Contemporary research trends on nanoparticles in endodontics: a bibliometric and scientometric analysis of the top 100 most-cited articles

Abstract

Objectives Advancements in nanotechnology have led to the widespread usage of nanoparticles in the endodontic field. This bibliometric study aimed to determine and analyze the top 100 most-cited articles about nanoparticles in endodontics from 2000 to 2022. Materials and Methods A detailed electronic search was conducted on the “Clarivate Analytics Web of Science, All Databases” to receive the most-cited articles related to the topic. Articles were ranked in descending order based on their citation counts, and the first 100 were selected for bibliometric analysis. Parameters such as citation density, publication year, journal, country, institution, author, study design, study field, evidence level, and keywords were analyzed. Results The top 100 most-cited articles received 4,698 citations (16–271) with 970.21 (1.91–181) citation density in total. Among decades, citations were significantly higher in 2011–2022 ( p < 0.001). Journal of Endodontics had the largest number of publications. Canada and the University of Toronto made the highest contribution as country and institution, respectively. Anil Kishen was the 1 who participated in the largest number of articles. The majority of the articles were designed in vitro . The main study field was “antibacterial effect.” Among keywords, “nanoparticles” followed by “ Enterococcus faecalis ” were used more frequently. Conclusions Developments in nanotechnology had an impact on the increasing number of studies in recent years. This bibliometric study provides a comprehensive view of nanoparticle advances and trends using citation analysis.

Exploring vital pulp Therapies: A bibliometric analysis of the most cited articles

“…Pointing out the prestige of a scientific article in a given subject or area is a difficult task, that can be achieved by observing the number of citations of a given publication in other articles ( Usta et al, 2023 ). This is a quantitative analysis of academic publications, and through mathematical analysis, it aims to create knowledge predictions, publication trends by tracing the main subjects, authors and study centers ( Mattos et al, 2021 , Ye et al, 2023 ), in addition to establishing gaps in the literature and suggesting future work ( Usta et al, 2023 ).…”