Recent Trends in Plastic Surgery: A Network Analysis of the Abstract Titles of the Largest German Plastic Surgery Congress 2023

TL;DR

This study uses network analysis to identify key themes and locations in abstracts from Germany's largest plastic surgery conference in 2023.

Contribution

The paper introduces network analysis as a novel method to extract thematic trends from conference abstracts in plastic surgery.

Findings

Keywords like 'Surgery', 'Breast', and 'Reconstruction' were most frequently mentioned in the abstract titles.

Ludwigshafen, Hanover, Leipzig, and Munich contributed the highest number of abstracts.

Network analysis revealed underlying structures and thematic connections in the conference content.

Abstract

Background: Every year, German-speaking experts in plastic, reconstructive, and aesthetic surgery gather to discuss the latest developments at Germany's largest conference for plastic surgery, the joint annual meeting of the German Society of Plastic, Reconstructive and Aesthetic Surgery (DGPRÄC) and the Association of German Aesthetic Plastic Surgeons (VDÄPC). Since the topics of the conference have a lasting impact on the practice and research of plastic surgery, an examination of the presented content provides insight into the driving developments in plastic surgery in Germany.

Materials and methods: We conducted a retrospective network analysis of all abstract titles from the DGPRÄC and VDÄPC annual meeting in 2023. Data were extracted regarding titles, language, author, and place of origin, and the titles were categorized into the four pillars of the specialty. The titles were standardized and subjected to network analysis.

Results: A total of 299 titles from 281 lectures and 18 instructional courses were analyzed. After preprocessing the data, 2463 words with 9384 connections qualified for network analysis. The most frequently mentioned keywords throughout the congress were 'Surgery', 'Breast', 'Reconstruction', 'Flap', 'Patient', 'Tissue', and 'Therapy'. Locations contributing the highest number of abstracts were Ludwigshafen, Hanover, Leipzig, and Munich.

Conclusion: In the era of big data, network analysis provides the ability to identify underlying structures and nodes in multidimensional, complex datasets. This study demonstrates the useful application of network analysis to identify thematic focuses and connections at the current DGPRÄC and VDÄPC annual meeting. Sites of intensified research could thus be identified.

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