Evidence map›Paper›PMID 40401055›Full record

ReviewFrontiers in public health2025

Visualization analysis of poisoning-related research based on CiteSpace.

Wen Zhu, Yao Xiao, LinShen Xie

Abstract readReview
In one paragraph

Review in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 3 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

5 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Review
  5. 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

3 authors.

Wen ZhuWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Yao XiaoWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
LinShen XieWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Summarize the current status, hotspots, and frontier trends in poisoning research over the past decade using CiteSpace software, and provide direction for future research in toxicology and public health. Methods: Relevant literature published between 2015 and 2024 was retrieved from the China National Knowledge Infrastructure (CNKI) and Web of Science Core Collection. CiteSpace software was employed to conduct a visual analysis of poisoning-related research literature from the past decade. Results: A total of 5,644 Chinese articles and 14,985 English articles were included. High-frequency keywords in Chinese literature included "hemoperfusion" and "nursing" while high-frequency keywords in English literature included "exposure" "oxidative stress" and "identification." Keywords with strong betweenness centrality included "treatment," "blood purification" and "carbon monoxide." Recent emerging hotspots in Chinese literature were "liver function" and "oxidative stress" while in English literature, "gut microbiota" has recently gained attention. Conclusion: Poisoning-related research has shown an overall upward trend. The research hotspots in this field primarily include epidemiology, oxidative stress, clinical treatment, prognosis, and chemical substances (e.g., CO, paraquat). In-depth studies on gut microbiota and oxidative stress are expected to become future research trends in this field.

Indexed as

Biomedical ResearchPoisoningSoftwareChinaHumansOxidative StressCiteSpacegut microbiotaoxidative stresspoisoningvisualization research

Identifiers

PMID40401055
PMCPMC12092380

What OpenQuestion 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 OpenQuestion graph.