Evidence map›Paper›PMID 36909348›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2023

Chinese Visceral Adipose Index Shows Superior Diagnostic Performance in Predicting the Risk of Metabolic Dysfunction Associated Fatty Liver Disease in Early Postmenopausal Chinese Women.

Yayun Lu, Lingxia Ge, Hao Yang, Yufeng He, Yujun Wang

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In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 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

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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

8 citing papers in PubMed, 1 synthesis or guideline 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

5 authors.

Yayun Lu *Health Examination Center, Huadong Sanatorium, Wuxi, People's Republic of China.ORCID 0000-0001-5143-582X
Lingxia Ge *Health Examination Center, Huadong Sanatorium, Wuxi, People's Republic of China.
Hao YangDepartment of Stomatology, Huadong Sanatorium, Wuxi, People's Republic of China.ORCID 0000-0002-9839-7960
Yufeng HeDepartment of Stomatology, Huadong Sanatorium, Wuxi, People's Republic of China.
Yujun WangDepartment of health Nursing, Huadong Sanatorium, Wuxi, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Previous studies have reported the diagnostic values of multiple obesity indicators for predicting the risk of non-alcoholic fatty liver disease. However, the diagnostic values of obesity indicators for predicting the risk of metabolic dysfunction-associated fatty liver disease (MAFLD) in early postmenopausal women is still unknown. Therefore, this study investigated the predictive values of common obesity indices for estimating the risk of MAFLD in early postmenopausal Chinese women. Methods: This study enrolled 2514 early postmenopausal women, aged between 45 and 55 years, who underwent abdominal ultrasonography examination at the Health examination center of the Huadong Sanatorium between June 2021 and December 2021. The values for six obesity indices, namely, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body adiposity index (BAI), and Chinese visceral adiposity index (CVAI) were extracted from the medical records. Results: Our data showed that all the six obesity indices were significantly associated with the risk of MAFLD ( Conclusion: This study demonstrated that all the obesity indices were associated with an increased risk of MAFLD in the obese subjects and five obesity indices except for BAI were associated with an increased risk of MAFLD in the lean subjects among the early postmenopausal women. CVAI showed the strongest predictive performance in estimating the risk of MAFLD among early menopausal women.

Indexed as

Chinese visceral adipose indexearly postmenopausal womenmetabolic dysfunction associated fatty liver diseaseobesity indices

Identifiers

PMID36909348
PMCPMC9999715

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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.