Evidence map›Paper›PMID 37077810›Full record

ReviewFrontiers in pharmacology2023

Potential therapeutic effects of Chinese meteria medica in mitigating drug-induced acute kidney injury.

Jun Li, Tonglu Li, Zongping Li, Zhiyong Song, Xuezhong Gong

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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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

5 authors.

Jun LiDepartment of Nephrology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Tonglu LiDepartment of Nephrology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Zongping LiDepartment of Nephrology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Zhiyong SongDepartment of Nephrology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Xuezhong GongDepartment of Nephrology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug-induced acute kidney injury (DI-AKI) is one of the leading causes of kidney injury, is associated with high mortality and morbidity, and limits the clinical use of certain therapeutic or diagnostic agents, such as antineoplastic drugs, antibiotics, immunosuppressants, non-steroidal anti-inflammatory drugs, and contrast media. In recent years, numerous studies have shown that many Chinese meteria medica, metabolites derived from botanical drugs, and Chinese medicinal formulas confer protective effects against DI-AKI by targeting a variety of cellular or molecular mechanisms, such as oxidative stress, inflammatory, cell necrosis, apoptosis, and autophagy. This review summarizes the research status of common DI-AKI with Chinese meteria medica interventions, including cisplatin, gentamicin, contrast agents, methotrexate, and acetaminophen. At the same time, this review introduces the metabolites with application prospects represented by ginseng saponins, tetramethylpyrazine, panax notoginseng saponins, and curcumin. Overall, this review provides a reference for the development of promising nephroprotectants.

Indexed as

Chinese meteria medicadrug-induced acute kidney injurymetabolitesmolecular mechanismsreview

Identifiers

PMID37077810
PMCPMC10106589

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.