Evidence map›Paper›PMID 38632455›Full record

ArticleScientific reports2024

Assessing the predictive value of insulin resistance indices for metabolic syndrome risk in type 2 diabetes mellitus patients.

Hadi Bazyar, Ahmad Zare Javid, Mahmood Reza Masoudi, Fatemeh Haidari, Zeinab Heidari, Sohrab Hajializadeh, Vahideh Aghamohammadi, Mahdi Vajdi

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. 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 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
10.0field-weighted citation impact, top 1% 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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 28 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 2 countries.

Hadi BazyarStudent Research Committee, Sirjan School of Medical Sciences, Sirjan, Iran.
Ahmad Zare JavidNutrition and Metabolic Diseases Research Center, Clinical Sciences Research Institute, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Mahmood Reza MasoudiSirjan School of Medical Sciences, Sirjan, Iran.
Fatemeh HaidariSchool of Health, Medical and Applied Sciences, Central Queensland University, Brisbane, Australia.
Zeinab HeidariStudent Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Sohrab HajializadehStudent Research Committee, Sirjan School of Medical Sciences, Sirjan, Iran.
Vahideh AghamohammadiDepartment of Nutrition, Khalkhal University of Medical Science, Khalkhal, Iran. v_agamohammadi@yahoo.com.
Mahdi VajdiDepartment of Community Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran. mv.vajdi@gmail.com.
Sirjan University of Technology · IRAhvaz Jundishapur University of Medical Sciences · IRCentral Queensland University · AUIsfahan University of Medical Sciences · IRLorestan University of Medical Sciences · IR

Funding

Student Research Committee of Sirjan School of Medical Sciences 401000024
6 · The paper itself

Abstract

Limited research has explored the effectiveness of insulin resistance (IR) in forecasting metabolic syndrome (MetS) risk, especially within the Iranian population afflicted with type 2 diabetes mellitus (T2DM). The present investigation aimed to assess the efficacy of IR indices in predicting the risk of MetS among T2DM patients. Convenient sampling was utilized to select four hundred subjects with T2DM. Metabolic factors and IR indices, including the Waist Circumference-Triglyceride Index (WTI), Triglyceride and Glucose Index (TyG index), the product of TyG index and abdominal obesity indices, and the Metabolic Score for Insulin Resistance (METS-IR), were evaluated. Logistic regression, coupled with modeling, was employed to explore the risk of MetS. The predictive performance of the indices for MetS stratified by sex was evaluated via receiver operating characteristic (ROC) curve analysis and estimation of the area under the curve (AUC) values. The TyG-Waist Circumference (TyG-WC) index exhibited the largest AUCs in both males (0.91) and females (0.93), while the TyG-Body Mass Index (TyG-BMI) demonstrated the smallest AUCs (0.77 in males and 0.74 in females). All indices significantly predicted the risk of MetS in all subjects before and after adjustment (p < 0.001 for all). The TyG-WC index demonstrated the highest odds ratios for MetS (8.06, 95% CI 5.41-12.00). In conclusion, all IR indices assessed in this study effectively predicted the risk of MetS among Iranian patients with T2DM, with the TyG-WC index emerging as the most robust predictor across both genders.

Indexed as

Diabetes Mellitus, Type 2Insulin ResistanceMetabolic SyndromeFemaleGlucoseHumansInsulinIranMaleRisk FactorsTriglyceridesGlucoseInsulinTriglyceridesInsulin resistance indicesMetabolic syndromeObesityTyG indexType 2 diabetes mellitus

Identifiers

PMID38632455
PMCPMC11024148
OpenAlexW4394918480

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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.