Evidence mapPaperPMID 40119385Full record

ArticleCardiovascular diabetology2025

Association between triglyceride glucose-body mass index and the trajectory of cardio-renal-metabolic multimorbidity: insights from multi-state modelling.

Haoxian Tang, Jingtao Huang, Xuan Zhang, Xiaojing Chen, Qinglong Yang, Nan Luo, Hanyuan Lin, Jianan Hong, Shiwan Wu, Cuihong Tian and 9 more

Abstract read
In one paragraph

Article in Cardiovascular diabetology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
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

19 authors.

Haoxian TangShantou University Medical College, Shantou, Guangdong, China.
Jingtao HuangShantou University Medical College, Shantou, Guangdong, China.
Xuan ZhangShantou University Medical College, Shantou, Guangdong, China.
Xiaojing ChenShantou University Medical College, Shantou, Guangdong, China.
Qinglong YangShantou University Medical College, Shantou, Guangdong, China.
Nan LuoShantou University Medical College, Shantou, Guangdong, China.
Hanyuan LinShantou University Medical College, Shantou, Guangdong, China.
Jianan HongDepartment of Cardiology, The First Affiliated Hospital of Shantou University Medical College, No. 57 Changping Road, Shantou, 515000, Guangdong, China.
Shiwan WuShantou University Medical College, Shantou, Guangdong, China.
Cuihong TianShantou University Medical College, Shantou, Guangdong, China.
Mengyue LinShantou University Medical College, Shantou, Guangdong, China.
Junshuang TangShantou University Medical College, Shantou, Guangdong, China.
Jiasheng WenShantou University Medical College, Shantou, Guangdong, China.
Pan ChenShantou University Medical College, Shantou, Guangdong, China.
Liwen JiangShantou University Medical College, Shantou, Guangdong, China.
Youti ZhangDepartment of Cardiology, Jiexi People's Hospital, Jieyang, Guangdong, China.
Kaihong YiDepartment of Medical Quality Management, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Xuerui TanDepartment of Cardiology, The First Affiliated Hospital of Shantou University Medical College, No. 57 Changping Road, Shantou, 515000, Guangdong, China. doctortxr@126.com.
Yequn ChenDepartment of Cardiology, The First Affiliated Hospital of Shantou University Medical College, No. 57 Changping Road, Shantou, 515000, Guangdong, China. gdcycyq@163.com.

Funding

2020 Li Ka Shing Foundation Cross-Disciplinary Research Grant 2020LKSFG19B"Dengfeng Project" for the construction of high-level hospitals in Guangdong Province - the First Affiliated Hospital of Shantou University Medical College 2020Fund from National Health Commission Medical and Health Science and Technology Development and Research Center WKZX2022JG0138Grant for Key Disciplinary Project of Clinical Medicine under the High-level University Development Program, Guangdong, China 2024-2025Innovation Team Project of Guangdong Universities, China 2024KCXTD019National Health Commission Hospital Management Research 2023 Medical Quality (Evidence-based) Management Research Project YLZLXZ23G121Provincial Science and Technology Special Fund of Guangdong in 2021 2021-88-53Provincial Science and Technology Special Fund of Guangdong in 2022 2022-124-6Science and Technology project in Guangdong Province 2021010303
6 · The paper itself

Abstract

backgroundAlthough some studies have examined the association between the triglyceride glucose-body mass index (TyG-BMI) and cardiovascular outcomes in the cardio-renal-metabolic (CRM) background, none have explored its role in the progression of CRM multimorbidity. In addition, prior research is limited by small sample sizes and a failure to account for the competitive effects of other CRM diseases.

methodsIn this study, data obtained from the large-scale, prospective UK Biobank cohort were used. CRM multimorbidity was defined as the new-onset of ischemic heart disease, type 2 diabetes mellitus, or chronic kidney disease during follow-up. Multivariable Cox regression was used to analyse the independent association between TyG-BMI and each CRM multimorbidity (first, double, or triple CRM diseases). The C-statistic was calculated for each model, and a restricted cubic spline was applied to assess the dose-response relationship. A multi-state model was used to investigate the association between TyG-BMI and the trajectory of CRM multimorbidity (from baseline [without CRM disease] to the first CRM disease, the first CRM disease to double disease, and double disease to triple disease), with disease-specific analyses.

resultsThis study included 349,974 participants, with a mean age of 56.05 (standard deviation [SD], 8.08), 55.93% of whom were female. Over a median follow-up of approximately 14 years, 56,659 (16.19%) participants without baseline CRM disease developed at least one CRM disease, including 8451 (14.92%) who progressed to double CRM disease and 789 (9.34%) who further developed triple CRM disease. In the crude model, each SD increase in TyG-BMI was associated with a 47% higher risk of the first CRM disease, a 72% higher risk of double CRM disease, and a 95% higher risk of triple CRM disease, with C-statistics of 0.625, 0.694, and 0.764, respectively. Multi-state model analysis showed a 32% increased risk of new CRM disease, a 24% increased risk of progression to double CRM disease, and a 23% increased risk of further progression for those with double CRM diseases. TyG-BMI was significantly associated with the onset of all individual first CRM diseases (except for stroke) and with the transition to double CRM disease. Significant interactions were also observed, but TyG-BMI remained significantly associated with CRM multimorbidity across subgroups. Sensitivity analyses, including varying time intervals for entering states and an expanded CRM definition (including atrial fibrillation, heart failure, peripheral vascular disease, obesity, and dyslipidaemia), confirmed these findings.

conclusionTyG-BMI remarkably influences the onset and progression of CRM multimorbidity. Incorporating it into CRM multimorbidity prevention and management could have important public health implications.

Indexed as

Blood GlucoseBody Mass IndexDiabetes Mellitus, Type 2Renal Insufficiency, ChronicTriglyceridesAgedBiomarkersCardiometabolic Risk FactorsDisease ProgressionFemaleHumansMaleMiddle AgedMultimorbidityPrognosisProspective StudiesBiomarkersBlood GlucoseTriglyceridesCardio-renal-metabolic multimorbidityMulti-state modelTriglyceride glucose-body mass indexUK Biobank

Identifiers

PMID40119385
PMCPMC11929281

What Socratic 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 Socratic graph.