Evidence mapPaperPMID 35957707Full record

ArticleAnnals of translational medicine2022

Gut microbiota diversity in middle-aged and elderly patients with end-stage diabetic kidney disease.

Rongping Chen, Dan Zhu, Rui Yang, Zezhen Wu, Ningning Xu, Fengwu Chen, Shuo Zhang, Hong Chen, Ming Li, Kaijian Hou

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 4% 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.

  1. Pooled it
  2. Observational
  3. CD4Frontiers in cellular and infection microbiology · 2026
    Article
  4. Microbiota-gut-kidney axis in health and renal disease.International journal of biological sciences · 2026
    Review
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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

10 authors at 3 institutions in 1 country.

Rongping Chen *School of Laboratory Medical and Biotechnology, Southern Medical University, Guangzhou, China.
Dan Zhu *Department of Endocrine and Metabolic Diseases, Longhu Hospital, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Rui Yang *Department of Endocrine and Metabolic Diseases, Southern Medical University, Guangzhou, China.
Zezhen Wu *Department of Endocrine and Metabolic Diseases, Longhu Hospital, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Ningning XuDepartment of Endocrine and Metabolic Diseases, Southern Medical University, Guangzhou, China.
Fengwu ChenDepartment of Endocrine and Metabolic Diseases, Longhu Hospital, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Shuo ZhangDepartment of Endocrine and Metabolic Diseases, Longhu Hospital, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Hong ChenDepartment of Endocrine and Metabolic Diseases, Southern Medical University, Guangzhou, China.
Ming LiSchool of Laboratory Medical and Biotechnology, Southern Medical University, Guangzhou, China.
Kaijian HouDepartment of Endocrine and Metabolic Diseases, Longhu Hospital, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Southern Medical University · CNFirst Affiliated Hospital of Shantou University Medical College · CNShantou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diabetic kidney disease (DKD) is the most common cause of end-stage renal disease (ESRD), but the mechanism between DKD and ESRD remains unclear. Some experts have put forward the "microbial-centered ESRD development theory", believing that the bacterial load caused by gut microecological imbalance and uremia toxin transfer are the core pathogenic links. The purpose of this study was to analyze the genomic characteristics of gut microbiota in patients with ESRD, specifically DKD or non-diabetic kidney disease (NDKD). Methods: In this cross-sectional study, patients with ESRD were recruited in a community, including 22 DKD patients and 22 NDKD patients matched using gender and age. Fecal samples of patients were collected for 16S rDNA sequencing and gut microbiota analysis. The distribution structure, diversity, and abundance of microflora in DKD patients were analyzed by constructing species evolutionary trees and analyzing alpha diversity, beta diversity, and linear discriminant analysis effect size (LEfSe). Results: The results of our study showed that there were statistically significant differences in the richness and species of gut microbiota at the total level between DKD patients and NDKD patients. The analysis of genus level between the two groups showed significant differences in 16 bacterial genera. Among them, Oscillibacter, Bilophila, UBA1819, Ruminococcaceae UCG-004, Anaerotruncus, Ruminococcaceae, and Ruminococcaceae NK4A214 bacteria in DKD patients were higher than those in NDKD patients. Conclusions: 16S rDNA sequencing technology was used in this study to analyze the characteristics of intestinal flora in ESRD patients with or without diabetes. We found that there was a significant difference in the intestinal flora of ESRD patients caused by DKD and NDKD, suggesting that these may be potential causative bacteria for the development of ERSD in DKD patients.

Indexed as

16S rDNAdiabetic kidney disease (DKD)End-stage renal disease (ESRD)gut microbiotanon-diabetic kidney disease (NDKD)

Identifiers

PMID35957707
PMCPMC9358493
OpenAlexW4285603475

What Socratic holds

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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 Socratic graph.