Evidence mapPaperPMID 41441634Full record

ReviewToxins2025

Targeting the Gut-Kidney Axis: Modulation of Gut Microbiota by Traditional Chinese Medicine for Chronic Kidney Disease Management.

Yijing Xin, Libin Pan

Abstract readReview
In one paragraph

Review in Toxins, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
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

2 authors.

Yijing XinDepartment of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Libin PanDepartment of Pharmacy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou 310022, China.

Funding

Medical Science and Technology Project of Zhejiang Province 2024KY798National Natural Science Foundation of China 82304608National Natural Science Foundation of China 82404750Zhejiang Provincial Natural Science Foundation of China LQ23H310002
6 · The paper itself

Abstract

The interaction between gut microbiota dysbiosis and CKD progression via the "gut-kidney axis" is increasingly recognized. Gut-derived uremic toxins (e.g., indoxyl sulfate and p-cresyl sulfate) accumulate systemically, while beneficial metabolites like short-chain fatty acids (SCFAs) decrease, contributing to inflammation, oxidative stress, and kidney fibrosis. Traditional Chinese Medicine (TCM), including complex formulae, single herbs, and active ingredients, has long been used to manage CKD. Emerging evidence-primarily from animal studies-highlights its potential to alleviate the disease by modulating the gut microbiota. This review summarizes how TCM interventions re-establish gut microbial symbiosis by regulating microbial composition, reducing toxin load, and reinforcing intestinal barrier integrity, thereby ameliorating systemic inflammation and protecting kidney function. Targeting the gut microbiota represents a promising therapeutic frontier for CKD, and TCM offers a rich resource for developing novel microbiota-modulating strategies. However, future research must focus on validating molecular mechanisms, standardizing TCM preparations, and conducting rigorous clinical trials to facilitate clinical translation.

Indexed as

Drugs, Chinese HerbalGastrointestinal MicrobiomeKidneyMedicine, Chinese TraditionalRenal Insufficiency, ChronicAnimalsDysbiosisHumansUremic ToxinsDrugs, Chinese HerbalUremic Toxinschronic kidney diseasegut–kidney axisgut microbiotamicrobial metabolitestraditional Chinese medicine

Identifiers

PMID41441634
PMCPMC12737660

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.