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Segunda especialidad

Permanent URI for this communityhttps://hdl.handle.net/20.500.14595/821

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    Uterine phantom pain syndrome
    (2024-12-16) Sandra Marisel Botía Pinzón
    Phantom uterus pain is an uncommon phenomenon observed in women following a hysterectomy, where painful sensations resembling menstrual cramps or uterine contractions persist despite the removal of the uterus. This report presents the case of a 34-year-old woman from Bogotá, Colombia, diagnosed with advanced endometrial adenocarcinoma who underwent a radical hysterectomy. The patient developed progressive pelvic pain associated with dyspareunia, suggestive of phantom uterus syndrome. Management included neuromodulators and pelvic nerve blockade. This case highlights the complexity of phantom uterus pain, where neuronal plasticity and neuroinflammatory responses may play crucial roles in the generation and persistence of post-surgical pain symptoms. It underscores the need for individualized therapeutic approaches and a deeper understanding of underlying mechanisms to enhance the quality of life of affected patients.
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    Clinical applications of artificial intelligence in symptom management and decision making in oncologic palliative care: a systematic review
    (Medicine Palliative in Practice (Early publication accepted 09.06.2025), 2025-06-09) Sandra Marisel Botía Pinzón
    Abstract Introduction: Artificial intelligence (AI) is increasingly being integrated into healthcare, offering innovative tools to improve symptom management and support clinical decisionmaking in patients with advanced cancer receiving palliative care (PC). The study aimed to systematically evaluate recent evidence (2021–2024) on the clinical use of AI-based tools for symptom management, prognosis prediction, and clinical decision support in adult oncology patients in PC settings. Methods: A systematic review was conducted following the PRISMA-P 2015 guidelines. Databases searched included PubMed, Scopus, Cochrane Library, BVS, Scielo, and ScienceDirect, using MeSH terms related to AI, cancer, pain, and palliative care. Studies were included if they involved adult oncology patients using AI tools in PC and reported outcomes related to symptom control, clinical decisions, or mortality estimation. Two independent reviewers conducted the selection and methodological quality assessment using STROBE, PRISMA, and CONSORT guidelines. Only studies rated as medium or high quality were included. Results: From an initial pool of 3,018 records, 20 studies were selected. AI applications were grouped into prognosis and mortality prediction (n = 9), symptom identification and monitoring (n = 5), clinical decision support (n = 4), and communication tools (n = 2). Models included neural networks, eXtreme Gradient Boosting (XGBoost), decision trees, natural language processing (NLP), and chatbots. Most studies demonstrated high accuracy in retrospective or real-world clinical settings. Conclusions: AI has shown potential in the early identification of palliative needs, symptom control, and care planning. Prospective validation and implementation studies are needed to ensure ethical and safe integration into palliative care.