Evidence map›Paper›PMID 39922866›Full record

ArticleScientific reports2025

Insulin resistance surrogates are associated with all-cause mortality and cardiovascular mortality in population with metabolic syndrome: a retrospective cohort study of NHANES.

Jinhao Liao, Linjie Wang, Lian Duan, Fengying Gong, Huijuan Zhu, Hui Pan, Hongbo Yang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

7 authors.

Jinhao LiaoKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Linjie WangKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Lian DuanKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Fengying GongKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Huijuan ZhuKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Hui PanKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Hongbo YangKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China. yanghb@pumch.cn.ORCID 0000-0003-2985-8265

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study aimed to assess the association of five insulin resistance surrogates, namely HOMA-β (Homeostasis Model Assessment of Beta-cell Function), QUICKI (Quantitative Insulin Sensitivity Check Index), IGR (Insulin Glucose Ratio), e-IS (Estimated Insulin Sensitivity), and Bennett ISI(Bennett's insulin sensitivity index) with all-cause and cardiovascular mortality in respondents with metabolic syndrome(MetS). The prospective cohort of 6662 participants aged 18 years and older with metabolic syndrome was extracted from the National Health and Nutrition Examination Survey(NHANES 1999-2016). The multivariate Cox proportional hazards regression model, Kaplan-Meier survival curve, and log-rank tests were applied to determine the association between the five indices and all-cause mortality and cardiovascular mortality in the MetS population. Restricted cubic splines, a two-piece segmented Cox proportional hazards model, and threshold effect analyses were performed to evaluate the nonlinear relationship. Sensitivity analyses were then conducted by removing individuals with CKD, CHF, CAD, stroke, or cancer, respectively. All five insulin resistance (IR) surrogates displayed a negative association with all-cause and cardiovascular mortality in participants with metabolic syndrome. Restricted cubic spline curves showed QUICKI, IGR, and e-IS had a nonlinear relationship with statistical significance. MetS population at the highest quartile of HOMA-β or IGR exhibited lower all-cause and cardiovascular event probabilities compared with those at the lowest quartile, and e-IS had a similar correlation with cardiovascular events. Threshold effect analyses showed that there were inflection points of IGR for all-cause and cardiovascular mortality. As IGR gradually approached inflection points, the two types of mortality risks descended by 15%[HR 0.85(0.80,0.91)] and 19%[HR 0.81(0.71,0.92)], respectively. Sensitivity analysis indicated most results were robust, but Bennett ISI did not exhibit significant outcomes in participants without CKD. Our study provides evidence that HOMA-β, QUICKI, IGR, e-IS, and Bennett ISI displayed a reverse correlation with all-cause mortality and cardiovascular mortality in participants with metabolic syndrome. The five IR surrogates should be given more attention during the follow-up of MetS population.

Indexed as

Cardiovascular DiseasesInsulin ResistanceMetabolic SyndromeAdultAgedBiomarkersFemaleHumansMaleMiddle AgedNutrition SurveysProportional Hazards ModelsRetrospective StudiesRisk FactorsBiomarkersAll-cause mortalityBennett ISICardiovascular mortalityE-ISHOMA-βIGRInsulin resistance surrogateMetabolic syndromeQUICKI

Identifiers

PMID39922866
PMCPMC11807226

What OpenQuestion holds

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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.