Evidence map›Paper›PMID 39006142›Full record

ArticleHepatology forum2024

Comparison of triglyceride-glucose index and anthropometric obesity indices in predicting severe grades of hepatic steatosis in nonalcoholic fatty liver disease among non-diabetic obese individuals.

Huseyin Karaaslan, Hasan Inan, Alper Tunga Turkmen, Ismail Altintas, Nida Uyar, Mehmet Ali Eren

Abstract read
In one paragraph

Article in Hepatology forum, 2024. 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

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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

5 citing papers in PubMed.

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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

6 authors.

Huseyin KaraaslanDepartment of Endocrinology, Harran University School of Medicine, Sanliurfa, Turkiye.
Hasan InanDepartment of Internal Medicine, Harran University School of Medicine, Sanliurfa, Turkiye.
Alper Tunga TurkmenDepartment of Radiology, Harran University School of Medicine, Sanliurfa, Turkiye.
Ismail AltintasDepartment of Internal Medicine, Harran University School of Medicine, Sanliurfa, Turkiye.
Nida UyarDepartment of Endocrinology, Harran University School of Medicine, Sanliurfa, Turkiye.
Mehmet Ali ErenDepartment of Endocrinology, Harran University School of Medicine, Sanliurfa, Turkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aim: The triglyceride glucose index (TyG) has been proposed as a promising indicator of both insulin resistance (IR) and non-alcoholic fatty liver disease (NAFLD). However, the efficacy of the TyG index in predicting NAFLD has not been adequately studied, particularly in obese individuals. Materials and Methods: We analyzed 190 morbidly obese individuals. The TyG index, anthropometric obesity indices, homeostatic model assessment (HOMA-IR), and biochemical parameters were compared. NAFLD was diagnosed by hepatic ultrasonography and classified into four grades (0, 1, 2, and 3). Individuals in grades 2 and 3 are considered to have severe steatosis, while those in grades 0 and 1 do not. Results: The area under the curve (AUC) values of the TyG index, body mass index, neck circumferences, waist-to-hip ratio, and HOMA-IR did not differ significantly in predicting severe steatosis (0.640, 0.742, 0.725, 0.620, and 0.624 respectively). However, the AUC values of waist circumference and alanine aminotransferase provided better predictions than the TyG index (0.782, 0.744, and 0.640 respectively). Conclusion: The TyG index is highly effective in predicting both the presence and severity of NAFLD. However, it did not outperform simple obesity indices in predicting NAFLD and its severity in obese patients.

Indexed as

Anthropometric obesity indicesinsülin resistancenon-alcoholic fatty liver diseaseobesitytriglyceride glucose index

Identifiers

PMID39006142
PMCPMC11237241

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.