Evidence map›Paper›PMID 36387912›Full record

ArticleFrontiers in endocrinology2022

Nonlinear relationship between aspartate aminotransferase to alanine aminotransferase ratio and the risk of prediabetes: A retrospective study based on chinese adults.

Changchun Cao, Xiaohua Zhang, Junhu Yuan, Yibing Zan, Xin Zhang, Chao Xue, Yulong Wang, Xiaodan Zheng

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

11 citing papers in PubMed, 17 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Changchun CaoDepartment of Rehabilitation, Shenzhen Dapeng New District Nan'ao People's Hospital, Shenzhen, Guangdong, China.
Xiaohua ZhangDepartment of Rehabilitation, Shenzhen Dapeng New District Nan'ao People's Hospital, Shenzhen, Guangdong, China.
Junhu YuanDepartment of Orthopedics, Foshan First People's Hospital, Foshan, Guangdong, China.
Yibing ZanDepartment of Rehabilitation, Shenzhen Dapeng New District Nan'ao People's Hospital, Shenzhen, Guangdong, China.
Xin ZhangDepartment of Rehabilitation, Shenzhen Dapeng New District Nan'ao People's Hospital, Shenzhen, Guangdong, China.
Chao XueDepartment of Rehabilitation, Shenzhen Dapeng New District Nan'ao People's Hospital, Shenzhen, Guangdong, China.
Yulong WangDepartment of Rehabilitation, Shenzhen Dapeng New District Nan'ao People's Hospital, Shenzhen, Guangdong, China.
Xiaodan ZhengDepartment of Neurology, Shenzhen Samii International Medical Center (The Fourth People's Hospital of Shenzhen), Shenzhen, Guangdong, China.
First People's Hospital of Foshan · CNThe Fourth People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Recent evidence has revealed that the aspartate aminotransferase to alanine aminotransferase ratio (AST/ALT ratio) may be closely associated with metabolic syndrome and insulin resistance. However, it is unclear whether the AST/ALT ratio correlates with prediabetes risk. The aim of our study was to examine the association between AST/ALT ratios and the risk of prediabetes among a large cohort of Chinese subjects. Methods: This retrospective cohort study recruited 75204 Chinese adults with normoglycemia at baseline who underwent physical examinations at the Rich Healthcare Group from 2010 to 2016. The AST/ALT ratio at baseline was the target independent variable, and the risk of developing prediabetes during follow-up was the dependent variable. Cox proportional-hazards regression was used to evaluate the independent association between the AST/ALT ratio and prediabetes. This study identified nonlinear relationships by applying a generalized additive model (GAM) and smooth curve fitting. In order to assess the robustness of this study, we performed a series of sensitivity analyses. Moreover, we performed a subgroup analysis to evaluate the consistency of the association in different subgroups. Data from this study have been updated on the DATADRYAD website. Results: The AST/ALT ratio was negatively and independently related to the prediabetes risk among Chinese adults (HR: 0.76, 95% CI: 0.75-0.84, P<0.0001) after adjusting demographic and biochemical covariates. Furthermore, a nonlinear relationship between the AST/ALT ratio and the risk of developing prediabetes was found at an inflection point of 1.50 for the AST/ALT ratio. When the AST/ALT ratio was to the left of the inflection point (AST/ALT ratio ≤ 1.50), the AST/ALT ratio was negatively related to the prediabetes risk (HR:0.70, 95%CI: 0.65-0.76, P<0.0001). In contrast, the relationship tended to be saturated when the AST/ALT ratio was more than 1.50 (HR: 1.01, 95%CI: 0.89-1.15, P=0.8976). Our findings remained robust across a range of sensitivity analyses. Subgroup analysis revealed that other variables did not alter the relationship between the AST/ALT ratio and prediabetes risk. Conclusion: This study revealed that AST/ALT ratio was negatively and independently associated with prediabetes risk among Chinese participants. The relationship between the AST/ALT ratio and prediabetes risk was nonlinear, and AST/ALT ratio ≤ 1.50 was strongly inversely correlated with prediabetes risk.

Indexed as

Prediabetic StateAdultAlanine TransaminaseAspartate AminotransferasesChinaHumansRetrospective StudiesAlanine TransaminaseAspartate AminotransferasesAST/ALT ratioinsulin resistancemetabolic syndromenonlinearityprediabetes

Identifiers

PMID36387912
PMCPMC9640919
OpenAlexW4307371014

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.