Raw Data Library
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
Green Science
​
​
EN
Kurumsal BaşvuruSign inGet started
​
​

About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User GuideGreen Science

Language

Kurumsal Başvuru

Sign inGet started
RDL logo

Verified research datasets. Instant access. Built for collaboration.

Navigation

About

Aims and Scope

Advisory Board Members

More

Who We Are?

Contact

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2026 Raw Data Library. All rights reserved.
PrivacyTermsContact
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. Predictive value of TG/HDL-C and GFR-adjusted uric acid levels on cardiovascular mortality: the URRAH study

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Article
en
2025

Predictive value of TG/HDL-C and GFR-adjusted uric acid levels on cardiovascular mortality: the URRAH study

0 Datasets

0 Files

en
2025
Vol 24 (1)
Vol. 24
DOI: 10.1186/s12944-025-02440-w

Get instant academic access to this publication’s datasets.

Create free accountHow it works

Frequently asked questions

Is access really free for academics and students?

Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.

How is my data protected?

Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.

Can I request additional materials?

Yes, message the author after sign-up to request supplementary files or replication code.

Advance your research today

Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.

Get free academic accessLearn more
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration
Access Research Data

Join our academic network to download verified datasets and collaborate with researchers worldwide.

Get Free Access
Institutional SSO
Secure
This PDF is not available in different languages.
No localized PDFs are currently available.
Gianfranco Parati
Gianfranco Parati

Institution not specified

Verified
Elisa Russo
Francesca Viazzi
Roberto Pontremoli
+43 more

Abstract

Both IR and SUA/GFR ratio independently predict CV mortality, regardless of age, gender, BMI, diabetes, hypertension and statin use. The joint effect of the TG/HDL-C ratio and the elevated SUA/GFR ratio was greater than the presence of each single risk factor on CV mortality. This highlights the importance of monitoring these markers to better assess cardiovascular risk.

How to cite this publication

Elisa Russo, Francesca Viazzi, Roberto Pontremoli, Fabio Angeli, Carlo M. Barbagallo, Bruno G. Berardino, Michele Bombelli, Federica Cappelli, Edoardo Casiglia, Rosario Cianci, Michele Ciccarelli, Arrigo F.G. Cicero, Massimo Círillo, Pietro Cirillo, Lanfranco D’Elia, Giovambattista Desideri, Claudio Ferri, Ferruccio Galletti, Loreto Gesualdo, Cristina Giannattasio, Guıdo Grassı, Guido Iaccarino, Egidio Imbalzano, Luciano Lippa, Francesca Mallamaci, Alessandro Maloberti, Stefano Masi, Maria Masulli, Alberto Mazza, Alessandro Mengozzi, María Lorenza Muiesan, Pietro Nazzaro, Paolo Palatini, Gianfranco Parati, Fosca Quarti‐Trevano, Marcello Rattazzi, Gianpaolo Reboldi, Giulia Rivasi, Massimo Salvetti, Valérie Tikhonoff, Giuliano Tocci, Andrea Ungar, Paolo Verdecchia, Agostino Virdis, Massimo Volpe, Claudio Borghi (2025). Predictive value of TG/HDL-C and GFR-adjusted uric acid levels on cardiovascular mortality: the URRAH study. , 24(1), DOI: https://doi.org/10.1186/s12944-025-02440-w.

Related publications

Why join Raw Data Library?

Quality

Datasets shared by verified academics with rich metadata and previews.

Control

Authors choose access levels; downloads are logged for transparency.

Free for Academia

Students and faculty get instant access after verification.

Publication Details

Type

Article

Year

2025

Authors

46

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1186/s12944-025-02440-w

Join Research Community

Access datasets from 50,000+ researchers worldwide with institutional verification.

Get Free Access