Evidence map›Paper›PMID 40517339›Full record

ArticleDiabetes therapy : research, treatment and education of diabetes and related disorders2025

The Predictive Value of Insulin Resistance Surrogates for Diabetic Kidney Disease in Type 2 Diabetes Mellitus.

Qiuying Sun, Meiru Zhao, Xiaonan Wang, Jiangteng Wang, Yaxi Yang, Lin Liu, Di Zhu, Xu Li, Qingbo Guan, Xu Zhang

Abstract read
In one paragraph

Article in Diabetes therapy : research, treatment and education of diabetes and related disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Insulin Resistance and Inflammation.International journal of molecular sciences · 2026
    Review
  7. Article
  8. Article
  9. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Qiuying SunKey Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Ministry of Education, Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China.
Meiru ZhaoDepartment of Endocrinology, Affiliated Qingdao Third People's Hospital, Qingdao University, Qingdao, 266100, Shandong, China.
Xiaonan WangDepartment of Endocrinology and Nephropathy, Boxing People's Hospital, Boxing, 256500, Shandong, China.
Jiangteng WangKey Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Ministry of Education, Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China.
Yaxi YangKey Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Ministry of Education, Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China.
Lin LiuKey Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Ministry of Education, Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China.
Di ZhuKey Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Ministry of Education, Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China.
Xu LiKey Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Ministry of Education, Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China.
Qingbo GuanKey Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Ministry of Education, Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China.
Xu ZhangKey Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Ministry of Education, Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China. zhangxu_lunwen1@126.com.

Funding

Key Technology Research and Development Program of Shandong Province No. 2021LCZX01Shandong Provincial Scientific Research Foundation of China No. 2006BS03012Shandong Provincial Scientific Research Foundation of China No. 2013GSF11814The Science and Technology Development Program of Shandong Province (No. 2009HW058
6 · The paper itself

Abstract

introductionInsulin resistance (IR) is a major feature of type 2 diabetes mellitus (T2DM) and plays a crucial role in the accelerated progression of diabetic kidney disease (DKD). It has been found that surrogates of IR are of high value in assessing IR status. This study aims to evaluate the associations between surrogates of IR and DKD in T2DM.

methodsA total of 1026 patients with T2DM from January 2021 to February 2022 were selected in our final analysis. Logistic regression analysis and the receiver operating characteristic (ROC) curve analysis were performed to assess the correlation between IR surrogates and DKD.

resultsThe levels of triglyceride glucose-waist circumference (TyG-WC), triglyceride glucose-waist to height ratio (TyG-WHtR), visceral adiposity index (VAI), and lipid accumulation product (LAP) were significantly higher in the microalbuminuria group and macroalbuminuria group compared with the normoalbuminuria group (P < 0.05). The results of multivariate logistic regression analysis showed that the highest quartile of triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-C), triglyceride glucose (TyG) index, TyG-WHtR, TyG-WC, LAP, and VAI were significantly correlated with DKD (all P < 0.05). The ROC curves and results showed that TyG area under the curve (AUC) > VAI AUC > TG/HDL-C AUC > TyG-WHtR AUC > LAP AUC > 0.7 > TyG-WC AUC > metabolic index of insulin resistance (METS-IR) AUC > 0.6 > triglyceride glucose-body mass index (TyG-BMI) AUC > 0.5.

conclusionsThe predictive value of IR surrogates for DKD in T2DM varies. TG/HDL-C, TyG, TyG-WHtR, LAP, and VAI can effectively predict DKD and are expected to be simple and economic biological indicators of DKD risk.

Indexed as

Diabetic kidney diseaseInsulin resistanceType 2 diabetes mellitus

Identifiers

PMID40517339
PMCPMC12317950

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.