Evidence map›Paper›PMID 27382573›Full record

ArticleJournal of diabetes research2016

Sex-Specific Association between Serum Uric Acid and Nonalcoholic Fatty Liver Disease in Type 2 Diabetic Patients.

Nengguang Fan, Lijuan Zhang, Zhenhua Xia, Liang Peng, Yufan Wang, Yongde Peng

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In one paragraph

Article in Journal of diabetes research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 3 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

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

35 citing papers in PubMed, 3 syntheses or guidelines 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

6 authors.

Nengguang FanDepartment of Endocrinology and Metabolism, Shanghai First People's Hospital, Shanghai Jiao Tong University, Shanghai 200080, China.
Lijuan ZhangDepartment of Endocrinology, Shanghai Songjiang Center Hospital, Shanghai 201600, China.
Zhenhua XiaDepartment of Endocrinology, Shanghai Songjiang Center Hospital, Shanghai 201600, China.
Liang PengDepartment of Laboratory Medicine, Shanghai Songjiang Center Hospital, Shanghai 201600, China.
Yufan WangDepartment of Endocrinology and Metabolism, Shanghai First People's Hospital, Shanghai Jiao Tong University, Shanghai 200080, China.
Yongde PengDepartment of Endocrinology and Metabolism, Shanghai First People's Hospital, Shanghai Jiao Tong University, Shanghai 200080, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Across-sectional study was performed in 541 type 2 diabetic patients to determine the relationship between serum uric acid (SUA) and NAFLD in type 2 diabetic patients. Clinical parameters including SUA were determined and NAFLD was diagnosed by ultrasonography. SUA was significantly higher in type 2 diabetic subjects with NAFLD than in those without NAFLD in men, but not in women. Furthermore, the prevalence rate of NAFLD increased progressively across the sex-specific SUA tertiles only in men (37.9%, 58.6%, and 72.6%, resp., P for trend < 0.001). After adjusting for confounding factors, the odd ratios (95% CI) for NAFLD were 1 (reference), 2.93 (95%CI 1.25-6.88), and 3.93 (95% CI 1.55-9.98), respectively, across the tertiles of SUA in men. Contrastingly, SUA levels in women were not independently associated with the risk of NAFLD. Our data suggests that SUA is specifically associated with NAFLD in male type 2 diabetic subjects, independent of insulin resistance and other metabolic factors.

Indexed as

AdultAgedCross-Sectional StudiesDiabetes Mellitus, Type 2FemaleHumansLiverMaleMiddle AgedNon-alcoholic Fatty Liver DiseaseSex FactorsUltrasonographyUric AcidUric Acid

Identifiers

PMID27382573
PMCPMC4921134

What OpenQuestion holds

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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.