Evidence map›Paper›PMID 39844261›Full record

ArticleCardiovascular diabetology2025

Association of different insulin resistance surrogates with all-cause and cardiovascular mortality among the population with cardiometabolic multimorbidity.

Hongqiang Zhang, Zhixin Tu, Sihua Liu, Jumei Wang, Jie Shi, Xingyu Li, Rongdongqing Shi, Minghui Chen, Tong Yue, Sihui Luo and 2 more

Erratum issuedAbstract readComparative Study
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. An erratum has been issued. Cited by 52 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

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

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

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Hongqiang Zhang *Department of Endocrinology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, China.
Zhixin Tu *Department of Endocrinology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, China.
Sihua Liu *Pan-Vascular Management Center, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, China.
Jumei WangDepartment of Endocrinology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, China.
Jie ShiDepartment of Endocrinology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, China.
Xingyu LiDepartment of Endocrinology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, China.
Rongdongqing ShiDepartment of Endocrinology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, China.
Minghui ChenDepartment of Endocrinology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, China.
Tong YueDepartment of Endocrinology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, China.
Sihui LuoDepartment of Endocrinology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, China.
Yu DingDepartment of Endocrinology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, China. yuding6815@163.com.ORCID 0000-0003-1617-2125
Xueying ZhengDepartment of Endocrinology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, China. lxyzheng@ustc.edu.cn.ORCID 0000-0001-8395-9476

Funding

2023 Diabetes Young and Middle-aged Physicians Research Project supported by Bethune Foundation No. 2023KY623Anhui Provincial Clinical Medical Research and Translational Special Project 202204295107020026Emergency Scientific and Technological Research Project on Novel Coronavirus Infection BJ9100000005National Natural Science Foundation of China Grant No. 82100857National Natural Science Foundation of China Grant No. 82300904
6 · The paper itself

Abstract

backgroundThe coexistence of cardiometabolic diseases (CMDs), defined as cardiometabolic multimorbidity (CMM), has been shown to significantly elevate mortality risk. Insulin resistance (IR) is one of the main contributing factors to the pathogenesis of CMM. Although several surrogates for IR are employed in clinical evaluations, their relationship with mortality in individuals with CMM remains unclear. This study aimed to investigate the associations between various IR surrogates and mortality in individuals with CMM, and to evaluate their prognostic value.

methodsThis study enrolled 1093 patients diagnosed with CMM. We developed five surrogate markers to assess IR levels: triglyceride-glucose (TyG) index, TyG-waist circumference (TyG-WC), TyG-waist height ratio (TyG-WHtR), homeostatic model assessment of insulin resistance (HOMA-IR), and metabolic score for insulin resistance (METS-IR). To investigate the associations between different IR surrogates and both all-cause and cardiovascular mortality, multivariable Cox proportional hazards models were applied. We employed restricted cubic splines to examine non-linear associations, and Cox models were developed on either side of the inflection point for additional investigation. Meanwhile, the predictive values of five IR surrogates were further assessed.

resultsOf the 477 all-cause deaths that occurred during a median follow-up of 5.8 years, 197 were related to cardiovascular disease. Among five surrogate markers of IR, the TyG index was the only one that significantly correlates with both all-cause and cardiovascular mortality. The threshold value for both types of mortality was 8.85. A TyG index beneath the inflection point exhibits an inverse correlation with cardiovascular mortality (HR 0.483; 95% CI = 0.281-0.831) and all-cause mortality (HR 0.519; 95% CI = 0.368-0.732). On the other hand, when the TyG index surpassed the inflection point, it demonstrated a positive correlation with cardiovascular mortality (HR 1.413; 95% CI = 1.075-1.857) and all-cause mortality (HR 1.279; 95% CI = 1.070-1.529). Based on the analysis of receiver operating characteristics, the TyG index has been recognized as a dependable predictor of survival outcomes.

conclusionsThis study emphasizes the prognostic significance of IR surrogates, particularly the TyG index, in predicting mortality among individuals with CMM. The TyG index constitutes a crucial element in the development of management and intervention strategies for these patients.

Indexed as

Blood GlucoseCardiovascular DiseasesInsulin ResistanceMetabolic SyndromeTriglyceridesAdultAgedBiomarkersCardiometabolic Risk FactorsCause of DeathFemaleHumansMaleMiddle AgedMultimorbidityPredictive Value of TestsBiomarkersBlood GlucoseTriglyceridesCardiometabolic multimorbidityInsulin resistanceMortality

Identifiers

PMID39844261
PMCPMC11755928

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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.