Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

Association of transglutaminase-2 with contrast-induced acute kidney injury in Chinese patients with acute coronary syndrome: a prospective cohort study.

Created on 10 Aug 2026

Authors

Ruixue Yao, Jie Zhang, Wenkang Zhang, Yuhan Qin, Yong Qiao, Dong Wang, Gaoliang Yan, Chengchun Tang

Published in

Annals of medicine. Volume 58. Issue 1. Pages 2712061. Epub Aug 10, 2026.

Abstract

To investigate the dynamic changes in serum and urinary Transglutaminase-2 (TG2) levels in acute coronary syndrome (ACS) patients and their association with contrast-induced acute kidney injury (CI-AKI), thereby providing novel clinical evidence for risk prediction of CI-AKI.
This single-center prospective cohort study consecutively enrolled ACS patients hospitalized in the Zhongda Hospital Affiliated to Southeast University, who underwent coronary angiography (CAG) between December 2023 and December 2024. Serum and urinary TG2 levels were measured before and after CAG using enzyme-linked immunosorbent assay. Multivariable logistic regression was performed to identify independent risk factors for CI-AKI, and a predictive model was constructed.
A total of 550 ACS patients were included, of whom 59 (10.7%) developed CI-AKI. Lasso regression analysis further confirmed that the differences between preoperative and postoperative serum TG2 (ΔsTG2) and urinary TG2 (ΔuTG2) were independent risk factors for CI-AKI (both p < 0.001). The logistic regression prediction model incorporating ΔsTG2, ΔuTG2, and other risk factors achieved area under the curve values of 0.870 (95% confidence interval [CI]: 0.818-0.921) in the training set and 0.818 (95% CI: 0.741-0.895) in the test set, indicating good predictive performance.
In ACS patients undergoing CAG, elevated serum and urinary TG2 levels and greater peri-procedural changes in these levels are closely associated with the occurrence of CI-AKI. Detecting TG2 levels, particularly their dynamic changes, may serve as an effective biomarker for predicting the risk of CI-AKI.

PMID:
42573605
Bibliographic data and abstract were imported from PubMed on 10 Aug 2026.

Read full publication at:
Please sign in to see all details.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Reviewers' rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 5
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement