Evidence map›Paper›PMID 28659657›Full record

Trial reportDisease markers2017

Serum Gamma-Glutamyl Transferase and Ferritin Synergistically Associated with the Rate of Chronic Kidney Disease.

Tao Chen, Yan Ren, Yun Gao, Haoming Tian

Open access · hybridAbstract readClinical Trial
In one paragraph

Trial report in Disease markers, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

8 citing papers in PubMed, 10 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

4 authors at 1 institution in 1 country.

Tao ChenDepartment of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu 610041, China.ORCID 0000-0002-8371-779X
Yan RenDepartment of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu 610041, China.
Yun GaoDepartment of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu 610041, China.
Haoming TianDepartment of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu 610041, China.ORCID 0000-0002-1921-4733
Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study investigated the effects of GGT and SF on the risk of CKD. 1024 participants (436 men and 588 women) were divided into three groups according to GGT and SF levels: group 1 (both GGT and SF not in the fourth quartile), group 2 (only GGT or SF in the fourth quartile), and group 3 (both GGT and SF in the fourth quartile). The risks of CKD in different levels of GGT and SF and in groups 2-3 compared with group 1 were analyzed by multiple logistic regression. GGT or SF in the highest quartile was associated with increased risk of CKD. Such associations attenuated after adjustment for confounding factors. The incidences of CKD, especially albuminuria, increased across the three groups. Correspondingly, malondialdehyde (MDA) levels gradually increased from group 1 to group 3. The risks of CKD were higher in groups 2 and 3 than that in group 1. In group 3, the increased rate was independent of age, BMI, alcohol drinking, diabetes mellitus, hypertension, hypertriglyceridemia, and metabolic syndrome (odds ratios from 1.887 to 2.293,

Indexed as

AdultAgedAlcohol DrinkingBiomarkersCross-Sectional StudiesDiabetes Mellitus, Type 2FemaleFerritinsgamma-GlutamyltransferaseHumansHypertensionMaleMetabolic SyndromeMiddle AgedOdds RatioPrognosisBiomarkersFerritinsgamma-Glutamyltransferase

Identifiers

PMID28659657
PMCPMC5474265
OpenAlexW2620639057

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.