Percorrer por autor "Alves, Paulo"
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- Abordagem à pessoa com lesões de pele associadas à humidadePublication . Almeida, Armando; Sousa, Filomena; Grilo, Liliana; Alves, Paulo; Ramos, PauloA preservação da integridade cutânea está considerada, à luz dos conhecimentos atuais, como um forte indicador da qualidade dos cuidados de saúde prestados, nomeadamente ao nível da prevenção de lesões. As Lesões de Pele Associadas à Humidade (LPAH) são causadas pela prolongada exposição da pele a fluidos e seus constituintes, de várias fontes. Existe um conjunto de mecanismos que interagem entre si, de forma a manter a homeostasia cutânea, impedindo a sua lesão. Contudo, em situações agudas ou crónicas, este equilíbrio fica comprometido e é necessária a intervenção externa para a prevenção e tratamento das lesões cutâneas. A APTFeridas elaborou este documento, com o apoio da 3M, como guia de orientação para as melhores práticas de prevenção e tratamento de Lesões Associadas à Humidade da Pele. Neste documento, para além de uma revisão da literatura, também encontrará instrumentos que ajudam na prática clínica, constituindo uma mais valia para a melhoria dos cuidados prestados à pessoa em risco ou com lesão de pele associada à humidade.
- Abordagem da pessoa com feridas - Perspectivando a transdisciplinaridade nas equipas de saúdePublication . Malta, Domingos; Alves, Paulo
- Algoritmos clínicos no apoio à tomada de decisão da pessoa com ferida complexa: uma proposta de validaçãoPublication . Marques, Raquel; Lopes, Marcos; Pais-Vieira, Carla; Neves-Amado, João; Alves, PauloIntrodução: As feridas crónicas ou complexas representam um desafio crescente para a saúde pública global, sendo uma das principais causas de morbimortalidade em populações vulneráveis(1,2). A validação é um processo essencial para assegurar a precisão, eficácia e segurança na tomada de decisão clínica(3), especialmente no cuidado a pessoas com feridas complexas, onde algoritmos clínicos desempenham um papel crucial na orientação no plano terapêutico. Objetivos: Avaliar o desempenho de algoritmos clínicos na classificação de tipologia de ferida em comparação com peritos, através da análise de precisão e do F1-score. Analisar a concordância (coeficiente kappa de Fleiss) na identificação de tipologia de ferida e concordância percentual nas recomendações do plano terapêutico. Conclusão: Os algoritmos clínicos identificam UPP e UPV com elevada fiabilidade, embora ainda precisem de ajustes na classificação de UPD. Apesar da concordância moderada entre avaliadores, a forte correspondência com as recomendações reforça o seu potencial como ferramenta de apoio à decisão. Futuras investigações devem focar- se na variabilidade diagnóstica e em estratégias para melhorar a consistência, sobretudo nos casos com menor concordância. Estes resultados sustentam o potencial da classificação de feridas assistida por algoritmos na melhoria da tomada de decisão clínica e dos cuidados prestados aos utentes.
- Amputação abomino-perineal: uso de terapia de pressão negativa na ferida perinealPublication . Miranda, Liliana; Carvalho, Ângela; Costa, Sandra; Martins, Mónica; Amado, João; Alves, PauloA Amputação Abdomino-Perineal (AAP) é a técnica mais eficaz no tratamento da neoplasia do reto baixo e do tumor do canal anal. Sendo uma cirurgia de grande excisão tecidular, associada a grande parte das vezes a radioterapia (RT) prévia à cirurgia, compromete a cicatrização da ferida perineal, que se traduz numa elevada taxa de complicações no pós-operatório imediato (entre 14% a 60%), nomeadamente infeção da ferida operatória e consequente deiscência. A Terapia de Pressão Negativa (TPN) tem surgido como uma opção no tratamento de complicações da ferida cirúrgica, bem como na prevenção das mesmas.
- An international consensus on device-related pressure ulcers: SECURE preventionPublication . Gefen, Amit; Alves, Paulo; Ciprandi, Guido; Coyer, Fiona; Milne, Catherine; Ousey, Karen; Ohura, Norihiko; Waters, Nicola; Worsley, Peter
- Artificial intelligence ethics and challenges in healthcare applications: a comprehensive review in the context of the European GDPR mandatePublication . Amini, Mohammad Mohammad; Jesus, Marcia; Sheikholeslami, Davood Fanaei; Alves, Paulo; Benam, Aliakbar Hassanzadeh; Hariri, FatemehThis study examines the ethical issues surrounding the use of Artificial Intelligence (AI) in healthcare, specifically nursing, under the European General Data Protection Regulation (GDPR). The analysis delves into how GDPR applies to healthcare AI projects, encompassing data collection and decision-making stages, to reveal the ethical implications at each step. A comprehensive review of the literature categorizes research investigations into three main categories: Ethical Considerations in AI; Practical Challenges and Solutions in AI Integration; and Legal and Policy Implications in AI. The analysis uncovers a significant research deficit in this field, with a particular focus on data owner rights and AI ethics within GDPR compliance. To address this gap, the study proposes new case studies that emphasize the importance of comprehending data owner rights and establishing ethical norms for AI use in medical applications, especially in nursing. This review makes a valuable contribution to the AI ethics debate and assists nursing and healthcare professionals in developing ethical AI practices. The insights provided help stakeholders navigate the intricate terrain of data protection, ethical considerations, and regulatory compliance in AI-driven healthcare. Lastly, the study introduces a case study of a real AI health-tech project named SENSOMATT, spotlighting GDPR and privacy issues.
- Artificial intelligence in wound care education: protocol for a scoping reviewPublication . Encarnação, Rúben; Manuel, Tânia; Palheira, Hélder; Neves-Amado, João; Alves, PauloAs healthcare continues evolving in the age of digital technology, the integration of artificial intelligence has emerged as a powerful force, particularly in wound care. The education of healthcare professionals in wound care is crucial for ensuring they acquire the necessary knowledge and skills, optimizing patient outcomes. This paper outlines the protocol for a scoping review with the goal of mapping and analyzing the current scientific evidence regarding the potential impact of artificial intelligence in wound care education. The current protocol follows the JBI methodological framework. The search was conducted in December 2023 in the following databases: CINAHL Complete (via EBSCOhost), MEDLINE (via PubMed), Cochrane Library, Academic Search Complete, Scientific Electronic Library Online (Scielo), Scopus, and Web of Science. Electronics searches were conducted in the Scientific Open Access Scientific Repositories of Portugal (RCAAP) and ProQuest Dissertations and Theses, OpenAIRE, and Open Dissertations databases to access gray literature. Additionally, searches were performed on Google Scholar and specific journals such as the International Wound Journal, Skin Research and Technology, Journal of Wound Care, and Wound Repair and Regeneration. The initial database searches retrieved a total of 11,323 studies. After removing duplicates, a total of 6450 studies were submitted for screening. Currently, 15 studies are included in this review, and data charting and analysis are underway. The findings of this scoping review will likely provide insights into the application of artificial intelligence in wound care education.
- Artificial intelligence in wound care education: scoping reviewPublication . Encarnação, Rúben; Alves, José; Marques, Ana; Neves-Amado, João; Alves, PauloBackground: Artificial intelligence is transforming healthcare education, offering innovative teaching and skill development approaches. However, its implementation and effectiveness in wound care education remain unclear. Objective: To map and analyze the available evidence on the potential impact of artificial intelligence in wound care education, identify knowledge gaps, and provide recommendations for future research. Design/methods: This scoping review followed the Joanna Briggs Institute guidelines for scoping reviews and the PRISMA-ScR guidelines. The search was first conducted in December 2023 and updated on 30 November 2024 across the following databases: CINAHL Ultimate, MEDLINE, Cochrane Library, Academic Search Complete, Scientific Electronic Library Online (Scielo), Scopus, and Web of Science. Grey literature was accessed through Scientific Open Access Scientific Repositories of Portugal (RCAAP), ProQuest Dissertations and Theses, OpenAIRE, and Open Dissertations. Additional searches were performed in Google Scholar and specific journals, including the International Wound Journal, Skin Research and Technology, Journal of Wound Care, and Wound Repair and Regeneration. Eligibility criteria encompassed any study design exploring the use of artificial intelligence in wound care education, published in English, Portuguese, or Spanish, with no restrictions on publication date. Results: This review revealed diverse artificial intelligence applications in wound care education, including adaptive e-learning platforms, virtual and augmented reality simulations, generative artificial intelligence for educational content, and diagnostic and treatment tools. These technologies offer personalized learning experiences, real-time feedback, and interactive engagement to enhance clinical skills. Despite their promise, most studies lacked empirical validation, highlighting significant gaps in integrating artificial intelligence into wound care education. Conclusions: This review highlights artificial intelligence’s transformative potential to revolutionize wound care education by fostering interactive and evidence-based learning environments. This work highlights the need for collaboration among educators, policymakers, and researchers. Future research is needed to ensure effective, ethical, and equitable integration of artificial intelligence in wound care education.
- Artificial intelligence to support clinical judgement in nursing: a scoping review protocolPublication . Alves, José; Azevedo, Rita; Encarnação, Rúben; Marques, Ana; Alves, PauloIntroduction: As artificial intelligence becomes increasingly explored in healthcare, its potential to influence nurses’ cognitive processes—including assessment, reasoning, and decision-making—has garnered growing attention. Nevertheless, the extent to which these technologies effectively support clinical judgment in nursing remains insufficiently understood, particularly regarding epistemological alignment, practical implementation, and documented outcomes.Objectives: To map and characterize the existing literature on how artificial intelligence technologies have been developed, implemented, or evaluated to support clinical judgment in nursing.Methodology: This scoping review follows the JBI guidelines and addresses the question: How has artificial intelligence been used to support clinical judgment in nursing practice? The search will include multiple international databases and grey literature, with no language restrictions, and will cover studies published from January 2015 to June 2025. Article selection will be based on predefined inclusion and exclusion criteria aligned with the JBI methodology. Eligible studies will include those involving nurses or nursing students in which artificial intelligence supports cognitive, interpretative, or reasoning processes related to clinical judgment. The final review will be reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.Conclusion: The proposed scoping review will systematically map and synthesize evidence on how artificial intelligence supports clinical judgment in nursing. It will analyze the types of artificial intelligence technologies used, the cognitive processes targeted, and the contexts of application. By identifying key findings and gaps, this review aims to clarify the potential of artificial intelligence to enhance nurses’ reasoning and decision-making, informing future research and practice.