Visual Bibliometric Analysis of Research Hotspots and Trends in Antimicrobial Resistance in China

To systematically analyze the research landscape of antimicrobial resistance (AMR) in China from 2016-2025, identify hotspots, and detect emerging trends using bibliometric visualization techniques. We compiled 3,096 publications from the Web of Science Core Collection (including Science Citation Index Expanded, SCI-E) and China National Knowledge Infrastructure (CNKI). Using CiteSpace, we performed co-authorship network analysis, keyword co-occurrence mapping, and cluster analysis employing the Log-Likelihood Ratio (LLR) algorithm. Burst detection via Kleinberg's algorithm identified research frontiers, while modularity Q (>0.3) and silhouette metrics validated network structural quality. Rising from 357 in 2016 to 365 in 2022, with accelerated growth following the 2019-2022 period. Six major research clusters emerged with significant structural validity (modularity Q = 0.8108). Burst analysis identified mobilized colistin resistance-1 (mcr-1, burst strength 9.12) and carbapenemase (8.52) as the strongest emerging signals. Resistance surveillance revealed divergent trends: carbapenem-resistant Klebsiella pneumoniae increased alarmingly from 5.6% to 20.0%, whereas methicillin-resistant Staphylococcus aureus declined from 48.8% to 25.8%. Author network analysis revealed a highly centralized structure with limited cross-regional collaboration. Novel therapeutics, including antimicrobial peptides, phage therapy, and machine learning applications, demonstrated significant emergence. Overall, the bibliometric patterns suggest that AMR research in China has evolved from descriptive surveillance toward mechanistic investigation and increasing attention to innovative interventions. The contrasting decline in methicillin-resistant Staphylococcus aureus and rise in carbapenem-resistant pathogens highlight the need for continued national surveillance, stronger inter-regional collaboration, targeted antimicrobial stewardship, and cautious translation of emerging technologies into clinical practice.