Bibliometric analysis of multimodal analgesia research in the perioperative period: trends, contributions, and emerging areas (2013-2023)

Abstract

Objectives: Multimodal analgesia (MA) is a cornerstone in perioperative pain management, enhancing pain relief and minimizing opioid consumption by targeting various pain pathways. This study conducts a bibliometric analysis of MA research from 2013 to 2023 to understand its development and impact on perioperative care.

Methods: A comprehensive literature search of the Web of Science Core Collection (WOSCC) was conducted, covering publications from January 2013 to December 2023. Data were analyzed using VOSviewer and other bibliometric tools to identify publication trends, key contributors, and emerging research themes.

Results: The analysis identified 1,939 studies on MA, with a notable increase in annual publications since 2020. The USA, China, and Canada were the leading contributors. Key terms like Non-Steroidal Anti-Inflammatory Drugs (NSAIDs), Enhanced Recovery After Surgery (ERAS), and Patient-Controlled Analgesia (PCA) were frequently associated with MA. Significant journals included the Cureus Journal of Medical Science and Anesthesia and Analgesia. Influential authors such as Richard D. Urman and Henrik Kehlet were highlighted for their contributions. The research showed significant advancements and growing global interest in MA.

Conclusion: The study underscores the growing importance of MA in perioperative pain management, with significant contributions from leading countries and researchers. Future research should focus on optimizing pain management protocols, enhancing patient recovery, and reducing opioid dependency through MA.

Keywords: CiteSpace; VOSviewer; bibliometric analysis; multimodal analgesia; perioperative pain management.

Figure 1

Flowchart of the search strategy and selection process for studies on multimodal analgesia in the perioperative period. This figure presents the step-by-step process of the literature search, screening, and selection criteria applied to identify relevant studies on multimodal analgesia during the perioperative period.

Figure 2

Publication trends in multimodal analgesia research during the perioperative period. The figure illustrates the annual growth in the number of publications related to multimodal analgesia in the perioperative setting, highlighting the increasing interest and research activity in this area over time.

Figure 3

Geographical collaboration and publication analysis. (A) A global map depicting the collaboration networks between countries in multimodal analgesia research. (B) An analysis of the number of publications by country over recent years, showing leading contributors. (C) A visual representation of collaborating institutions on a global scale. (D) An analysis of institutional publication outputs over recent years, emphasizing key research centers in the field.

Figure 4

Journal contribution and citation analysis in multimodal analgesia research. (A) Visualization of journals that contribute to research on multimodal analgesia. (B) A map of co-cited journals, reflecting inter-journal citation patterns. (C) Dual-map overlay showing the relationship between citing and cited journals, providing insights into the interdisciplinary nature of the research.

Figure 5

Analysis of authors and co-cited authors in multimodal analgesia research. (A) Visualization of the most prolific authors contributing to perioperative multimodal analgesia research. (B) A map of co-cited authors, illustrating the key contributors whose work has had significant influence in the field.

Figure 6

Reference citation analysis in multimodal analgesia research. (A) Visualization of the most frequently co-cited references in the field. (B) A timeline showcasing the top 25 references with the most significant citation bursts, indicating highly influential works over time.

Figure 7

Keyword analysis in multimodal analgesia research. (A) Visualization of the most frequently used keywords in multimodal analgesia studies. (B) A temporal map showing the evolution of keyword usage over time, reflecting trends and shifts in research focus. (C) Clustering of related keywords, revealing key thematic areas and research topics within the field.