Journal of pain and symptom management
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J Pain Symptom Manage · Dec 2024
Optimizing the Dosing Regimen During Rotation From Subcutaneous to Transdermal Administration of Fentanyl.
Subcutaneous (SC) administration of fentanyl allows for rapid dose titration to treat urgent cancer-related pain. After establishing the optimal fentanyl dose, patients typically rotate towards transdermal (TD) fentanyl patches. Continuing the SC fentanyl up to 12h after application of the patch led to elevated fentanyl concentrations and fentanyl-related toxicities. Based on these findings, and simulations using a pharmacokinetic (PK) model, SC fentanyl administration was discontinued immediately following the application of the patch. ⋯ The updated rotation scheme, implying a 1:1 dose conversion and discontinuation of SC fentanyl directly after rotation, resulted in equivalent fentanyl exposure pre and post-rotation. Moreover, the dosing regimen showed to be safe and efficacious during rotation. The new dosing regimen when rotating from SC to TD fentanyl can be effectively and safely implemented in routine palliative care.
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J Pain Symptom Manage · Dec 2024
Randomized Controlled TrialCulturally Adapted RN-MD Collaborative SICP-Based ACP: Feasibility RCT in Advanced Cancer Patients.
Cultural adaptation is essential for optimizing programs centered around autonomy, such as the Serious Illness Care Program (SICP), especially for populations valuing family-involved decision-making. ⋯ Despite not meeting the targeted completion rate, the intervention group demonstrated enhanced spiritual well-being, QOL, and ACP progress. Our findings suggest revisions to the intervention manual to improve feasibility and to progress to an efficacy-focused randomized controlled trial.
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J Pain Symptom Manage · Dec 2024
ReviewArtificial Intelligence and Machine Learning in Cancer Pain: A Systematic Review.
Pain is a challenging multifaceted symptom reported by most cancer patients. This systematic review aims to explore applications of artificial intelligence/machine learning (AI/ML) in predicting pain-related outcomes and pain management in cancer. ⋯ Implementation of AI/ML tools promises significant advances in the classification, risk stratification, and management decisions for cancer pain. Further research focusing on quality improvement, model calibration, rigorous external clinical validation in real healthcare settings is imperative for ensuring its practical and reliable application in clinical practice.