Emerging Trends in Virtual Surgical Planning for Orthognathic Surgery: A Global Overview of Research and Publication Patterns

Purpose: Anticipating trends and pursuing innovative ideas are imperative for the advancement of science. The objective of this study was to conduct a bibliometric analysis of 3-dimensional virtual simulation in orthognathic surgery, explore its implications for clinical practice, and identify future publication trends through digital tools. Methods: This study employed a retrospective bibliometric analysis using data obtained from the Web of Science database. The search strategy focused on articles related to orthognathic surgery and virtual simulation techniques. RStudio and bibliometrix tools were used to data mining. The independent variables retrieved from digital analysis were the emerging themes related to virtual planning in orthognathic surgery. The trends that we identified were facial esthetics, digital workflow, personalized treatments, and complex cases. The primary outcome variable was the number of publications dedicated to virtual simulation in orthognathic surgery, along with secondary outcomes such as citation rates, language of publication, country of origin, institutional affiliations, and emerging research themes. Covariates included variables related to publication characteristics, author affiliations, and geographic distribution of publication tests, and graphical representation techniques. Statistical significance was set at a 95% confidence Results: A comprehensive analysis of 987 articles reveals the impact of included authors, with a mean h-index of 62 (SD = 18.4). The analysis further illuminates a discernible upward trend in publications on this subject, showcasing a linear pattern with a notable R2 value of 0.88 (P = .021). English remains the predominant language of publication, accounting for 97.97% of articles, while contributions hailed from a diverse spectrum of 56 countries. Interestingly, a moderate correlation emerges between publication numbers and gross domestic product per capita (r = 0.30, P = .044) and total area (r = 0.30, P = .032), whereas a more substantial correlation is evident with total population (r = 0.61, P = .034). Notably, the most cited article amassed 254 citations. Furthermore, a Pearson correlation coefficient of 0.97 underscores the correlation between citation density and the year of publication.