Evidence map›Paper›PMID 38983807›Full record

ArticleWorld journal of diabetes2024

Evaluating new biomarkers for diabetic nephropathy: Role of α2-macroglobulin, podocalyxin, α-L-fucosidase, retinol-binding protein-4, and cystatin C.

Jing-Jing Li, Ru-La Sa, Yu Zhang, Zhao-Li Yan

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Article in World journal of diabetes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

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8citing papers in PubMed, 1 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

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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

8 citing papers in PubMed, 1 synthesis or guideline 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.

Jing-Jing LiDepartment of Infectious Diseases, Inner Mongolia Medical University, Hohhot First Hospital, Hohhot 010000, Inner Mongolia Autonomous Region, China.
Ru-La SaDepartment of Endocrinology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot 010000, Inner Mongolia Autonomous Region, China.
Yu ZhangDepartment of Dermatology, Inner Mongolia Autonomous Region People's Hospital, Hohhot 010000, Inner Mongolia Autonomous Region, China.
Zhao-Li YanDepartment of Endocrinology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot 010000, Inner Mongolia Autonomous Region, China. aliceyzl@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe intricate relationship between type 2 diabetes mellitus (T2DM) and diabetic nephropathy (DN) presents a challenge in understanding the significance of various biomarkers in diagnosis.

aimTo elucidate the roles and diagnostic values of α2-macroglobulin (α2-MG), podocalyxin (PCX), α-L-fucosidase (AFU), retinol-binding protein-4 (RBP-4), and cystatin C (CysC) in DN.

methodsFrom December 2018 to December 2020, 203 T2DM patients were enrolled in the study. Of these, 115 were diagnosed with DN (115 patients), while the remaining 88 patients were classified as non-DN. The urinary levels of α2-MG, PCX, and AFU and the serum concentrations RBP-4 and CysC were measured in conjunction with other relevant clinical indicators to evaluate their potential correlations and diagnostic utility.

resultsAfter adjustments for age and gender, significant positive correlations were observed between the biomarkers CysC, RBP-4, α2-MG/urinary creatinine (UCr), PCX/UCr, and AFU/UCr, and clinical indicators such as urinary albumin-to-creatinine ratio (UACR), serum creatinine, urea, 24-h total urine protein, and neutrophil-to-lymphocyte ratio (NLR). Conversely, these biomarkers exhibited negative correlations with the estimated glomerular filtration rate (

conclusionThis study underscores the diagnostic significance of α2-MG, PCX, and AFU in the development of DN. The biomarkers RBP-4, CysC, PCX, AFU, and α2-MG provide promising diagnostic insights, while UACR is the most potent diagnostic biomarker in assessing DN.

Indexed as

Cystatin CDiabetic nephropathyPodocalysinRetinol binding protein-4α2-macroglobulinα-L-fucosidase

Identifiers

PMID38983807
PMCPMC11229980

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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.