Global trends in biomarker research for periprosthetic joint infection: a bibliometric analysis

Periprosthetic joint infection (PJI) remains a major diagnostic challenge, and no single biomarker provides definitive accuracy. With rapid advances in synovial, serum, and molecular assays, a comprehensive overview of global biomarker research is needed. This study provides a broad, data-driven mapping of PJI biomarker research, clarifying major thematic shifts and their implications for clinical translation.

A literature search of the Web of Science Core Collection (2011-2024) identified research and review articles on PJI diagnostics and biomarkers. Bibliometric indicators, collaboration networks, and keyword co-occurrence were analyzed using VOSviewer, CiteSpace, and Bibliometrix. Co-citation and keyword analyses were used to determine influential references and evolving hotspots. Recent high-impact studies and consensus guidelines were reviewed to contextualize the findings.

PJI biomarker publications increased markedly, rising from fewer than five per year before 2014 to 57 in 2020. The 380 papers included accumulated more than 5,200 citations (mean 13.8 per article). China (103) and the USA (88) accounted for half of all output, with the USA showing the strongest citation impact; Germany, the UK, and Italy were also key contributors. Collaboration mapping highlighted Parvizi, Trampuz, and the Rothman Institute as central nodes. The Journal of Arthroplasty published the largest share of studies, while JBJS-Am and CORR had the highest citations per article. Keyword evolution showed a transition from conventional serum markers (2011-2015) to synovial α-defensin and leukocyte esterase assays (2016-2018), and more recently to synovial calprotectin, machine learning, microfluidics, and molecular diagnostics (2019-2024).

From 2011 to 2024, PJI biomarker research grew rapidly, driven mainly by institutions in the United States, China, and Europe. Key themes included synovial α-defensin, calprotectin, machine learning, and next-generation sequencing. Future progress depends on multicenter validation, assay standardization, and integrating biomarkers into diagnostic algorithms. Stronger collaboration, data sharing, and decision-support tools will be essential for earlier and more accurate PJI diagnosis. Video Abstract.