ReviewMedical science monitor : international medical journal of experimental and clinical research2023
Drug-Induced Cardiotoxicity in Children During the Past 30 Years: A Bibliometric Study and Visualization Analysis.
Review in Medical science monitor : international medical journal of experimental and clinical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Precision Pediatric Cancer Nanomedicine: Advancing Personalized Nano Therapies to Reduce Non-Communicable Diseases Through AI-Driven 3D-Printed Drugs.International journal of nanomedicine · 2026Review
- Visualized bibliometric panorama of ureteral stents (1975-present): trends and hotspots revealed.World journal of urology · 2025Review
- Therapeutic hypothermia for neonates: a bibliometric analysis and visualization research.Frontiers in neurology · 2025Article
- A bibliometric analysis of chemotherapy and pain in pediatric patients over the last decade.Frontiers in pediatrics · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Drug-induced cardiotoxicity (DICT) is one of the most serious adverse drug reactions, which is an important safety issue in drug development and clinical practice. This study aimed to summarize the knowledge structure and to detect emerging trends, and provide ideas for future research on DICT in children using bibliometric methods. MATERIAL AND METHODS All publications on DICT in children were retrieved through the Web of Science Core Collection up to April 20, 2022. The document type was restricted to articles with the language set to English. CiteSpace and VOSviewer were used to conduct this bibliometric analysis. RESULTS A total of 298 articles were included, and the annual publications decreased since 2021. The United States was the leading country with the most publications (117), the highest centrality (0.39), and total citations (4055). The most influential institution was the University of British Columbia, while Carleton BC and Rassekh SR, both from Canada, were the most productive authors, but there was no leader in this field. The keywords with both high frequency and high centrality after excluding "cardiotoxicity" and "children" were acute lymphoblastic leukemia (Freq=43, Central=0.15), childhood cancer (Freq=42, Central=0.13), toxicity (Freq=33, Central=0.16), and breast cancer (Freq=29, Central=0.19). "Adriamycin cardiotoxicity" was the first burst keyword, while "childhood cancer", "oxidative stress", and "cardiac dysfunction" were emerging research hotspots. CONCLUSIONS Attention to DICT in children was insufficient. This study serves as a breakthrough point, providing a comprehensive overview of the knowledge structure, development landscape, and future opportunities in this field.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.