An examination of antibiotic administration in septorhinoplasty: A systematic review and meta-analysis.

PURPOSE: Septoplasty and rhinoplasty are common otolaryngological procedures, often combined as septorhinoplasty (SRP), offering aesthetic and functional benefits. These surgeries are believed to potentially risk postoperative infections due to natural bacterial flora in the nares. This study evaluates the effectiveness of prophylactic antibiotics in reducing post-surgical infection complications. MATERIALS AND METHODS: A systematic review was conducted using PubMed, Cochrane, and Web of Science, adhering to PRISMA guidelines, focusing on antibiotic use in septoplasty, rhinoplasty, and SRP. The study included randomized control trials, single/double-blind studies, retrospective chart reviews, and prospective cohort studies, excluding pediatric, non-human research, or studies with inaccessible data. Postoperative infection rates were analyzed utilizing R software as a form of Statistic. RESULTS: From 697 articles, 15 studies were chosen for meta-analysis, involving 2225 patients, with 1274 receiving prophylactic antibiotics and 951 as controls. The meta-analysis indicated an odds ratio of 0.65 (95 % CI: [0.23, 1.89]), showing no significant protective effect of prophylactic antibiotics. DISCUSSION: The study found no significant infection rate reduction with prophylactic antibiotic use. Notable were inconsistencies in study designs, antibiotic administration timing, and varied surgical practices. Antibiotic use risks were considered. Study limitations include potential biases and the retrospective nature of many studies. CONCLUSIONS: This review and meta-analysis found no substantial evidence supporting prophylactic antibiotics' effectiveness in reducing postoperative infection rates in septoplasty, rhinoplasty, and SRP, indicating a need to reevaluate practices and develop evidence-based guidelines. Future research should focus on comprehensive, randomized control studies, covering both preoperative and postoperative stages.

What Goes In, Must Come Out: Generative Artificial Intelligence Does Not Present Algorithmic Bias Across Race and Gender in Medical Residency Specialties.

Objective Artificial Intelligence (AI) has made significant inroads into various domains, including medicine, raising concerns about algorithmic bias. This study investigates the presence of biases in generative AI programs, with a specific focus on gender and racial representations across 19 medical residency specialties. Methodology This comparative study utilized DALL-E2 to generate faces representing 19 distinct residency training specialties, as identified by the Association of American Medical Colleges (AAMC), which were then compared to the AAMC's residency specialty breakdown with respect to race and gender. Results Our findings reveal an alignment between OpenAI's DALL-E2's predictions and the current demographic landscape of medical residents, suggesting an absence of algorithmic bias in this AI model. Conclusion This revelation gives rise to important ethical considerations. While AI excels at pattern recognition, it inherits and mirrors the biases present in its training data. To combat AI bias, addressing real-world disparities is imperative. Initiatives to promote inclusivity and diversity within medicine are commendable and contribute to reshaping medical education. This study underscores the need for ongoing efforts to dismantle barriers and foster inclusivity in historically male-dominated medical fields, particularly for underrepresented populations. Ultimately, our findings underscore the crucial role of real-world data quality in mitigating AI bias. As AI continues to shape healthcare and education, the pursuit of equitable, unbiased AI applications should remain at the forefront of these transformative endeavors.

Tweeting for Success: The Role of Twitter in Enhancing SCImago Journal Rank for Specialty Surgical Journals.

Background The cornerstone of surgical education and practice is the surgical journal, but the ability to disperse the vital information within their pages had previously been limited. The use of Twitter by surgical journals has increased in recent years and has allowed these journals to reach a wider audience than they previously could. In this article, we discuss the role Twitter engagement has on a journal's impact factor, visibility, and prestige. Methods The authors compiled a list of journals using the SciMago Journal and Country rank platform. Included journals' Twitter profiles were then assessed using Twitonomy, an online platform that collects and processes data regarding individual Twitter profiles. Statistical analysis was conducted to determine the relationship between Twitter use and SCImago Journal Rank (SJR). Results Simple linear regression and multiple linear regression models determined that the only variables that had a statistically significant impact on all journals were the age of the Twitter account (p=0.003) and the percentage of retweets (p=0.001). When it comes to specialty-specific journals, further analysis showed that the only significant factor regarding its impact on SJR was the percentage of retweets (p=0.007). Conclusions Surgical journals' regular use of Twitter is important in the dissemination of important information to a wide audience. This article shows that the most important variable to determine the impact and visibility of a surgical journal is the percentage of retweets. Further research should be performed to better understand how to use Twitter and other social media platforms to reach a larger audience.