Background: In the evolving field of maxillofacial surgery, integrating advanced technologies like Large Language Models (LLMs) into medical practices, especially for trauma triage, presents a promising yet largely unexplored potential. This study aimed to evaluate the feasibility of using LLMs for triaging complex maxillofacial trauma cases by comparing their performance against the expertise of a tertiary referral center. Methods: Utilizing a comprehensive review of patient records in a tertiary referral center over a year-long period, standardized prompts detailing patient demographics, injury characteristics, and medical histories were created. These prompts were used to assess the triage suggestions of ChatGPT 4.0 and Google GEMINI against the center’s recommendations, supplemented by evaluating the AI’s performance using the QAMAI and AIPI questionnaires. Results: The results in 10 cases of major maxillofacial trauma indicated moderate agreement rates between LLM recommendations and the referral center, with some variances in the suggestion of appropriate examinations (70% ChatGPT and 50% GEMINI) and treatment plans (60% ChatGPT and 45% GEMINI). Notably, the study found no statistically significant differences in several areas of the questionnaires, except in the diagnosis accuracy (GEMINI: 3.30, ChatGPT: 2.30; p = 0.032) and relevance of the recommendations (GEMINI: 2.90, ChatGPT: 3.50; p = 0.021). A Spearman correlation analysis highlighted significant correlations within the two questionnaires, specifically between the QAMAI total score and AIPI treatment scores (rho = 0.767, p = 0.010). Conclusions: This exploratory investigation underscores the potential of LLMs in enhancing clinical decision making for maxillofacial trauma cases, indicating a need for further research to refine their application in healthcare settings.

The present study investigates the impact of the COVID-19 pandemic on the management of Non-Melanoma Skin Cancer (NMSC) in the head and neck region. Conducted at the University Hospital “Le Scotte” in Siena, Italy, the research includes 111 patients treated from 2018 to 2021. The study aims to understand how pandemic-related healthcare changes affected NMSC treatment, focusing on differences in diagnosis and management before and during the pandemic. Methods involved retrospective analysis of patient demographics, clinical characteristics, lesion details, and treatment modalities, using Jamovi software (version 1.6) for statistical analysis. Results revealed the scalp as the most common NMSC site, with Squamous Cell Carcinoma (SCC) being the predominant histotype. A significant rise in Basal Cell Carcinoma (BCC) cases and a reduction in surgery duration were noted during the pandemic. The shift to local anesthesia was more pronounced, reflecting the necessity to adapt to healthcare limitations. Despite the disruptions caused by the pandemic, there was no significant drop in NMSC cases, which is attributed to the noticeable nature of head and neck lesions. In conclusion, this study highlights that the COVID-19 pandemic significantly influenced surgical practices in NMSC management, emphasizing the need for effective healthcare strategies that balance quality patient care with public health safety measures.

Background: The surgical treatment of lymphedema has seen advancements in recent years, with supramicrosurgical lymphaticovenular anastomosis (sLVA) gaining global acceptance. The integration of 3D exoscopes into microsurgery offers potential ergonomic and educational benefits. However, systematic evaluation of their efficacy in sLVA remains limited. Methods: A retrospective cross-sectional study was conducted comparing the use of 3D exoscopes to conventional operating microscopes (OM) in sLVA surgeries. Patient data from January 2019 to January 2024 were reviewed, with demographic, clinical, and surgical outcome variables analyzed. Ergonomic assessments were performed using Rapid Entire Body Assessment (REBA) and Rapid Upper Limb Assessment (RULA), while surgeon satisfaction was evaluated through the Microsurgical Intraoperative Satisfaction and Comfort questionnaire (MISCq). Results: An analysis of 25 patients (OM group: n = 14; exoscope group: n = 11) revealed no significant differences in age, sex, etiology, or surgical site between the two groups. Surgical time, number of incisions, and number of anastomoses showed nonsignificant variations between the OM and exoscope groups. Ergonomic assessments indicated potential benefits with exoscope use, particularly for the assistant surgeon. Survey results demonstrated comparable levels of surgeon satisfaction with both instruments, with no significant differences in image quality, contrast, illumination, magnification, visual field, ergonomic maintenance, or stereoscopic orientation. Conclusions: The study suggests that 3D exoscopes are a valuable tool for sLVA supermicrosurgery, offering comparable outcomes to traditional microscopes with potential ergonomic advantages. Their integration into microsurgical practice may contribute to improved surgical comfort and team performance. Further research is warranted to confirm these findings and explore additional factors such as cost-effectiveness and long-term patient outcomes.

Temporomandibular disorders (TMDs) have been historically linked to symptoms such as tinnitus, hearing loss, and vertigo. The aim of this systematic review is to investigate the association between TMDs and audiological symptoms. Adhering to the PRISMA guidelines, a comprehensive literature search in three databases was performed searching for studies utilizing imaging and audiometric assessments to diagnose TMDs and audiological symptoms. Of the 1153 studies retrived, a total number of 6 studies were included. Although tinnitus was commonly reported among patients with TMDs, objective audiological deficits were not consistently confirmed. The majority of existing studies lack standardized diagnostic methods and the heterogeneity of methodologies and limited sample sizes restricted the feasibility of a meta-analysis. The lack of appropriate instrumental diagnostic tests makes it difficult to draw conclusions about the causal relationship between TMDs and audiological symptoms. Future trials are needed to clarify this clinical association.

Background: Zygomatico-maxillary complex (ZMC) fractures are prevalent facial injuries with significant functional and aesthetic implications. Computer-assisted surgery (CAS) offers precise surgical planning and outcome evaluation. The study aimed to evaluate the application of CAS in the analysis of ZMC fracture outcomes and to propose a reproducible workflow for surgical outcome assessment using cephalometric landmarks. Methods: A retrospective cohort study was conducted on 16 patients treated for unilateral ZMC fractures at the Maxillofacial Surgery Unit of Siena University Hospital (2017–2024). Inclusion criteria included ZMC fractures classified as Zingg B or C, treated via open reduction and internal fixation (ORIF). Pre- and post-operative CT scans were processed for two- and three-dimensional analyses. Discrepancies between CAS-optimized reduction and achieved surgical outcomes were quantified using cephalometric landmarks and volumetric assessments. Results: Out of the 16 patients (69% male, mean age 48.1 years), fractures were predominantly on the right side (81%). CAS comparison between the post-operative and the contralateral side revealed significant asymmetries along the X and Y axes, particularly in the fronto-zygomatic suture (FZS), zygo-maxillary point (MP), and zygo-temporal point (ZT). Computer-assisted comparison between the post-operative and the CAS-simulated reductions showed statistical differences along all three orthonormal axes, highlighting the challenges in achieving ideal symmetry despite advanced surgical techniques. CAS-optimized reductions demonstrated measurable improvements compared to traditional methods, underscoring their utility in outcome evaluation. Conclusions: CAS technology enhances the precision of ZMC fracture outcome evaluation, allowing for detailed comparison between surgical outcomes and virtual simulations. Its application underscores the potential for improved surgical planning and execution, especially in complex cases. Future studies should focus on expanding sample size, refining workflows, and integrating artificial intelligence to automate processes for broader clinical applicability.