 and 74 and have been hospitalized for AF between January 2018 and December 2020. Eligible participants will have their heart rhythm assessed using tests like electrocardiograms (ECG) or Holter monitoring, which records heart activity over 24 hours. However, people with severe heart, liver, or kidney issues, certain types of cancers, or missing important health data will not be included. Participants can expect to contribute to important research that might enhance our understanding of atrial fibrillation and help improve future care for patients.

Gender

ALL

Eligibility criteria

• • Inclusion Criteria: This retrospective study enrolled all hospitalized patients from January 2018 to December 2020 at the Department of Cardiology in The First Affiliated Hospital of Shandong First Medical University. The diagnosis of AF was based on 12-lead electrocardiography (ECG) or 24-hour Holter monitoring, and classification was based on the published 2020 ESC guidelines for the diagnosis and management of AF.
• Exclusion Criteria:
• • 1. acute heart failure and acute myocardial infarction;
• • 2. severe liver or kidney dysfunction (with aspartate aminotransferase or alanine aminotransferase levels three times higher than normal and estimated glomerular filtration rate \<30 ml/ (min\*1.73 m2));
• • 3. malignant tumors;
• • 4. missing data of laboratory indicators at baseline.