Background: While the well-being and working conditions of healthcare professionals are increasingly scrutinized, there remains a critical research gap regarding the quality of life and job satisfaction of plastic surgeons in Switzerland. No prior national study has systematically examined these aspects within this specialty. Objective: This study aims to address this gap by evaluating workload, career satisfaction, and quality of life among Swiss plastic surgeons and trainees, thereby providing evidence to inform systemic improvements in the profession. Methods: A national, multilingual online survey was distributed to all members of the Swiss Society for Plastic Surgery and the Association of Young Plastic Surgeons. A total of 102 plastic surgeons responded (response rate: 22.7%). The survey assessed contractual versus actual working hours, work performed during personal time, mental health indicators (e.g., burnout), and career satisfaction. Descriptive and correlational analyses were conducted. Results: The respondents reported an average of 58 actual versus 49 contractual working hours per week, with an additional 8.1 h spent working during leisure time. Burnout symptoms were present in 29%, and 63% experienced work-related stress during their free time. While 42% wished to reduce their workload, 88.7% would still choose the profession again. Career satisfaction averaged 3.66/5, although 35% rated their salary as inadequate. Notably, 79.8% reported work negatively affecting private relationships, despite 82.65% feeling supported by their environment. Conclusion: This first nationwide assessment highlights the high workload and psychological strain faced by Swiss plastic surgeons. Key priorities include targeted burnout prevention, structural workload reduction, enhanced support for work–life integration (especially among women and younger surgeons), and improved compensation. These measures are essential to sustain the well-being of practitioners and ensure long-term quality in surgical care.

Background: Upper and lower extremity lymphedema is a chronic, progressive condition that significantly impairs the quality of life of affected patients. Despite the recently established effectiveness of physical therapy and supermicrosurgical interventions, current guidelines frequently lag behind emerging evidence and commonly do not offer stage-specific treatment algorithms. This gap in evidence-based guidance may prompt clinicians with limited experience to seek support from large language models such as ChatGPT. Objective: Given the potential of artificial intelligence to rapidly integrate emerging research, this study evaluated how clinicians from different professional backgrounds rate the quality and reliability of personalized lymphedema management recommendations generated by ChatGPT. Methods: In this exploratory cross-sectional study, ChatGPT generated treatment recommendations for 6 standardized lymphedema case scenarios. An international panel of 67 participants (resident doctors, board-certified specialists, physiotherapists, and advanced practice nurses) from 34 institutions across 11 countries assessed the recommendations using a modified DISCERN questionnaire with a 9-point agreement scale ranging from 1 (completely disagree) to 9 (completely agree). Ratings were summarized as pooled means with variability measures and compared across clinician groups (residents vs board-certified physicians vs physiotherapists or advanced practice nurses) using group comparison testing. Results: ChatGPT was rated most favorably for diagnostic accuracy and treatment relevance, with higher ratings among residents than board-certified physicians. Residents assigned significantly lower scores for source indication, source currency, and communication of uncertainty. Between-group differences were observed across multiple DISCERN items, consistent with systematically more critical appraisal by experienced specialists. Participants reported moderate to high trust and willingness to consider ChatGPT as a supplementary resource, with more favorable perceptions among younger respondents. Conclusions: Clinicians perceived ChatGPT as potentially useful for preliminary orientation and educational support in lymphedema management, especially for less experienced users. Despite not being blinded, lower ratings in evidence transparency and uncertainty communication, particularly among experienced specialists, suggest that current artificial intelligence outputs should not be used as stand-alone guidance. Future work should test clinically integrated, citation-grounded workflows in prospective settings and evaluate whether they improve decision quality and efficiency.

Background: Breast cancer, irrespective of gender, stands as the most prevalent cancer globally, with an annual estimate of 2.3 million new cases. Surgical intervention, including therapeutic mastectomy (excluding prophylactic procedures), is performed on approximately 28% of patients, necessitating subsequent breast reconstruction. Although implant-based breast reconstruction (IBBR) is frequently employed due to its relative ease compared to autologous methods, it presents a notable risk for complications at mid-term such as peri-prosthetic infections. These complications can lead to implant loss and the eventual compromise of the mastectomy pocket. To address these complications, negative pressure wound therapy with instillation and dwell (NPWTi-d) emerges as a promising rescue intervention, known for its capacity to significantly reduce bacterial load and potentially salvage compromised soft tissues. However, the evidence supporting its effectiveness in infected pockets after mastectomy is currently insufficient. This study aims at investigating the efficacy of NPWTi-d in the management of peri-prosthetic mastectomy pocket infection. Methods: A thorough literature search has been concluded through PubMed, Web of Science, and Cochrane databases up until 18th March 2025 on evaluating NPWTi-d’s ability to manage peri-prosthetic infections and preserve mastectomy pockets for subsequent reconstruction. Furthermore, a meta-analysis on the salvage rate of the mastectomy pocket was carried out, while for other outcomes, a descriptive analysis was applied. Results: Nine studies (n = 230 patients) were included, investigating whether the us NPWTi-d was successful in treating peri-prosthetic infection and preserving the mastectomy pocket for subsequent reconstruction by expander or implant. The pooled salvage rate of the implant-based BR due to the use of NPWTi-d was 86.1% (95%CI: 80.6–91.6%). Preservation of the skin envelope avoided secondary reconstruction after a defined time interval, reducing number and complexity of surgeries and related costs. Conclusions: This innovative surgical approach should be considered in selected cases of infected implants after breast reconstruction in breast cancer centers. However, the actual low level of evidence is based on case series, and it is not possible to define generally accepted recommendations for the use of NPWTi-d to save the mastectomy pocket.

Background: The application of large language model (LLM) in surgical decision-making is rapidly expanding, yet its potential in hand and peripheral nerve surgery remains largely unexplored. This study assessed the diagnostic and therapeutic performance of a large language model (ChatGPT-4o) in scenarios characterized by multiple valid management strategies and absent expert consensus. Methods: Three representative cases—thumb carpometacarpal (CMC I) arthritis, scaphoid nonunion, and carpal tunnel syndrome (CTS)—were developed to reflect frequent conditions in hand surgery with competing but accepted treatment options. Each case was submitted to ChatGPT-4o using a standardized prompt. LLM-generated responses were evaluated by 52 participants (34 board-certified hand surgeons and 18 residents) across diagnostic accuracy, clinical relevance, and completeness. Readability indices, including Flesch–Kincaid Grade Level, were analyzed to assess appropriateness for a medical audience. Results: ChatGPT-4o demonstrated coherent but limited diagnostic accuracy (mean 2.9 ± 1.2 SD), moderate clinical relevance (3.5 ± 1.0 SD), and slightly higher completeness (3.4 ± 1.1 SD). Performance was strongest in the standardized scenario (carpal tunnel syndrome, CTS) and weakest in individualized reasoning (CMC I arthritis). No significant differences were observed between experts and residents (p > 0.05). In higher-level reasoning, ChatGPT-4o performed best in CTS and weakest in CMC I arthritis. Readability confirmed professional-level language (mean Flesch–Kincaid Grade Level: 16.4). Conclusions: ChatGPT-4o shows promise as a supportive tool for diagnostic reasoning and surgical education, particularly where standardized frameworks exist. Its limitations in ambiguous scenarios highlight the ongoing need for expert oversight. Future large language model development should emphasize specialty-specific training and context-aware reasoning to enhance their role in surgical decision support.

Background: Flow couplers (FCs) are increasingly used in microsurgical free tissue transfer to provide continuous, real-time monitoring of venous outflow at the anastomotic site. This systematic review and meta-analysis evaluates the clinical performance of FCs, focusing on diagnostic accuracy and flap outcomes compared with conventional monitoring techniques. Methods: A systematic search of PubMed, Web of Science, and the Cochrane Library was conducted through November 1, 2025, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Clinical studies reporting FC use in free flap reconstruction were included. Data on flap survival, venous thrombosis, complications, and FC diagnostic performance were extracted. Meta-analyses were performed to calculate pooled sensitivity, specificity, and flap failure rates. Results: Eleven studies including 1775 free flaps (876 monitored with FCs) met inclusion criteria. Pooled sensitivity and specificity for detecting flap compromise were 96.5% and 90.9%, respectively. Flap failure occurred in 2.2% of FC-monitored flaps versus 3.1% in controls. FCs showed a high negative predictive value but variable positive predictive value, with false-positive signal losses being frequently caused by technical issues rather than true thrombosis. False negatives were uncommon. Compared with traditional monitoring methods, FCs provided superior continuous venous assessment. Conclusions: FCs are highly sensitive tools for early detection of venous compromise in free flap surgery, particularly in buried reconstructions. However, limited specificity and inability to detect arterial insufficiency support the use of multimodal monitoring strategies. Standardized protocols and technical expertise are essential to minimize false positives and optimize flap monitoring outcomes.

This exploratory study investigates the feasibility and diagnostic value of high-resolution peripheral quantitative computed tomography (HR-pQCT) in detecting structural and microarchitectural changes in lunate avascular necrosis (AVN), or Kienböck’s disease. Five adult patients with unilateral AVN underwent either MRI or CT, alongside HR-pQCT of both wrists. Imaging features such as subchondral remodeling, joint space narrowing, and bone fragmentation were assessed across modalities. HR-pQCT detected at least one additional pathological feature not seen on MRI or CT in four of five patients and revealed early subchondral changes in two contralateral asymptomatic wrists. Quantitative measurements of bone volume fraction (BV/TV) further indicated altered trabecular structure correlating with disease stage. These findings suggest that HR-pQCT may offer enhanced sensitivity for early-stage AVN and better delineation of disease extent, which is critical for informed surgical planning. While limited by small sample size, this study provides preliminary evidence supporting HR-pQCT as a complementary imaging tool in the assessment of lunate AVN, with potential to improve early detection, staging accuracy, and individualized treatment strategies.