Background: Postoperative infections in artificial joints provide considerable difficulties in the field of orthopedics, especially after joint replacement procedures. These infections rank among the most severe postoperative consequences, frequently leading to treatment ineffectiveness and reduced quality of life for surgery patients. Consequently, it is crucial to acquire knowledge about worldwide research trends in this area in order to educate clinical practices and improve therapeutic techniques. This work exploits bibliometric analysis to investigate the present state, developing patterns, and main areas of focus in research on artificial joint infection.
Objective: To analyze the research trends, hotspots, and international collaborations on artificial joint infections worldwide from 2013 to 2023.
Methods: Extractions of raw data were made from the WoSCC (Web of Science Core Collection) database. Detailed information collected includes the quantity of publications, authors, citations, publication year, h-index, references, country/region, journal, and keywords. Analysis of the data was conducted using VOSviewer version 1.6.10.0 and CiteSpace version 6.3.R1.
Results: A total of 1,799 articles published between 2013 and 2023 were included in this analysis, showing a steady increase in publication with the United States leading at 553 articles. Infection rates and topics such as biofilm formation and antimicrobial resistance were highly cited, with Mayo Clinic contributing 65 articles as the most prolific institution.
Conclusion: Research on biofilm infections, antibiotic resistance, and new biomarkers is a key focus, particularly on disrupting biofilms and enhancing diagnostics. There's growing attention in biomarkers like α-defensins and exosomal miRNAs for PJI diagnosis, pointing to new clinical uses. Studies on antimicrobial-coated prosthetics and topical agents are also gaining importance in treatment strategies.
Keywords: antibiotic resistance; artificial joint infection; bibliometrics; biofilm; infection control strategies; infection diagnosis antimicrobial coating.
Copyright © 2024 Zhang, Li, Zhao, Duan, Bai and Yan.