Evidence map›Paper›PMID 38042816›Full record

ArticleEuropean journal of medical research2023

Validation of non-invasive indicators in the screening of metabolic dysfunction-associated fatty liver disease: a cross-sectional study among Uighurs in rural Xinjiang.

Yanbo Guo, Yunhua Hu, Jing Yang, Rulin Ma, Xianghui Zhang, Heng Guo, Xinping Wang, Yu Li, Xinyu Peng, Shijie Zhang and 2 more

Open access · goldAbstract read
In one paragraph

Article in European journal of medical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

9 citing papers in PubMed, 18 citations in OpenAlex.

  1. Association betweenFrontiers in nutrition · 2026
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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

12 authors at 2 institutions in 1 country.

Yanbo Guo *Department of Public Health, Shihezi University School of Medicine, Suite 721, Beier Road, Shihezi, 832000, China.
Yunhua Hu *Department of Public Health, Shihezi University School of Medicine, Suite 721, Beier Road, Shihezi, 832000, China.
Jing YangDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Shihezi University School of Medicine, Shihezi, 832000, China.
Rulin MaDepartment of Public Health, Shihezi University School of Medicine, Suite 721, Beier Road, Shihezi, 832000, China.
Xianghui ZhangDepartment of Public Health, Shihezi University School of Medicine, Suite 721, Beier Road, Shihezi, 832000, China.
Heng GuoDepartment of Public Health, Shihezi University School of Medicine, Suite 721, Beier Road, Shihezi, 832000, China.
Xinping WangDepartment of Public Health, Shihezi University School of Medicine, Suite 721, Beier Road, Shihezi, 832000, China.
Yu LiDepartment of Public Health, Shihezi University School of Medicine, Suite 721, Beier Road, Shihezi, 832000, China.
Xinyu PengDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Shihezi University School of Medicine, Shihezi, 832000, China.
Shijie ZhangDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Shihezi University School of Medicine, Shihezi, 832000, China.
Jia HeDepartment of Public Health, Shihezi University School of Medicine, Suite 721, Beier Road, Shihezi, 832000, China. hejia206@shzu.edu.cn.
Shuxia GuoDepartment of Public Health, Shihezi University School of Medicine, Suite 721, Beier Road, Shihezi, 832000, China. gsxshzu@sina.com.
Shihezi University · CNFirst Affiliated Hospital of Shihezi University Medical College · CN

Funding

the Key science and technology project of Xinjiang Production and Construction Corps No. 2018AB022
6 · The paper itself

Abstract

backgroundMetabolic dysfunction-associated fatty liver disease (MAFLD) is the most common chronic liver disease in China. Our study aimed to evaluate the screening value of the fatty liver index (FLI), hepatic steatosis index (HSI), lipid accumulation product (LAP), visceral adiposity index (VAI), and Zhejiang University index (ZJU), as well as other single indicators for MAFLD. We aimed to find the optimal screening tool and its appropriate cut-off values for rural Uyghur adults.

methodsWe completed a survey of 14,321 Uyghur adults in 51 groups in Kashgar, Xinjiang, in 2016 using a typical sampling method, with 12,794 patients ultimately included in statistical analyses. Fatty liver was diagnosed using ultrasonography.

resultsThe prevalence of fatty liver disease (FLD) and MAFLD was 16.73% and 16.55%, respectively, and the FLI, HSI, LAP, VAI, and ZJU were all independently associated with an increased risk of MAFLD. The areas under the receiver operating characteristic curves (AUCs) of the FLI for diagnosing MAFLD in men and women were 0.853 and 0.847, respectively. The AUCs of the body mass index (BMI) for diagnosing MAFLD in men and women were 0.850 and 0.852, respectively. Compared with other metabolic-related markers, FLI had the largest AUC. In men, the optimal cut-off values of FLI and BMI for diagnosing MAFLD were 45 (sensitivity 84.83%, specificity 69.57%) and 27.4 (sensitivity 78.47%, specificity 76.30%), respectively. In women, the optimal cut-off values of FLI and BMI for diagnosing MAFLD were 45 (sensitivity 80.11%, specificity 74.23%) and 28.0 (sensitivity 79.56%, specificity 75.41%), respectively. In men and women, an FLI score of < 30 ruled out MAFLD, while a score of ≥ 50 was a basis for diagnosis.

conclusionFLI and BMI had good screening ability for MAFLD and were superior to HSI, LAP, VAI, and ZJU in both sexes.

Indexed as

Non-alcoholic Fatty Liver DiseaseAdultChinaCross-Sectional StudiesFemaleHumansMaleROC CurveMetabolic dysfunction-associated fatty liver diseaseNon-invasive indicatorsScreening valueSteatosis index

Identifiers

PMID38042816
PMCPMC10693158
OpenAlexW4389275000

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.