A Systematic Review of Questionnaires Assessing Patient Satisfaction in Plastic Surgery: Tools, Topics, and Surgical Types.

Background: Patient satisfaction is crucial for evaluating healthcare services, including plastic surgery. This systematic review aims to analyze questionnaires assessing patient satisfaction in plastic surgery, identifying their strengths and weaknesses to improve outcomes and enhance the quality of care. Methods: A comprehensive literature search was conducted using electronic databases. Studies were included if they were original research articles, written in English, and focused on patient satisfaction questionnaires in plastic surgery. Data extraction and descriptive statistics were used to summarize the data. Results: A total of 105 studies were included. General/overall satisfaction was the most common topic addressed (99.04%). Cosmetic outcomes were the most frequently assessed category (34.3%). Breast reconstruction was the most common procedure (33.3%). Most studies used a combination of generic and procedure-specific questionnaires (45.71%). The most frequently used measurement tools were BREAST-Q and self-developed questionnaires, each accounting for 28.57% and 27.61%. Conclusions: This review provides a comprehensive analysis of patient satisfaction questionnaires in plastic surgery, emphasizing the importance of a holistic approach and well-established, validated tools. The findings contribute to improving plastic surgery outcomes and enhancing the quality of care. Future research should refine assessment tools to address patients' needs and promote patient-centered outcomes in plastic surgery.

Microvascular Thrombosis in Celiac Disease: Is Free Flap an Option? Case Presentation and Literature Review.

Celiac disease is an autoimmune disease that occurs due to gluten intolerance. The prevalence of breast cancer among celiac disease patients is the same as in the general population. It is of note that breast cancer is the most common type of cancer in women. Following mastectomy, these patients visit plastic surgeons for breast reconstruction. Based on various factors, autologous reconstruction using abdominal-based flaps is the best option. Patients with celiac disease have a high incidence of thromboembolic disorders, which may prevent plastic surgeons from doing breast reconstruction with free flaps. We present a case of a patient with celiac disease who underwent a free flap for breast reconstruction with an uneventful course after using our routine postoperative protocol. This case report highlights that patients with celiac disease cannot be denied the option of breast reconstruction with free flaps.

Does tranexamic acid effectively minimise blood loss in cleft palate repair? A rigorous assessment through comprehensive systematic review and meta-analysis.

Cleft palate repair is a common reconstructive procedure that can involve significant blood loss. Tranexamic acid (TXA) has been proposed to minimise blood loss during various surgical procedures, but its effectiveness in cleft palate repair remains unclear. This systematic review and meta-analysis aimed to assess the effectiveness of TXA to reduce postoperative blood loss. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a comprehensive search across multiple databases, including PubMed, Cochrane, and Web of Science, to identify relevant studies published up to September 2023. Only randomised controlled trials (RCTs) were included. Primary outcomes measured were total blood loss, transfusion rates, and postoperative complications. We identified four relevant RCTs, which included 275 cleft palate patients with a mean (range) age of 28.7 (6-65) months. The pooled analysis found no significant difference in duration of surgery (MD -18.40 minutes, p = 0.09), preoperative haemoglobin (MD 0.46 g/dl, p = 0.27), or postoperative haemoglobin (MD 0.07 g/dl, p = 0.86) between TXA and control groups. Intraoperative blood loss was lower with TXA, but with TXA, the difference was not statistically significant (MD -16.63 ml, p = 0.15). TXA significantly improved surgical field visibility (p = 0.004). No adverse events occurred with its use. While no significant differences were found in surgical outcomes with TXA, surgical field visibility significantly improved, and TXA showed a promising safety profile. Larger and higher-quality RCTs are still needed to validate these preliminary findings before TXA can be considered as a standard treatment.

Can a Machine Ace the Test? Assessing GPT-4.0's Precision in Plastic Surgery Board Examinations.

Background: As artificial intelligence makes rapid inroads across various fields, its value in medical education is becoming increasingly evident. This study evaluates the performance of the GPT-4.0 large language model in responding to plastic surgery board examination questions and explores its potential as a learning tool. Methods: We used a selection of 50 questions from 19 different chapters of a widely-used plastic surgery reference. Responses generated by the GPT-4.0 model were assessed based on four parameters: accuracy, clarity, completeness, and conciseness. Correlation analyses were conducted to ascertain the relationship between these parameters and the overall performance of the model. Results: GPT-4.0 showed a strong performance with high mean scores for accuracy (2.88), clarity (3.00), completeness (2.88), and conciseness (2.92) on a three-point scale. Completeness of the model's responses was significantly correlated with accuracy (P < 0.0001), whereas no significant correlation was found between accuracy and clarity or conciseness. Performance variability across different chapters indicates potential limitations of the model in dealing with certain complex topics in plastic surgery. Conclusions: The GPT-4.0 model exhibits considerable potential as an auxiliary tool for preparation for plastic surgery board examinations. Despite a few identified limitations, the generally high scores on key parameters suggest the model's ability to provide responses that are accurate, clear, complete, and concise. Future research should focus on enhancing the performance of artificial intelligence models in complex medical topics, further improving their applicability in medical education.