Evidence map›Paper›PMID 39364793›Full record

ArticleJournal of diabetes2024

Assessing and predicting type 2 diabetes risk with triglyceride glucose-body mass index in the Chinese nondiabetic population-Data from long-term follow-up of Da Qing IGT and Diabetes Study.

Haixu Wang, Siyao He, Jinping Wang, Xin Qian, Bo Zhang, Zhiwei Yang, Bo Chen, Guangwei Li, Qiuhong Gong, Da Qing Diabetes Prevention Outcome Study Group

Abstract read
In one paragraph

Article in Journal of diabetes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

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0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
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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

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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

9 citing papers in PubMed, 1 synthesis or guideline 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

10 authors.

Haixu WangCenter of Endocrinology, National Center of Cardiology &Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Siyao HeCenter of Endocrinology, National Center of Cardiology &Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jinping WangDepartment of Cardiology, Da Qing Oilfield General Hospital, Da Qing, China.
Xin QianCenter of Endocrinology, National Center of Cardiology &Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0003-2961-3380
Bo ZhangDepartment of Endocrinology, China-Japan Friendship Hospital, Beijing, China.ORCID https://orcid.org/0000-0003-3060-7850
Zhiwei YangDepartment of Cardiology, Da Qing Oilfield General Hospital, Da Qing, China.
Bo ChenDivision of Non-Communicable Disease Control and Community Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Guangwei LiCenter of Endocrinology, National Center of Cardiology &Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0003-1061-7293
Qiuhong GongCenter of Endocrinology, National Center of Cardiology &Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0002-8781-1214
Da Qing Diabetes Prevention Outcome Study Group

Funding

and China-Japan Friendship HospitalCGH CDC HHS U19 GH000636Chinese Center for Disease Control and Prevention 5U19GH000636-05Da Qing First HospitalDa Qing Oilfield General HospitalMinistry of Public Health of the People's Republic of ChinaNational Center of Cardiology & Fuwai HospitalWorld BankWorld Health Organization U58/CCU424123-01-02
6 · The paper itself

Abstract

aimsWe intended to characterize the superiority of triglyceride glucose-body mass index (TyG-BMI) in predicting type 2 diabetes mellitus (T2DM) compared with triglyceride glucose (TyG) and homeostatic model assessment for insulin resistance (HOMA-IR).

methodsA total of 699 nondiabetic participants in the Da Qing IGT and Diabetes Study were involved in the present analysis and classified according to the median of baseline TyG-BMI, namely the G1 (low TyG-BMI) and G2 (high TyG-BMI) groups. Information on developing diabetes was assessed from 1986 to 2020.

resultsDuring the 34-year follow-up, after adjustment for confounders, the G2 group had a higher risk of developing type 2 diabetes than the G1 group (hazard ratio [HR]: 1.92, 95% confidence interval [CI]: 1.51-2.45, p < 0.0001). Restricted cubic spline analyses showed that increased TyG-BMI was linearly related to higher risks of type 2 diabetes (p for non-linearity>0.05). Time-dependent receiver operator characteristics curves suggested that TyG-BMI exhibited higher predictive ability than TyG (6-year: area under the curve [AUC]

conclusionsIn this post hoc study, higher TyG-BMI was associated with an increased risk of type 2 diabetes and demonstrated better predictability than TyG and HOMA-IR, favoring the application of TyG-BMI as a potential tool for evaluating the risk of type 2 diabetes in clinical practice.

Indexed as

Blood GlucoseBody Mass IndexDiabetes Mellitus, Type 2TriglyceridesAdultAgedChinaEast Asian PeopleFemaleFollow-Up StudiesGlucose IntoleranceHumansInsulin ResistanceMaleMiddle AgedPrognosisBlood GlucoseTriglyceridesDa Qing Studypredictabilitytriglyceride glucose‐body mass indextype 2 diabetes

Identifiers

PMID39364793
PMCPMC11450669

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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.