Comparing surrogate indexes for insulin resistance as predictors of type 2 diabetes

Surrogate measures based on OGTTs are best for predicting T2D, while measures based on fasting insulin perform better than those that do not measure insulin.

Authors

Institutions

Publication Details

Journal
The Journal of Clinical Endocrinology & Metabolism
Published
2026-03-07
DOI
https://doi.org/10.1210/clinem/dgag101
Citations
1
Primary Topic
Diabetes, Cardiovascular Risks, and Lipoproteins
Type
article
Field-Weighted Citation Impact
30.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparing surrogate indexes for insulin resistance as predictors of type 2 diabetes

Elsa Vazquez Arreola, Jonathan Krakoff, R. L. Hanson, Laura Vazquez et al.
1 citations
The Journal of Clinical Endocrinology & Metabolism
Diabetes, Cardiovascular Risks, and Lipoproteins
30.73
article

Comparing surrogate indexes for insulin resistance as predictors of type 2 diabetes

Elsa Vazquez Arreola, Jonathan Krakoff, R. L. Hanson, Laura Vazquez, MURUGASU NAGUL
article en
1 citations

Abstract

Surrogate measures based on OGTTs are best for predicting T2D, while measures based on fasting insulin perform better than those that do not measure insulin.

The Journal of Clinical Endocrinology & Metabolism
National Institute of Diabetes and Digestive and Kidney Diseases (US)
Zero hunger
Openalex Percentile: Top 0%
Diabetes, Cardiovascular Risks, and Lipoproteins
30.73
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.