Evidence map›Paper›PMID 35782950›Full record

ArticleFrontiers in nutrition2022

Evaluated Glomerular Filtration Rate Is Associated With Non-alcoholic Fatty Liver Disease: A 5-Year Longitudinal Cohort Study in Chinese Non-obese People.

Ji Cen, Yong Han, Yufei Liu, Haofei Hu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
4.5field-weighted citation impact, top 4% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

  1. 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

4 authors at 2 institutions in 1 country.

Ji CenDepartment of Nephrology, Hechi People's Hospital, Hechi, China.
Yong HanDepartment of Emergency, Shenzhen Second People's Hospital, Shenzhen, China.
Yufei LiuShenzhen University Health Science Center, Shenzhen, China.
Haofei HuShenzhen University Health Science Center, Shenzhen, China.
Shenzhen University · CNHechi University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Evidence regarding the association between evaluated glomerular filtration rate (eGFR) and non-alcoholic fatty liver disease (NAFLD) is still limited. On that account, the purpose of our research is to survey the link of evaluated eGFR on NAFLD. Methods: This study is a retrospective cohort study. Which consecutively and non-selectively collected a total of 16,138 non-obese participants in a Chinese hospital from January 2010 to December 2014. We then used the Cox proportional-hazards regression model to explore the relationship between baseline eGFR and NAFLD risk. A Cox proportional hazards regression with cubic spline functions and smooth curve fitting (the cubic spline smoothing) was used to identify the non-linear relationship between eGFR and NAFLD. Additionally, we also performed a series of sensitivity analyses and subgroup analyses. Data had been uploaded to the DATADRYAD website. Results: The mean age of the included individuals was 43.21 ± 14.95 years old, and 8,467 (52.47%) were male. The mean baseline eGFR was 98.83 ± 22.80 mL/min per 1.73m Conclusion: This study demonstrates a negative and non-linear association between eGFR and incident NAFLD in the Chinese non-obese population. eGFR is strongly related to NAFLD when eGFR is above 103 mL/min per 1.73 m

Indexed as

cohort studyCox proportional-hazards regressionevaluated glomerular filtration ratenon-alcoholic fatty liver diseasenon-linear

Identifiers

PMID35782950
PMCPMC9244698
OpenAlexW4282973119

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.