Evidence map›Paper›PMID 36411302›Full record

ArticleScientific reports2022

Triglyceride-glucose index is significantly associated with the risk of hyperuricemia in patients with diabetic kidney disease.

Qiuhong Li, Xian Shao, Saijun Zhou, Zhuang Cui, Hongyan Liu, Tongdan Wang, Xiaoguang Fan, Pei Yu

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
4.6field-weighted citation impact, top 4% 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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 32 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Qiuhong LiNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
Xian ShaoNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
Saijun ZhouNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
Zhuang CuiDepartment of Epidemiology and Health Statistics, Tianjin Medical University, Tianjin, 300010, China.
Hongyan LiuNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
Tongdan WangNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
Xiaoguang FanDepartment of Nephrology, Henan Provincial People's Hospital, Department of Nephrology of Central China Fuwai Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou Henan, 450003, China.
Pei YuNHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China. peiyu@tmu.edu.cn.ORCID 0000-0001-6137-5824
Tianjin Medical University · CNHenan Provincial People's Hospital · CNSecond Hospital of Tianjin Medical University · CN

Funding

China International Medical Exchange Foundation Key Fund Project Z-2017-26-1902Scientific Research Funding of Tianjin Medical University Chu Hsien-I Memorial Hospital ZXY-ZDSYSZD-1Tianjin Health Research Project RC20175Tianjin Municipal Health Care Commission Scientific Research Fund Project ZC20128Tianjin Science and Technology Plan Project Public Health Science and Technology Major Special Project 21ZXGWSY00100Whitehorn Diabetes Research Fund Project G-X-2019-56
6 · The paper itself

Abstract

Triglyceride-glucose (TyG) index has been proposed to be a simple, economical, and reliable marker of insulin resistance. We aimed to investigate whether TyG is an independent predictor of hyperuricemia in diabetic kidney disease (DKD) populations by conducting a cross-sectional and longitudinal study. A total of 6,471 patients were enrolled in cross-sectional analysis, and 3,634 patients without hyperuricemia at the baseline were included in longitudinal analysis and were followed up for a median of 23.0 months. Hyperuricemia was categorized as a serum uric acid level ≥ 420 umol/L (7 mg/dL). In this study, 19.58% of participants had hyperuricemia. In the cross-sectional analysis, multivariate logistics regression analysis showed that the ORs (95% CI) for hyperuricemia in the second, third, and fourth TyG quartiles were 1.40 (95% CI 0.73-2.65), 1.69 (95% CI 0.90-3.18), and 4.53 (95% CI 2.39-8.57), respectively, compared with the first quartile. Longitudinally, the Kaplan-Meier survival analysis showed that higher TyG levels predicted higher incidence of hyperuricemia. Multivariate Cox regression model revealed that the hazard ratios for hyperuricemia in the upper quartiles of the TyG index were 1.69 (95% CI 0.97-2.93), 2.23 (95% CI 1.33-3.75), and 2.50 (95% CI 1.46-4.27), respectively, compared with the first quartile. Moreover, the subgroup analyses revealed that the relationship between TyG levels and hyperuricemia was robust in DKD patients. Our findings indicate a significant independent correlation between the TyG index and the risk of hyperuricemia in DKD patients.

Indexed as

Diabetes MellitusDiabetic NephropathiesHyperuricemiaBlood GlucoseCross-Sectional StudiesGlucoseHumansLongitudinal StudiesRisk FactorsTriglyceridesUric AcidBlood GlucoseGlucoseTriglyceridesUric Acid

Identifiers

PMID36411302
PMCPMC9678876
OpenAlexW4309656801

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.