Publication Name	World Journal of Clinical Cases
Manuscript ID	108380
Country	Japan

Category	Medicine, General & Internal
Manuscript Type	Minireviews
Article Title	Mini-review on insulin resistance assessment: Advances in surrogate indices and clinical applications
Manuscript Source	Invited Manuscript
All Author List	Kengo Moriyama
Funding Agency and Grant Number
Corresponding Author	Kengo Moriyama, MD, PhD, Professor, Department of Clinical Health Science, Tokai University School of Medicine, 1838 Ishikawa-machi, Hachioji 1920032, Tōkyō, Japan. kengomoriyama@tokai.ac.jp
Key Words	Insulin resistance; Homeostasis model assessment of insulin resistance; Quantitative insulin sensitivity check index; Matsuda index; Triglyceride-glucose index; Surrogate markers; Metabolic disorders; Diabetes; Cardiovascular disease; Risk assessment
Core Tip	Surrogate indices for insulin resistance (IR) are receiving growing validation in the international scientific literature. While gold standard methods remain the most accurate, their complexity limits clinical applicability. Indices such as the homeostasis model assessment of IR, the quantitative insulin sensitivity check index, and the Matsuda index offer valuable estimates of IR, while emerging indices like the triglyceride-glucose index are gaining attention. Further validation across diverse populations is required. Integrating these indices into routine practice may enhance metabolic risk assessment and preventive strategies.
Citation	Moriyama K. Mini-review on insulin resistance assessment: Advances in surrogate indices and clinical applications. World J Clin Cases 2025; In press

Received	2025-04-13 12:07
Peer-Review Started	2025-04-13 12:07
To Make the First Decision
Return for Revision	2025-05-12 02:12
Revised	2025-05-24 05:41
Second Decision	2025-08-07 02:44
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-08-08 09:53
Articles in Press	2025-08-08 09:53
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2307-8960 (online)
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