Evidence map›Paper›PMID 39780236›Full record

ArticleDiabetology & metabolic syndrome2025

Prediction of MASLD using different screening indexes in Chinese type 2 diabetes mellitus.

Mengmeng Hu, Jingyu Yang, Beibei Gao, Zhoulu Wu, Ying Wu, Dandan Hu, Qiong Shen, Lei Chen

Abstract read
In one paragraph

Article in Diabetology & metabolic syndrome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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

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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

8 authors.

Mengmeng Hu *Department of Endocrinology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, No. 126 Daoqian Street, Suzhou, 215000, China.
Jingyu Yang *Department of Endocrinology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, No. 126 Daoqian Street, Suzhou, 215000, China.
Beibei GaoDepartment of Endocrinology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, No. 126 Daoqian Street, Suzhou, 215000, China.
Zhoulu WuDepartment of Endocrinology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, No. 126 Daoqian Street, Suzhou, 215000, China.
Ying WuDepartment of Endocrinology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, No. 126 Daoqian Street, Suzhou, 215000, China.
Dandan HuDepartment of Endocrinology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, No. 126 Daoqian Street, Suzhou, 215000, China.
Qiong ShenDepartment of Endocrinology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, No. 126 Daoqian Street, Suzhou, 215000, China.
Lei ChenDepartment of Endocrinology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, No. 126 Daoqian Street, Suzhou, 215000, China. szslyynfm@163.com.

Funding

the project of development of Suzhou Medical Key disciplines SZXK202107the Project of diagnosis and treatment for key clinical disease in Suzhou LCZX202009the Project of Invigorating Healthcare through Science,Technology and Education No.KJXW2021028
6 · The paper itself

Abstract

backgroundFormerly known as non-alcoholic fatty liver disease (NAFLD), metabolic dysfunction-associated steatotic liver disease (MASLD) has now become the most widespread chronic liver disease worldwide. The primary goal of this study is to assess the ability of different indexes (including VAI, TyG, HOMA-IR, BMI, LAP, WHtR, TyG-BMI, TyG-WC, and TyG-WHtR) to predict MASLD in individuals diagnosed with type 2 diabetes mellitus (T2DM), particularly within the Chinese population.

methodsThis cross-sectional study involved 1,742 patients with T2DM, recruited from the Metabolic Management Centers (MMC) at Suzhou Municipal Hospital. Abdominal ultrasonography was employed for MASLD diagnosis in patients with T2DM. The predictive accuracy of various screening indexes for MASLD in the Chinese T2DM population was evaluated using logistic regression and receiver operating characteristic (ROC) curve analyses.

resultsAmong the 1,742 participants, 996 were diagnosed with MASLD. After adjusting for potential confounding factors, positive associations with the risk of MASLD were found for all the nine indexes. The lipid accumulation product (LAP) exhibited the greatest predictive value for detecting MASLD, with an area under the curve (AUC) of 0.786(95%CI 0.764,0.807), followed by BMI(AUC = 0.785), VAI(AUC = 0.744), TyG(AUC = 0.720), WHtR(AUC = 0.710) and HOMA-IR(AUC = 0.676). The composite Indexes (TyG-BMI, TyG-WC, TyG-WHtR) also showed considerable predictive ability with AUCs of 0.765, 0.752 and 0.748, respectively.

conclusionOur results indicated that all nine indexes have favorable correlations with the risk of MASLD, and most of them have a good performance in predicting MASLD. According to our study, LAP was a reliable index for predicting MASLD among Chinese T2DM patients. The exploration of non-invasive screenings will provide significant support for the early detection and diagnosis of MASLD.

Indexed as

BMIHOMA-IRLAPMASLDT2DMTyGTyG-BMITyG-WCTyG-WHtRVAIWHtR

Identifiers

PMID39780236
PMCPMC11716454

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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.