Evidence map›Paper›PMID 42668917›Full record

ArticleInternational journal of endocrinology2026

Association Between Iron Metabolism and Microalbuminuria in Patients With Type 2 Diabetes Mellitus and MASLD.

Huanjia Qu, Lingling Zhou, Jinhua Hu, Dong Tang, Lu Yang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Huanjia QuDepartment of Endocrinology, the Affiliated Hospital of Hangzhou Normal University, Hangzhou 310000, China, hznu.edu.cn.ORCID https://orcid.org/0009-0002-1024-7181
Lingling ZhouDepartment of Endocrinology, the Affiliated Yueqing Hospital of Wenzhou Medical University, Wenzhou 325600, China.ORCID https://orcid.org/0000-0002-6479-6656
Jinhua HuDepartment of Endocrinology, the Affiliated Hospital of Hangzhou Normal University, Hangzhou 310000, China, hznu.edu.cn.ORCID https://orcid.org/0009-0008-2282-7478
Dong TangDepartment of Radiology, the Affiliated Hospital of Hangzhou Normal University, Hangzhou 310000, China, hznu.edu.cn.ORCID https://orcid.org/0009-0003-3329-4121
Lu YangDepartment of Endocrinology, the Affiliated Hospital of Hangzhou Normal University, Hangzhou 310000, China, hznu.edu.cn.ORCID https://orcid.org/0009-0003-3750-1423

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the association between iron metabolism markers and microalbuminuria in patients with Type 2 diabetes mellitus (T2DM) and metabolic dysfunction-associated steatotic liver disease (MASLD). Methods: A total of 137 patients with T2DM and MASLD were enrolled and stratified into microalbuminuria-positive and microalbuminuria-negative groups based on the urinary albumin-to-creatinine ratio (UACR). Iron metabolism markers, including serum ferritin, serum iron, total iron-binding capacity (TIBC), transferrin saturation (TS), and hepcidin, were measured. Hepatic iron and fat content were assessed using magnetic resonance imaging (MRI), including R2 Results: Patients with microalbuminuria had significantly higher levels of serum ferritin, serum iron, hepcidin, and MRI-R2 Conclusions: Altered iron metabolism is associated with microalbuminuria in patients with T2DM and MASLD. MRI-R2

Indexed as

hepatic iron contentiron metabolismmetabolic dysfunction-associated steatotic liver diseasemicroalbuminuriaType 2 diabetes mellitus

Identifiers

PMID42668917
PMCPMC13525477

What OpenQuestion holds

Textmetadata
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.