Free hemi-hamate arthroplasty: A review of donor site outcomes.

Introduction: The use of the dorsal hamate as a free osteochondral bone graft or vascularized bone flap has become the mainstay for large, comminuted middle phalanx volar lip fractures. To date, few studies have been conducted in the assessment of donor site morbidity for the hemi-hamate graft or flap, and none have discussed modes of repair or reconstruction of this donor site. Methods: A retrospective analysis of 14 hemi-hamate arthroplasty (HHA) procedures, including 6 vascularized and 8 non-vascularized grafts, from two surgeons was performed. Four hamate defect reconstruction techniques were utilized: no formal reconstruction, autologous bone grafting, gel foam, or synthetic bone substitute. The dorsal capsule was repaired with either extensor retinaculum grafting or by direct closure. Wrist range of motion, pain scores, and radiographic alignment were assessed. Results: At 6 months follow-up, all patients achieved full, pain-free wrist motion compared to the uninjured side, with visual analog scale pain scores of 0. Serial radiographs showed maintained carpal alignment without instability or subluxation. No differences based on the hamate defect reconstruction method or capsular repair technique was demonstrated. Conclusion: Safe return to pain free, unrestricted wrist function is achievable after HHA, regardless of hamate donor site management. Adequate dorsal capsular repair appears critical to prevent instability. Further study is needed to compare techniques, but choice may be guided by surgeon preference in the absence of clear evidence.

Exploring Age-Related Variations in Carpal Bone Volume: Implications for Clinical Practice and Anatomical Understanding.

BACKGROUND: Clinically recognizing the changes in carpal bone volumes and understanding their implications in predicting osteoarthritis (OA) is crucial in clinical practice This study aimed to explore age-related differences in carpal bone volumes across genders, leveraging computed tomography (CT) wrist scans to create 3D surface models of these bones. METHODS: Carpal bone volumes were calculated using the 3D Slicer software from CT scans obtained from Frankston Hospital and additional datasets from Brown and Auckland Universities. The data were statistically processed using Stata V13. Double-sided P-values < .05 were considered statistically significant. The study was conducted in accordance with the ethical standards laid out in the Declaration of Helsinki. RESULTS: A total of 181 patients were analyzed, and 48% of whom were female. A statistically significant positive Spearman correlation (rho = 0.37-0.611, P <.05) was observed between increasing age and the volume of all surveyed carpal bones (scaphoid, lunate, triquetrum, pisiform, hamate, capitate, and trapezium) across genders. Intrauser and interuser reliabilities for 3D Slicer-generated volumes of trapezium and pisiform bones were statistically significant, with Interclass Correlation Coefficient (ICC) values of 0.86 and 0.95, respectively. CONCLUSION: Trapezial volumes increase with age, potentially due to the presence of OA and consequent osteophyte formation. This pattern is more prevalent among older individuals and women. However, the positive correlation between carpal bone volume and age was consistent across all carpal bones and both genders, regardless of OA presence. These findings suggest that carpal bone volume may naturally increase with age, independent of OA-related changes. LEVEL OF EVIDENCE: III, cohort study.

Artificial Intelligence Language Model Performance for Rapid Intraoperative Queries in Plastic Surgery: ChatGPT and the Deep Inferior Epigastric Perforator Flap.

Background: The integration of artificial intelligence in healthcare has led to the development of large language models that can address various medical queries, including intraoperatively. This study investigates the potential of ChatGPT in addressing intraoperative questions during the deep inferior epigastric perforator flap procedure. Methods: A series of six intraoperative questions specific to the DIEP flap procedure, derived from real-world clinical scenarios, were proposed to ChatGPT. A panel of four experienced board-certified plastic surgeons evaluated ChatGPT's performance in providing accurate, relevant, and comprehensible responses. Results: The Likert scale demonstrated to be medically accurate, systematic in presentation, and logical when providing alternative solutions. The mean readability score of the Flesch Reading Ease Score was 28.7 (±0.8), the Flesch-Kincaid Grade Level was 12.4 (±0.5), and the Coleman-Liau Index was 14.5 (±0.5). Suitability-wise, the DISCERN score of ChatGPT was 48 (±2.5) indicating suitable and comprehensible language for experts. Conclusions: Generative AI tools such as ChatGPT can serve as a supplementary tool for surgeons to offer valuable insights and foster intraoperative problem-solving abilities. However, it lacks consideration of individual patient factors and surgical nuances. Nevertheless, further refinement of its training data and rigorous scrutiny under experts to ensure the accuracy and up-to-date nature of the information holds the potential for it to be utilized in the surgical field.

Comparison of large language models in management advice for melanoma: Google's AI BARD, BingAI and ChatGPT.

Large language models (LLMs) are emerging artificial intelligence (AI) technology refining research and healthcare. Their use in medicine has seen numerous recent applications. One area where LLMs have shown particular promise is in the provision of medical information and guidance to practitioners. This study aims to assess three prominent LLMs-Google's AI BARD, BingAI and ChatGPT-4 in providing management advice for melanoma by comparing their responses to current clinical guidelines and existing literature. Five questions on melanoma pathology were prompted to three LLMs. A panel of three experienced Board-certified plastic surgeons evaluated the responses for reliability using reliability matrix (Flesch Reading Ease Score, the Flesch-Kincaid Grade Level and the Coleman-Liau Index), suitability (modified DISCERN score) and comparing them to existing guidelines. t-Test was performed to calculate differences in mean readability and reliability scores between LLMs and p value <0.05 was considered statistically significant. The mean readability scores across three LLMs were same. ChatGPT exhibited superiority with a Flesch Reading Ease Score of 35.42 (±21.02), Flesch-Kincaid Grade Level of 11.98 (±4.49) and Coleman-Liau Index of 12.00 (±5.10), however all of these were insignificant (p > 0.05). Suitability-wise using DISCERN score, ChatGPT 58 (±6.44) significantly (p = 0.04) outperformed BARD 36.2 (±34.06) and was insignificant to BingAI's 49.8 (±22.28). This study demonstrates that ChatGPT marginally outperforms BARD and BingAI in providing reliable, evidence-based clinical advice, but they still face limitations in depth and specificity. Future research should improve LLM performance by integrating specialized databases and expert knowledge to support patient-centred care.

The provision of general surgery in rural Australia: a narrative review.

Rural surgery is most commonly provided by general surgeons to the 29% of people (7 million) living in rural Australia. The provision of rural general surgery to enable equitable and safe surgical care for rural Australians is a multifaceted issue concerning recruitment, training, retention, surgical procedures and surgical outcomes. Sustaining the rural general surgical workforce will be dependent upon growing an increased number of resident rural general surgeons, as well as changed models of care, with a need for ongoing review to track the outcomes of these changes. To increase recruitment, rural general surgical training must improve to be less stressful for trainees and to be incorporated alongside a rural-facing generalist curriculum. Rural general surgical outcomes (excluding some oncology conditions) achieve comparable results to metropolitan centres. Access to, and outcomes of, surgical oncology services continues to be inequitable for rural Australians and should be a major focus for improved service delivery.

Thermal Challenges in Dynamic Infrared Thermography Used for Perforator Mapping.

BACKGROUND: The aim of this study is to investigate the different approaches to thermal challenges, both cold and warm, used in dynamic infrared thermography for reconstructive surgery, and explore whether it affects the success of preoperative perforator mapping. METHODS: Literature was collected from Ovid Medline, Embase, PubMed, and Cochrane. The references of the full-text articles located from the original search were also appraised. Thirteen articles were extracted for the final qualitative analysis. A systematic review was then conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. RESULTS: Thirteen articles looked at a cold challenge, which included airflow cooling, direct contact cooling, and evaporation-based cooling. Two articles investigated warm challenges. One paper used no challenge, suggesting it unnecessary with a highly sensitive camera. All cold challenges were positively supported by a high level of flap perfusion success and/or a high level of correlation with other forms of investigation. CONCLUSION: Cold challenges were overall superior to no challenge and warm challenges; however, this conclusion is limited by the small participant size, the possibility of detection bias, and poor methodology detailing. Airflow cooling-specifically, using a desktop fan to blow air for 2 minutes-was noted to likely cause the least discomfort due to a low cooling capacity yet simultaneously maintain effectiveness and allow for a uniform cooling application. Warm challenges showed less conclusive results and were restricted by lack of studies. This topic would benefit from larger scale studies that compare multiple approaches while using standardized equipment to eliminate confounding factors.

Autologous Fat Grafting in Breast Augmentation: A Systematic Review Highlighting the Need for Clinical Caution.

BACKGROUND: Autologous fat grafting (AFG) is a breast augmentation method for treating volume and contour abnormalities. This systematic review aims to summarize complications, radiologic safety, volume retention, and patient satisfaction associated with AFG. METHODS: The PubMed, Embase, Google Scholar, Cochrane Central Register of Controlled Trials, Wiley library, clinical key/Elsevier, and EBSCO databases were searched for relevant studies from January of 2009 to March of 2022. Articles describing AFG for breast augmentation were selected based on predetermined inclusion and exclusion criteria. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were adhered to, and the study was registered on the International Prospective Register of Systematic Reviews. The Risk of Bias in Nonrandomized Studies of Interventions assessment was used to assess the quality of studies and the risk of bias was measured using the Cochrane Risk of Bias Assessment Tool for Nonrandomized Studies of Interventions. RESULTS: A total of 35 studies comprising 3757 women were included. The average follow-up duration was 24.5 months (range, 1 to 372 months). The overall complication rate was 27.8%, with fat necrosis making up 43.7% of all complications. Average fat volume injected was 300 mL (range, 134 to 610 mL), and average volume retention was 58% (range, 44% to 83%). Volume retention was greater with supplementation of fat with platelet-rich plasma and stromal vascular fraction. The most common radiologic changes were fat necrosis (9.4%) and calcification (1.2%). After 1 year of follow-up, patient satisfaction was, on average, 92% (range, 83.2% to 97.5%). The included studies were of good quality and consisted of a moderate risk of bias. CONCLUSIONS: AFG was associated with an overall complication rate of 27.8%. Additional supplementation of fat with platelet-rich plasma and stromal vascular fraction may improve graft survival. Despite poor volume retention being a persistent drawback, patient satisfaction remains high.

Investigating the impact of innovative AI chatbot on post-pandemic medical education and clinical assistance: a comprehensive analysis.

BACKGROUND: The COVID-19 pandemic has significantly disrupted clinical experience and exposure of medical students and junior doctors. Artificial Intelligence (AI) integration in medical education has the potential to enhance learning and improve patient care. This study aimed to evaluate the effectiveness of three popular large language models (LLMs) in serving as clinical decision-making support tools for junior doctors. METHODS: A series of increasingly complex clinical scenarios were presented to ChatGPT, Google's Bard and Bing's AI. Their responses were evaluated against standard guidelines, and for reliability by the Flesch Reading Ease Score, Flesch-Kincaid Grade Level, the Coleman-Liau Index, and the modified DISCERN score for assessing suitability. Lastly, the LLMs outputs were assessed by using the Likert scale for accuracy, informativeness, and accessibility by three experienced specialists. RESULTS: In terms of readability and reliability, ChatGPT stood out among the three LLMs, recording the highest scores in Flesch Reading Ease (31.2 ± 3.5), Flesch-Kincaid Grade Level (13.5 ± 0.7), Coleman-Lau Index (13) and DISCERN (62 ± 4.4). These results suggest statistically significant superior comprehensibility and alignment with clinical guidelines in the medical advice given by ChatGPT. Bard followed closely behind, with BingAI trailing in all categories. The only non-significant statistical differences (P > 0.05) were found between ChatGPT and Bard's readability indices, and between the Flesch Reading Ease scores of ChatGPT/Bard and BingAI. CONCLUSION: This study demonstrates the potential utility of LLMs in fostering self-directed and personalized learning, as well as bolstering clinical decision-making support for junior doctors. However further development is needed for its integration into education.

Quantification of level I neck lymph nodes for lymph node transfer in lymphedema treatment: an anatomical study and review of literature.

Background: Vascularized lymph node transfer (VLNT) is an effective microsurgical method for the treatment of lymphedema. Knowledge of lymph node quantity and regional anatomy of donor sites are essential for surgery optimization. The aim of the study was to quantify the level I lymph nodes of the neck (submental and submandibular lymph nodes), describe the regional anatomy and review the current literature. Methods: Level I lymph nodes were identified from pathology specimens of 73 patients in Melbourne, Australia who underwent radical, modified, and selective neck dissection were quantified. Level I was further subcategorized into levels IA (submental) and IB (submandibular), with data assessed qualitatively and quantitatively. PubMed, Google Scholar, Science Direct, Cochrane CENTRAL, and trial registries (http://clinicialtrials.gov/) were searched for relevant studies published from infinity to December 2021. Results: A mean of 5.2±2.9 lymph nodes were identified in the level I neck region. Subcategorization into level IA and level IB showed means of 3.7±1.6 and 4.7±3.0 lymph nodes, respectively. No statistical differences were detected regarding patients' gender (P=0.8) and age (P=0.5). Current literature shows level I neck VLNT is a suitable treatment for lymphedema. Conclusions: Level I of the neck offers a consistent quantity of lymph nodes and is suitable for free lymph node transfer. Current literature states VLNT is an effective technique for lymphedema treatment. This study details the regional anatomy of the level I neck lymph nodes, which will assist surgeons to optimize their surgeries and prevent donor-site morbidity.

A History of Innovation: Tracing the Evolution of Imaging Modalities for the Preoperative Planning of Microsurgical Breast Reconstruction.

Breast reconstruction is an essential component in the multidisciplinary management of breast cancer patients. Over the years, preoperative planning has played a pivotal role in assisting surgeons in planning operative decisions prior to the day of surgery. The evolution of preoperative planning can be traced back to the introduction of modalities such as ultrasound and colour duplex ultrasonography, enabling surgeons to evaluate the donor site's vasculature and thereby plan operations more accurately. However, the limitations of these techniques paved the way for the implementation of modern three-dimensional imaging technologies. With the advancements in 3D imaging, including computed tomography and magnetic resonance imaging, surgeons gained the ability to obtain detailed anatomical information. Moreover, numerous adjuncts have been developed to aid in the planning process. The integration of 3D-printing technologies has made significant contributions, enabling surgeons to create complex haptic models of the underlying anatomy. Direct infrared thermography provides a non-invasive, visual assessment of abdominal wall vascular physiology. Additionally, augmented reality technologies are poised to reshape surgical planning by providing an immersive and interactive environment for surgeons to visualize and manipulate 3D reconstructions. Still, the future of preoperative planning in breast reconstruction holds immense promise. Most recently, artificial intelligence algorithms, utilising machine learning and deep learning techniques, have the potential to automate and enhance preoperative planning processes. This review provides a comprehensive assessment of the history of innovation in preoperative planning for breast reconstruction, while also outlining key future directions, and the impact of artificial intelligence in this field.

Exploring the Role of a Large Language Model on Carpal Tunnel Syndrome Management: An Observation Study of ChatGPT.

PURPOSE: Recently, large language models, such as ChatGPT, have emerged as promising tools to facilitate scientific research and health care management. The present study aimed to explore the extent of knowledge possessed by ChatGPT concerning carpal tunnel syndrome (CTS), a compressive neuropathy that may lead to impaired hand function and that is frequently encountered in the field of hand surgery. METHODS: Six questions pertaining to diagnosis and management of CTS were posed to ChatGPT. The responses were subsequently analyzed and evaluated based on their accuracy, coherence, and comprehensiveness. In addition, ChatGPT was requested to provide five high-level evidence references in support of its answers. A simulated doctor-patient consultation was also conducted to assess whether ChatGPT could offer safe medical advice. RESULTS: ChatGPT supplied clinically relevant information regarding CTS, although at a relatively superficial level. In the context of doctor-patient interaction, ChatGPT suggested a diagnostic pathway that deviated from the widely accepted clinical consensus on CTS diagnosis. Nevertheless, it incorporated differential diagnoses and valuable management options for CTS. Although ChatGPT demonstrated the ability to retain and recall information from previous patient conversations, it infrequently produced pertinent references, many of which were either nonexistent or incorrect. CONCLUSIONS: ChatGPT displayed the capability to deliver validated medical information on CTS to nonmedical individuals. However, the generation of nonexistent and inaccurate references by ChatGPT presents a challenge to academic integrity. CLINICAL RELEVANCE: To increase their utility in medicine and academia, large language models must go through specialized reputable data set training and validation from experts. It is essential to note that at present, large language models cannot replace the expertise of health care professionals and may act as a supportive tool.

Use of Artificial Intelligence in the Advancement of Breast Surgery and Implications for Breast Reconstruction: A Narrative Review.

BACKGROUND: Breast reconstruction is a pivotal part of the recuperation process following a mastectomy and aims to restore both the physical aesthetic and emotional well-being of breast cancer survivors. In recent years, artificial intelligence (AI) has emerged as a revolutionary technology across numerous medical disciplines. This narrative review of the current literature and evidence analysis explores the role of AI in the domain of breast reconstruction, outlining its potential to refine surgical procedures, enhance outcomes, and streamline decision making. METHODS: A systematic search on Medline (via PubMed), Cochrane Library, Web of Science, Google Scholar, Clinical Trials, and Embase databases from January 1901 to June 2023 was conducted. RESULTS: By meticulously evaluating a selection of recent studies and engaging with inherent challenges and prospective trajectories, this review spotlights the promising role AI plays in advancing the techniques of breast reconstruction. However, issues concerning data quality, privacy, and ethical considerations pose hurdles to the seamless integration of AI in the medical field. CONCLUSION: The future research agenda comprises dataset standardization, AI algorithm refinement, and the implementation of prospective clinical trials and fosters cross-disciplinary partnerships. The fusion of AI with other emergent technologies like augmented reality and 3D printing could further propel progress in breast surgery.

The Utility of Bone Burring for the Clearance of Locally Advanced Scalp Malignancies: A Scoping Review.

The scalp harbors a range of neoplasms occurring at inordinate rates and associated with poorer outcomes. Its unique anatomy poses surgical challenges, including clear deep margins when resecting these lesions. For malignancies extending to the pericranium, removal of outer cortical cranial bone is ideal and routinely achieved with a burr. This review aims to investigate the literature to ascertain the utility and safety of this technique while highlighting evidence gaps. Methods: A literature search was conducted systematically using MEDLINE, Embase, and PubMed. Articles were reviewed for inclusion, and eligible studies were analyzed for study design, patient and intervention details, and outcome measures. A formal statistical analysis was not conducted. Results: The original search yielded 1506 unique results, and eight studies met the inclusion criteria: four case series, two retrospective analysis of records, two case reports. A number of tumor types were identified, but the burring method used was consistent in all studies. Despite reassuring primary outcome measure results, specifically in terms of local control rates, the overall evidence quality is limited by the nature of the included studies. Few adverse events were reported. Conclusions: Evidence for the oncological efficacy of scalp bone burring remains limited. Although the technique seems relatively safe, further investigation is required into its utility and drawbacks. Future studies should aim to report more technical details and more information about outcomes. It may also be worth comparing burring to alternatives such as outer cortical splitting, curettage, and high-dose curative radiotherapy.

Efficacy and Safety of Different Trapezium Implants for Trapeziometacarpal Joint Osteoarthritis: A Systematic Review and Meta-Analysis.

Background: The trapeziometacarpal joint (TMCJ) is the most common hand joint affected by osteoarthritis (OA), and trapezium implant arthroplasty is a potential treatment for recalcitrant OA. This meta-analysis aimed to investigate the efficacy and safety of various trapezium implants as an interventional option for TMCJ OA. Methods: Web of Science, PubMed, Scopus, Google Scholar, and Cochrane library databases were searched for relevant studies up to May 28, 2022. Preferred Reported Items for Systematic Review and Meta-Analysis guidelines were adhered to, and the protocol was registered in PROSPERO. The methodological quality was assessed by National Heart, Lung, and Blood Institute tools for observational studies and the Cochrane risk of bias tool. Subgroup analyses were performed on different replacement implants; the analysis was done using Open Meta-Analyst software and P values <.05 were considered statistically significant. Results: A total of 123 studies comprising 5752 patients were included. Total joint replacement (TJR) implants demonstrate greater significant improvements in visual analogue scale pain scores postoperatively. Interposition with partial trapezial resection implants were associated with highest grip strength and highest reduction in the Disabilities of the Arm, Shoulder, and Hand (DASH) score. Revision rates were highest in TJR (12.3%) and lowest in interposition with partial trapezial resection (6.2%). Conclusion: Total joint replacement and interposition with partial trapezial resection implants improve pain score, grip strength, and DASH scores more than other implant options. Future studies should focus on high-quality randomized clinical trials comparing different implants to accumulate higher quality evidence and more reliable conclusions.

Evaluation of the Artificial Intelligence Chatbot on Breast Reconstruction and Its Efficacy in Surgical Research: A Case Study.

BACKGROUND: ChatGPT is an open-source artificial intelligence (AI) chatbot that uses deep learning to produce human-like text dialog. Its potential applications in the scientific community are vast; however, its efficacy on performing comprehensive literature searches, data analysis and report writing in aesthetic plastic surgery topics remains unknown. This study aims to evaluate both the accuracy and comprehensiveness of ChatGPT's responses to assess its suitability for use in aesthetic plastic surgery research. METHODS: Six questions were prompted to ChatGPT on post-mastectomy breast reconstruction. First two questions focused on the current evidence and options for breast reconstruction post-mastectomy, and remaining four questions focused specifically on autologous breast reconstruction. Using the Likert framework, the responses provided by ChatGPT were qualitatively assessed for accuracy and information content by two specialist plastic surgeons with extensive experience in the field. RESULTS: ChatGPT provided relevant, accurate information; however, it lacked depth. It could provide no more than a superficial overview in response to more esoteric questions and generated incorrect references. It created non-existent references, cited wrong journal and date, which poses a significant challenge in maintaining academic integrity and caution of its use in academia. CONCLUSION: While ChatGPT demonstrated proficiency in summarizing existing knowledge, it created fictitious references which poses a significant concern of its use in academia and healthcare. Caution should be exercised in interpreting its responses in the aesthetic plastic surgical field and should only be used for such with sufficient oversight. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The effect of chemotherapy on the complication rates of breast reconstruction: A systematic review and meta-analysis.

BACKGROUND: The impact of chemotherapy on complications following breast reconstruction surgery (BRS) is currently inconclusive. This meta-analysis investigates the impact of chemotherapy on complication rates in BRS. METHODS: Preferred Reporting in Systematic Review and Meta-Analysis (PRISMA) guidelines was used to search relevant studies published from January 2006 to March 2022. The complication rates of neoadjuvant systemic therapy (NST) and adjuvant systemic therapy (AST) were analyzed via RevMan software 5.4, and a P value of< 0.05 was considered significant. The quality of selected studies was performed using the Newcastle-Ottawa scale for quality assessment. RESULTS: A total of 18 studies comprising 49,217 patients were included. There was no significant difference in the total complications rate, major complications, or minor complications between NST and BRS or control. The rate of wound dehiscence was higher in the NST group compared with the BRS only group [RR= 1.54, 95% CI, (1.08, 2.18), P = 0.02], and the rate of infection was lower in the NST group compared with the BRS only group, [RR= 0.75, 95% CI, (0.61, 0.94), P = 0.01]. No significant difference in the rates of hematoma, seroma, skin necrosis, and implant loss was detected between NST and AST, or NST with BRS only. No statistically significant differences in total complication rates were observed between flap and implant BRS types (P = 0.88). CONCLUSION: No significant differences between AST and NST were detected for complications. Significantly, NST had more wound dehiscence and less infection rates compared with BRS only groups, possibly reflecting selection bias or issues in the design of reported studies. LEVEL OF EVIDENCE: I.

Artificial or Augmented Authorship? A Conversation with a Chatbot on Base of Thumb Arthritis.

ChatGPT is an open artificial intelligence chat box that could revolutionize academia and augment research writing. This study had an open conversation with ChatGPT and invited the platform to evaluate this article through series of five questions on base of thumb arthritis to test if its contributions and contents merely add artificial unusable input or help us augment the quality of the article. The information ChatGPT-3 provided was accurate, albeit surface-level, and lacks analytical ability to dissect for important limitations about base of thumb arthritis, which would not be conducive to potentiating creative ideas and solutions in plastic surgery. ChatGPT failed to provide relevant references and even "created" references instead of indicating its inability to perform the task. This highlights that as an AI-generator for medical publishing text, ChatGPT-3 should be used cautiously.