Evidence map›Paper›PMID 33319507›Full record

ArticleJournal of diabetes investigation2021

Association between the triglyceride-glucose index and diabetic nephropathy in patients with type 2 diabetes: A cross-sectional study.

Li Liu, Rui Xia, Xiaoqing Song, Benping Zhang, Wentao He, Xinrong Zhou, Shengzhong Li, Gang Yuan

Open access · goldAbstract read
In one paragraph

Article in Journal of diabetes investigation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed, 2 pooled it
5.1field-weighted citation impact, top 3% of its field
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

71 citing papers in PubMed, 2 syntheses or guidelines pooled it, 91 citations in OpenAlex.

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11 more citing papers are in PubMed but not listed here.

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

8 authors at 2 institutions in 1 country.

Li LiuDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Rui XiaDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Xiaoqing SongDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Benping ZhangDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.ORCID https://orcid.org/0000-0001-9107-6833
Wentao HeDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Xinrong ZhouDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Shengzhong LiDepartment of Surgery, Wuhan Jinyintan Hospital, Wuhan, Hubei, China.
Gang YuanDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.ORCID https://orcid.org/0000-0002-8672-8849
Tongji Hospital · CNJinyintan Hospital · CN

Funding

China Diabetes Young Scientific Talent Research Project of China International Medical Foundation 2018-N-01National Natural Science Foundation of China 81700727National Natural Science Foundation of China 81770817
6 · The paper itself

Abstract

AIMS/

introductionThe triglyceride-glucose (TyG) index has been proposed as a reliable and simple marker of insulin resistance. We investigated the association between TyG index and diabetic nephropathy (DN) in patients with type 2 diabetes. MATERIALS AND

methodsA consecutive case series of 682 adult patients with type 2 diabetes hospitalized in the Department of Endocrinology at the Tongji Hospital (Wuhan, Hubei, China) from January 2007 to December 2009 was included in this cross-sectional analysis. Receiver operating characteristics curve analysis, correlation analysis and multiple logistic regression analysis were carried out.

resultsA total of 232 (34.0%) participants were identified with DN. Compared with the non-DN group, the DN group had longer disease duration, and higher bodyweight, systolic blood pressure, diastolic blood pressure, glycated hemoglobin, triglycerides, total cholesterol, serum uric acid, 24 h-urinary albumin, TyG index and homeostasis model assessment 2 estimates for insulin resistance (HOMA2-IR; P < 0.05 for each). The TyG index with an optimal cut-off point >9.66 showed a higher area under the receiver operating characteristic curve of 0.67 (P = 0.002) than HOMA2-IR (area under the curve 0.61, P = 0.029) on receiver operating characteristic curve analysis for DN identification. Additionally, the TyG index positively correlated with the levels of metabolic indicators (bodyweight, glycated hemoglobin, triglycerides, total cholesterol, serum uric acid, fasting glucose and HOMA2-IR) and natural logarithmic 24 h-urinary albumin (P < 0.05 for each), but not natural logarithm of estimated glomerular filtration rate. On multiple regression analysis, an increased TyG index was shown to be an independent risk factor (odds ratio 1.91, P = 0.001) for DN.

conclusionsThe TyG index was independently associated with DN in patients with type 2 diabetes, and was a better marker than HOMA2-IR for identification of DN in type 2 diabetes patients.

Indexed as

Blood GlucoseInsulin ResistanceCross-Sectional StudiesDiabetes Mellitus, Type 2Diabetic NephropathiesFemaleHumansMaleMiddle AgedRetrospective StudiesTriglyceridesBlood GlucoseTriglyceridesDiabetic nephropathyInsulin resistanceTriglyceride-glucose index

Identifiers

PMID33319507
PMCPMC8015837
OpenAlexW3045196970

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.