The nonlinear association between Body Roundness Index and left ventricular diastolic dysfunction in type 2 diabetes

BRI is nonlinearly associated with LVDD risk in T2DM, with a threshold effect at BRI = 8.1. The association is stronger in patients with diabetic kidney disease, suggesting that BRI could serve as a valuable marker for the stratification and prevention of LVDD in high-risk populations.

Authors

Institutions

Publication Details

Journal
Frontiers in Endocrinology
Published
2026-02-25
DOI
https://doi.org/10.3389/fendo.2026.1709785
Primary Topic
Cardiovascular Function and Risk Factors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The nonlinear association between Body Roundness Index and left ventricular diastolic dysfunction in type 2 diabetes

Y. Q. Li, Yifei Ma, Nailong Yang, Zhiliang Wang
Frontiers in Endocrinology
Cardiovascular Function and Risk Factors
article

The nonlinear association between Body Roundness Index and left ventricular diastolic dysfunction in type 2 diabetes

Y. Q. Li, Yifei Ma, Nailong Yang, Zhiliang Wang
article en

Abstract

BRI is nonlinearly associated with LVDD risk in T2DM, with a threshold effect at BRI = 8.1. The association is stronger in patients with diabetic kidney disease, suggesting that BRI could serve as a valuable marker for the stratification and prevention of LVDD in high-risk populations.

Frontiers in EndocrinologyVol. 17
Qingdao University (CN), Affiliated Hospital of Qingdao University (CN)
Openalex Percentile: Top 48%
Cardiovascular Function and Risk Factors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.