Evidence map›Paper›PMID 39911351›Full record

ArticleiScience2025

CKD patients comorbid with hypertension are associated with imbalanced gut microbiome.

Pan Wang, Yang Shen, Kaixin Yan, Siyuan Wang, Jie Jiao, Hongjie Chi, Jiuchang Zhong, Qianmei Sun, Ying Dong, Jing Li

Abstract read
In one paragraph

Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Microbiota-gut-kidney axis in health and renal disease.International journal of biological sciences · 2026
    Review
  9. Article
  10. 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

10 authors.

Pan WangHeart Center and Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Yang ShenDepartment of Nephrology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Kaixin YanHeart Center and Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Siyuan WangHeart Center and Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Jie JiaoHeart Center and Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Hongjie ChiHeart Center and Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Jiuchang ZhongHeart Center and Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Qianmei SunDepartment of Nephrology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Ying DongHeart Center and Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Jing LiHeart Center and Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intestinal flora has been linked to chronic kidney disease (CKD) and hypertension, respectively. This study aimed to investigate the microbial community among 54 individuals without CKD, 46 hypertensive CKD patients (CKD_HTN), and 48 non-hypertensive CKD patients. Variations in microbial diversity were detected in CKD. The

Indexed as

MicrobiologyMicrobiomeMolecular physiology

Identifiers

PMID39911351
PMCPMC11795142

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.