Evidence map›Paper›PMID 38332944›Full record

ReviewDrugs in context2024

Chronic liver disease and management with silymarin: an introductory review of a clinical case collection.

Francesco Angelico

Open access · goldAbstract readReview
In one paragraph

Review in Drugs in context, 2024. 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
1.2field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. 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

1 author at 1 institution in 1 country.

Francesco AngelicoInternal Medicine, Sapienza University, Rome, Italy.
Sapienza University of Rome · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic liver disease (CLD) is a significant global health concern and generally leads to fibrosis, cirrhosis and hepatocellular carcinoma. Various factors, such as metabolic abnormalities, viral infections, alcoholism, genetics and autoimmune responses, contribute to liver damage. CLD is characterized by different phenotypes, including non-alcoholic fatty liver disease, metabolic-associated fatty liver disease, drug-induced liver injury and alcoholic liver disease. These conditions have seen an increase in comorbidities and hospitalizations over the past decade, imposing a substantial burden on patients and healthcare systems. Understanding the underlying mechanisms of liver injury is crucial for effective management and reducing the clinical and economic burden of CLD. Although several attempts have been evaluated to find a drug therapy option for the management of non-alcoholic fatty liver disease and metabolic-associated fatty liver disease, there is no effective drug approved to date. However, different studies have demonstrated that silymarin, the milk thistle extract, could exert hepatoprotective, antioxidant, anti-inflammatory and antifibrotic properties and should therefore be considered an efficacious, tolerable and promising herbal product for the management of liver activity in CLDs. This review discusses the clinical features, diagnosis and available treatments for major liver diseases, acting as an introduction to a clinical case collection based on the management and treatment of major liver diseases with silymarin. This article is part of the

Indexed as

chronic liver diseaseclinical cases silymarindrug-induced liver injuryherbal-induced liver injurymetabolic-associated fatty liver diseasenon-alcoholic fatty liver disease

Identifiers

PMID38332944
PMCPMC10852028
OpenAlexW4391402134

What OpenQuestion 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 OpenQuestion graph.