Mycobacterium ulcerans(M Ulcerans)infection leads to the debilitating Buruli ulcer(BU),characterized by necrotizing skin and soft tissue lesions.Conventional treatment primarily focuses on an antibiotic regimen,but wo...Mycobacterium ulcerans(M Ulcerans)infection leads to the debilitating Buruli ulcer(BU),characterized by necrotizing skin and soft tissue lesions.Conventional treatment primarily focuses on an antibiotic regimen,but wound management remains paramount to patient recovery.This literature review aims to evaluate the efficacy and benefits of Vacuum Assisted Dressing(VAC)in the treatment and management of BU wounds.A systematic literature search was undertaken using databases such as PubMed,Cinahl,Cochrane database,Joanna Briggs Institute,Medline,Internurse,Nursing&Allied Health database,and Scopus search from January 1995 to December 2023.The key search terms included“Mycobacterium ulcerans”,OR“Buruli ulcer”,AND“vacuum assisted dressing”,“vacuum assisted therapy”,“Vacuum Assisted Dressing”,“negative pressure wound therapy”,and“Negative Pressure Wound Therapy(NPWT)”.The exclusion criteria were animal studies and studies not in the English language.The current literature emphasizes the importance of antibiotic treatment for BU and highlights the skin and soft tissue damage that results in open,infected wounds.However,there is a notable lack of quantitative data on the efficacy of NPWT for treating BU wounds.Early evidence indicates that NPWT might accelerate wound healing,decrease secondary infections,and enhance wound bed readiness for grafting or secondary healing.While more comprehensive quantitative studies are warranted,NPWT emerges as a promising adjunctive therapy in the holistic management of BU wounds,offering benefits that may improve patient outcomes and reduce morbidity.展开更多
The integration of artificial intelligence(AI)into plastic surgery is transforming the field by enhancing precision in preoperative planning,diagnostic accuracy,intraoperative assistance,and postoperative care.AI enco...The integration of artificial intelligence(AI)into plastic surgery is transforming the field by enhancing precision in preoperative planning,diagnostic accuracy,intraoperative assistance,and postoperative care.AI encompasses machine learning,natural language processing,computer vision,and artificial neural networks,each offering unique advancements to surgical practice.This narrative review explores the ethical challenges of AI in plastic surgery,addressing concerns such as data protection,algorithmic bias,transparency,accountability,and informed consent.A comprehensive search adhering to PRISMA guidelines identified 63 studies,with 15 selected for in-depth analysis.Findings indicate significant ethical issues:data privacy needs stringent cybersecurity,biases in AI models must be mitigated,and transparency in AI decision making is essential.The review emphasizes the necessity for updated Health Insurance Portability and Accountability Act(HIPAA)regulations,robust validation mechanisms,and the development of explainable AI models.It also highlights the need for an independent regulatory body to oversee AI integration,ensuring ethical standards and protecting patient welfare.Although AI presents promising benefits,its successful application in plastic surgery hinges on addressing these ethical challenges comprehensively.展开更多
Three-dimensional(3D)printed models offer potential advantages over traditional teaching methods by providing realistic,tactile learning aids.The overall efficacy of 3D printing in plastic surgery education has not be...Three-dimensional(3D)printed models offer potential advantages over traditional teaching methods by providing realistic,tactile learning aids.The overall efficacy of 3D printing in plastic surgery education has not been previously systematically analysed.A review of PubMed,Web of Science,and Embase databases up to October 2023 identified studies using 3D printed models in plastic surgery education.Inclusion criteria were set to select before-after studies or studies comparing 3D printed models to traditional teaching methods.Outcome measures included Likert scales,Multiple choice quest tests or other scoring systems.37 studies met the inclusion criteria.Learners demonstrated enhanced anatomical understanding and procedural knowledge after engaging with 3D models.The comparative studies included in the review further highlight the superiority of 3D models over traditional learning tools,with average increases in test scores and procedural confidence,quantified through Likert scales and multiple-choice questionnaires.Ultimately,the findings of this review suggest that 3D printing enhances learning,making educational experiences more interactive and effective than traditional methods.While costs,accessibility,and a lack of technical expertise may pose challenges,integrating 3D models into training could enhance plastic surgical education.High-quality randomized controlled trials are necessary to confirm these findings and standardise outcomes for broader applications.展开更多
The introduction of generative artificial intelligence(AI)has revolutionized healthcare and education.These AI systems,trained on vast datasets using advanced machine learning(ML)techniques and large language models(L...The introduction of generative artificial intelligence(AI)has revolutionized healthcare and education.These AI systems,trained on vast datasets using advanced machine learning(ML)techniques and large language models(LLMs),can generate text,images,and videos,offering new avenues for enhancing surgical education.Their ability to produce interactive learning resources,procedural guidance,and feedback post-virtual simulations makes them valuable in educating surgical trainees.However,technical challenges such as data quality issues,inaccuracies,and uncertainties around model interpretability remain barriers to widespread adoption.This review explores the integration of generative AI into surgical training,assessing its potential to enhance learning and teaching methodologies.While generative AI has demonstrated promise for improving surgical education,its integration must be approached cautiously,ensuring AI input is balanced with traditional supervision and mentorship from experienced surgeons.Given that generative AI models are not yet suitable as standalone tools,a blended learning approach that integrates AI capabilities with conventional educational strategies should be adopted.The review also addresses limitations and challenges,emphasizing the need for more robust research on different AI models and their applications across various surgical subspecialties.The lack of standardized frameworks and tools to assess the quality of AI outputs in surgical education necessitates rigorous oversight to ensure accuracy and reliability in training settings.By evaluating the current state of generative AI in surgical education,this narrative review highlights the potential for future innovation and research,encouraging ongoing exploration of AI in enhancing surgical education and training.展开更多
The increasing adoption and widespread acceptance of negative pressure wound therapy(NPWT)have paralleled the expansion of its indications in clinical practice.The spectrum of indications for NPWT now extends to encom...The increasing adoption and widespread acceptance of negative pressure wound therapy(NPWT)have paralleled the expansion of its indications in clinical practice.The spectrum of indications for NPWT now extends to encompass soft tissue defects arising from trauma,infection,surgical wound care,and soft tissue grafting procedures.Recent advancements in NPWT devices have introduced various adjuncts,such as instillation of fluids or antibiotics into the wound.These additions empower surgeons to enhance the wound healing environment and contribute to combatting infections more effectively.This review delves into the latest literature addressing the proposed mechanisms underlying NPWT's action,its cost-effectiveness,its impact on patient quality of life,and the essential components necessary for its safe use.The review examines the evidence supporting NPWT's application in managing traumatic extremity injuries,controlling infections,and wound care.While NPWT generally exhibits a low complication rate,surgeons must remain aware of the potential risks linked to its utilization.Moreover,the review explores the widening scope of indications for NPWT,shedding light on prospective avenues for innovation and research in this field.展开更多
This study evaluated three prominent Large Language Models(LLMs)-Google’s AI BARD,Bing’s AI,and ChatGPT-4 in providing patient advice for hand laceration.Five simulated patient inquiries on hand trauma were prompted...This study evaluated three prominent Large Language Models(LLMs)-Google’s AI BARD,Bing’s AI,and ChatGPT-4 in providing patient advice for hand laceration.Five simulated patient inquiries on hand trauma were prompted to them.A panel of Board-certified plastic surgical residents evaluated the responses for accuracy,comprehensiveness,and appropriate sources.Responses were also compared against existing literature and guidelines.This study suggests that ChatGPT outperforms BARD and Bing AI in providing reliable,evidence-based clinical advice,but they still face limitations in depth and specificity.Healthcare professionals are essential in interpreting LLM recommendations,and future research should improve LLM performance by integrating specialized databases and human expertise to advance nerve injury management and optimize patient-centred care.展开更多
文摘Mycobacterium ulcerans(M Ulcerans)infection leads to the debilitating Buruli ulcer(BU),characterized by necrotizing skin and soft tissue lesions.Conventional treatment primarily focuses on an antibiotic regimen,but wound management remains paramount to patient recovery.This literature review aims to evaluate the efficacy and benefits of Vacuum Assisted Dressing(VAC)in the treatment and management of BU wounds.A systematic literature search was undertaken using databases such as PubMed,Cinahl,Cochrane database,Joanna Briggs Institute,Medline,Internurse,Nursing&Allied Health database,and Scopus search from January 1995 to December 2023.The key search terms included“Mycobacterium ulcerans”,OR“Buruli ulcer”,AND“vacuum assisted dressing”,“vacuum assisted therapy”,“Vacuum Assisted Dressing”,“negative pressure wound therapy”,and“Negative Pressure Wound Therapy(NPWT)”.The exclusion criteria were animal studies and studies not in the English language.The current literature emphasizes the importance of antibiotic treatment for BU and highlights the skin and soft tissue damage that results in open,infected wounds.However,there is a notable lack of quantitative data on the efficacy of NPWT for treating BU wounds.Early evidence indicates that NPWT might accelerate wound healing,decrease secondary infections,and enhance wound bed readiness for grafting or secondary healing.While more comprehensive quantitative studies are warranted,NPWT emerges as a promising adjunctive therapy in the holistic management of BU wounds,offering benefits that may improve patient outcomes and reduce morbidity.
文摘The integration of artificial intelligence(AI)into plastic surgery is transforming the field by enhancing precision in preoperative planning,diagnostic accuracy,intraoperative assistance,and postoperative care.AI encompasses machine learning,natural language processing,computer vision,and artificial neural networks,each offering unique advancements to surgical practice.This narrative review explores the ethical challenges of AI in plastic surgery,addressing concerns such as data protection,algorithmic bias,transparency,accountability,and informed consent.A comprehensive search adhering to PRISMA guidelines identified 63 studies,with 15 selected for in-depth analysis.Findings indicate significant ethical issues:data privacy needs stringent cybersecurity,biases in AI models must be mitigated,and transparency in AI decision making is essential.The review emphasizes the necessity for updated Health Insurance Portability and Accountability Act(HIPAA)regulations,robust validation mechanisms,and the development of explainable AI models.It also highlights the need for an independent regulatory body to oversee AI integration,ensuring ethical standards and protecting patient welfare.Although AI presents promising benefits,its successful application in plastic surgery hinges on addressing these ethical challenges comprehensively.
文摘Three-dimensional(3D)printed models offer potential advantages over traditional teaching methods by providing realistic,tactile learning aids.The overall efficacy of 3D printing in plastic surgery education has not been previously systematically analysed.A review of PubMed,Web of Science,and Embase databases up to October 2023 identified studies using 3D printed models in plastic surgery education.Inclusion criteria were set to select before-after studies or studies comparing 3D printed models to traditional teaching methods.Outcome measures included Likert scales,Multiple choice quest tests or other scoring systems.37 studies met the inclusion criteria.Learners demonstrated enhanced anatomical understanding and procedural knowledge after engaging with 3D models.The comparative studies included in the review further highlight the superiority of 3D models over traditional learning tools,with average increases in test scores and procedural confidence,quantified through Likert scales and multiple-choice questionnaires.Ultimately,the findings of this review suggest that 3D printing enhances learning,making educational experiences more interactive and effective than traditional methods.While costs,accessibility,and a lack of technical expertise may pose challenges,integrating 3D models into training could enhance plastic surgical education.High-quality randomized controlled trials are necessary to confirm these findings and standardise outcomes for broader applications.
文摘The introduction of generative artificial intelligence(AI)has revolutionized healthcare and education.These AI systems,trained on vast datasets using advanced machine learning(ML)techniques and large language models(LLMs),can generate text,images,and videos,offering new avenues for enhancing surgical education.Their ability to produce interactive learning resources,procedural guidance,and feedback post-virtual simulations makes them valuable in educating surgical trainees.However,technical challenges such as data quality issues,inaccuracies,and uncertainties around model interpretability remain barriers to widespread adoption.This review explores the integration of generative AI into surgical training,assessing its potential to enhance learning and teaching methodologies.While generative AI has demonstrated promise for improving surgical education,its integration must be approached cautiously,ensuring AI input is balanced with traditional supervision and mentorship from experienced surgeons.Given that generative AI models are not yet suitable as standalone tools,a blended learning approach that integrates AI capabilities with conventional educational strategies should be adopted.The review also addresses limitations and challenges,emphasizing the need for more robust research on different AI models and their applications across various surgical subspecialties.The lack of standardized frameworks and tools to assess the quality of AI outputs in surgical education necessitates rigorous oversight to ensure accuracy and reliability in training settings.By evaluating the current state of generative AI in surgical education,this narrative review highlights the potential for future innovation and research,encouraging ongoing exploration of AI in enhancing surgical education and training.
文摘The increasing adoption and widespread acceptance of negative pressure wound therapy(NPWT)have paralleled the expansion of its indications in clinical practice.The spectrum of indications for NPWT now extends to encompass soft tissue defects arising from trauma,infection,surgical wound care,and soft tissue grafting procedures.Recent advancements in NPWT devices have introduced various adjuncts,such as instillation of fluids or antibiotics into the wound.These additions empower surgeons to enhance the wound healing environment and contribute to combatting infections more effectively.This review delves into the latest literature addressing the proposed mechanisms underlying NPWT's action,its cost-effectiveness,its impact on patient quality of life,and the essential components necessary for its safe use.The review examines the evidence supporting NPWT's application in managing traumatic extremity injuries,controlling infections,and wound care.While NPWT generally exhibits a low complication rate,surgeons must remain aware of the potential risks linked to its utilization.Moreover,the review explores the widening scope of indications for NPWT,shedding light on prospective avenues for innovation and research in this field.
文摘This study evaluated three prominent Large Language Models(LLMs)-Google’s AI BARD,Bing’s AI,and ChatGPT-4 in providing patient advice for hand laceration.Five simulated patient inquiries on hand trauma were prompted to them.A panel of Board-certified plastic surgical residents evaluated the responses for accuracy,comprehensiveness,and appropriate sources.Responses were also compared against existing literature and guidelines.This study suggests that ChatGPT outperforms BARD and Bing AI in providing reliable,evidence-based clinical advice,but they still face limitations in depth and specificity.Healthcare professionals are essential in interpreting LLM recommendations,and future research should improve LLM performance by integrating specialized databases and human expertise to advance nerve injury management and optimize patient-centred care.
