Evidence map›Paper›PMID 40634102›Full record

ReviewInternal medicine (Tokyo, Japan)2026

Therapeutic Mechanisms of Traditional Kampo Medicines in the Management of Mild COVID-19 through Gut Microbiota Modulation.

Satoru Chiba, Yusuke Niwa, Masayuki Furukata, Kazuki Morishita, Kaoru Shinohara

Abstract readReview
In one paragraph

Review in Internal medicine (Tokyo, Japan), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Satoru ChibaDepartment of Internal Medicine, Sapporo Suzuki Hospital, Medical Corporation Kenseikai, Japan.
Yusuke NiwaDepartment of Psychiatric Medicine, Sapporo Suzuki Hospital, Medical Corporation Kenseikai, Japan.
Masayuki FurukataDepartment of Psychiatric Medicine, Sapporo Suzuki Hospital, Medical Corporation Kenseikai, Japan.
Kazuki MorishitaDepartment of Psychiatric Medicine, Sapporo Suzuki Hospital, Medical Corporation Kenseikai, Japan.
Kaoru ShinoharaDepartment of Psychiatric Medicine, Sapporo Suzuki Hospital, Medical Corporation Kenseikai, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite antiviral administration, a small number of patients still suffer from prolonged and severe COVID-19 owing to excessive inflammation. Traditional Kampo medicines (TKMs) with a heat-clearing effect have anti-inflammatory effects, such as a reduced NF-κB activity, and rarely cause serious side effects when administered for a short period of time. After oral administration, TKMs interact with the gut microbiota, producing two types of metabolites: metabolites from the gut microbiota (of food and host origin) and TKM compounds transformed by the gut microbiota. Both metabolites decreased the levels of pro-inflammatory cytokines. TKM compounds transformed by the gut microbiota may exhibit superior bioavailability compared with their precursors. In this review, we assessed the mechanism by which bioactive substances with anti-inflammatory effects, such as berberine, baicalin, saikosaponin, kaempferol, and short-chain fatty acids, are effective in treating respiratory symptoms after COVID-19 infection.

Indexed as

COVID-19 Drug TreatmentGastrointestinal MicrobiomeMedicine, KampoAnti-Inflammatory AgentsCOVID-19Drugs, Chinese HerbalHumansPandemicsSARS-CoV-2Anti-Inflammatory AgentsDrugs, Chinese Herbalheat-clearing herbesinflammationintestinal florarespiratory diseaseSARS-CoV-2

Identifiers

PMID40634102
PMCPMC12945432

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.