Evidence map›Paper›PMID 38907937›Full record

ArticleDiabetes therapy : research, treatment and education of diabetes and related disorders2024

Triglyceride Glucose Index for the Detection of Diabetic Kidney Disease and Diabetic Peripheral Neuropathy in Hospitalized Patients with Type 2 Diabetes.

Zhihui Tu, Juan Du, Xiaoxu Ge, Wenfang Peng, Lisha Shen, Lili Xia, Xiaohong Jiang, Fan Hu, Shan Huang

Abstract read
In one paragraph

Article in Diabetes therapy : research, treatment and education of diabetes and related disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 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

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

9 authors.

Zhihui Tu *Department of Endocrinology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111, Xianxia Road, Changning District, Shanghai, China.
Juan Du *Department of Endocrinology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111, Xianxia Road, Changning District, Shanghai, China.
Xiaoxu Ge *Department of Endocrinology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111, Xianxia Road, Changning District, Shanghai, China.
Wenfang PengDepartment of Endocrinology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111, Xianxia Road, Changning District, Shanghai, China.
Lisha ShenDepartment of Endocrinology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111, Xianxia Road, Changning District, Shanghai, China.
Lili XiaDepartment of Endocrinology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111, Xianxia Road, Changning District, Shanghai, China.
Xiaohong JiangDepartment of Endocrinology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111, Xianxia Road, Changning District, Shanghai, China. jxh1653@shtrhospital.com.
Fan HuShanghai Jiao Tong University School of Medicine, No. 227, Chongqing South Road, Huangpu District, Shanghai, China. joyking2003@163.com.
Shan HuangDepartment of Endocrinology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No. 1111, Xianxia Road, Changning District, Shanghai, China. hs1147@126.com.ORCID http://orcid.org/0000-0001-8125-953X

Funding

Changning District Committee of Science and Technology CNKW2017Y06Master and Doctor innovation talent base for endocrine and metabolic diseases RCJD2021S03Natural Science Foundation Project of Shanghai Scientific and technological innovation plan No.22ZR1457000Research Fund of Shanghai Tongren Hospital, Shanghai Jiaotong University School of Medicine TRYJ2021LC07Rising Star Programme in Tongren Hospital TRKYRC-xx202209
6 · The paper itself

Abstract

introductionThe triglyceride-glucose index (TyG) has been identified as a dependable and simple indicator marker of insulin resistance (IR). Research has demonstrated a correlation between macrovascular complications and TyG. However, limited research exists regarding the relationship between TyG and diabetic microvascular complications. Consequently, the objective of this study is to investigate the association between TyG and diabetic kidney disease (DKD) and diabetic peripheral neuropathy (DPN).

methodsThis is a cross-sectional, observational study. A total of 2048 patients from Tongren Hospital, Shanghai Jiao Tong University School of Medicine were enrolled. The primary outcomes are DKD and DPN. Quantile regression analysis was employed to investigate the implicit factors of TyG quartiles. Subsequently, based on implicit factors, logistic regression models were constructed to further examine the relationship between TyG and DKD and DPN.

resultsIn the baseline, TyG exhibited higher values across patients with DKD, DPN, and co-existence of DKD and DPN (DKD + DPN) in type 2 diabetes (T2D). Univariate logistic regressions demonstrated a significant association between an elevated TyG and an increased risk of DKD (OR = 1.842, [95% CI] 1.317-2.578, P for trend < 0.01), DPN (OR = 1.516, [95% CI] 1.114-2.288, P for trend < 0.05), DKD + DPN (OR = 2.088, [95% CI] 1.429-3.052, P for trend < 0.05). Multivariable logistic regression models suggested a statistically significant increase in the risk of DKD (OR = 1.581, [95% CI] 1.031-2.424, p < 0.05), DKD + DPN (OR = 1.779, [95% CI] 1.091-2.903, p < 0.05) after adjusting the implicit factors of TyG quartiles. However, no significant relationship was observed between TyG and DPN in the multivariable regression analysis.

conclusionsElevated TyG was significantly associated with an increased risk of DKD in T2D, but no significant relationship was shown with DPN. This finding provided further evidence for the clinical significance of integrating TyG into the initial assessment of diabetic microvascular complications.

Indexed as

Diabetic kidney diseaseDiabetic peripheral neuropathyInsulin resistanceTriglyceride–glucose indexType 2 diabetes

Identifiers

PMID38907937
PMCPMC11263315

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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 OpenQuestion graph.