Postgraduate medical journal
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To investigate the phenotype of sarcoidosis according to the time when a malignancy is diagnosed (preexisting to the diagnosis of sarcoidosis, concomitant, or sequential) and to identify prognostic factors associated with malignancies in a large cohort of patients with sarcoidosis. ⋯ It is essential to consider the synchronous or metachronous timing of the diagnosis of malignancies in people with sarcoidosis. We found that half of the malignancies were diagnosed after a diagnosis of sarcoidosis, with spleen and bone marrow involvement associated with a four to eight times higher risk of developing hematological malignancies. Key messages What is already known on this topic Malignancies are one of the comorbidities more frequently encountered in people with sarcoidosis What this study adds Malignancies occur in 12% of patients with sarcoidosis Malignancy may precede, coincide with, or follow the diagnosis of sarcoidosis One-third were identified before sarcoidosis, and half were diagnosed after Spleen and bone marrow involvement are risk factors for developing hematological malignancies How this study might affect research, practice or policy Patients with sarcoidosis should be regularly monitored for neoplasms, informed of the increased risk, and educated on early detection. Those with spleen or bone marrow involvement must be closely followed.
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With the advent of artificial intelligence (AI) in healthcare, digital platforms like ChatGPT offer innovative alternatives to traditional medical consultations. This study seeks to understand the comparative outcomes of AI-assisted ChatGPT consultations and conventional face-to-face interactions among infertility patients. ⋯ AI-assisted ChatGPT consultations offer a promising alternative to traditional face-to-face consultations in assisted reproductive medicine. While patient satisfaction was higher and consultation durations were shorter with ChatGPT, further studies are required to understand the long-term implications and clinical outcomes associated with AI-driven medical consultations. Key Messages What is already known on this topic: Artificial intelligence (AI) applications, such as ChatGPT, have shown potential in various healthcare settings, including primary care and mental health support. Infertility is a significant global health issue that requires extensive consultations, often facing challenges such as long waiting times and varied patient satisfaction. Previous studies suggest that AI can offer personalized care and immediate feedback, but its efficacy compared with traditional consultations in reproductive medicine was not well-studied. What this study adds: This study demonstrates that AI-assisted ChatGPT consultations result in significantly higher patient satisfaction and shorter consultation durations compared with traditional face-to-face consultations among infertility patients. Both consultation methods were comparable in terms of patient understanding, demographic distributions, and subsequent actions postconsultation. How this study might affect research, practice, or policy: The findings suggest that AI-driven consultations could serve as an effective and efficient alternative to traditional methods, potentially reducing consultation times and improving patient satisfaction in reproductive medicine. Further research could explore the long-term impacts and broader applications of AI in clinical settings, influencing future healthcare practices and policies toward integrating AI technologies.