Evidence map›Paper›PMID 35068935›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2022

The Relationship of Hyperferritinemia to Metabolism and Chronic Complications in Type 2 Diabetes.

Xiaojing Shang, Rui Zhang, Xiaolai Wang, Junxin Yao, Xiaoying Zhao, Huanming Li

Open access · goldAbstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

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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

5 citing papers in PubMed, 6 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

6 authors at 1 institution in 1 country.

Xiaojing ShangDepartment of Endocrinology, Tianjin Fourth Central Hospital, Tianjin, People's Republic of China.
Rui ZhangDivision of Health Management, Tianjin Fourth Central Hospital, Tianjin, People's Republic of China.
Xiaolai WangDepartment of Endocrinology, Tianjin Fourth Central Hospital, Tianjin, People's Republic of China.
Junxin YaoDepartment of Endocrinology, Tianjin Fourth Central Hospital, Tianjin, People's Republic of China.
Xiaoying ZhaoDepartment of Endocrinology, Tianjin Fourth Central Hospital, Tianjin, People's Republic of China.
Huanming LiDepartment of Cardiology, Tianjin Fourth Central Hospital, Tianjin, People's Republic of China.
Tianjin Fourth Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimElevated serum ferritin has been found to be closely related to type 2 diabetes mellitus. This study aimed to explore the relationship of high serum ferritin to metabolism and chronic complications in type 2 diabetes.

methodsThis was a cross-sectional study. A total of 330 type 2 diabetes patients who visited an endocrine clinic were included for the analysis. Serum ferritin and metabolic parameters were recorded. The prevalence of chronic diabetic complications was evaluated. Based on serum ferritin, participants were divided into hyperferritinemia and normal-ferritin groups. Metabolic parameters and prevalence of chronic diabetic complications were compared. The relationship between hyperferritinemia and chronic diabetic complications was explored with multivariate logistic regression models. Data were statistically analyzed by sex.

resultsCompared with the normal-ferritin group, the hyperferritinemia group showed higher levels of the serum inflammatory marker CRP and higher prevalence of diabetic retinopathy (DR) and coronary heart disease (CHD), regardless of sex (

conclusionThis study found that hyperferritinemia was associated with increased CRP and higher prevalence of DR and CHD in type 2 diabetes. In men, high serum ferritin was also associated with dyslipidemia, hepatic dysfunction, and microalbuminuria.

Indexed as

chronic complicationdiabetes mellitusferritinmetabolismtype 2

Identifiers

PMID35068935
PMCPMC8769058
OpenAlexW4205529690

What OpenQuestion holds

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LicenceCC BY-NC
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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.