RESUMO
BACKGROUND: Amyloidosis, a rare multisystem condition, often requires complex, multidisciplinary care. Its low prevalence underscores the importance of efforts to ensure the availability of high-quality patient education materials for better outcomes. ChatGPT (OpenAI) is a large language model powered by artificial intelligence that offers a potential avenue for disseminating accurate, reliable, and accessible educational resources for both patients and providers. Its user-friendly interface, engaging conversational responses, and the capability for users to ask follow-up questions make it a promising future tool in delivering accurate and tailored information to patients. OBJECTIVE: We performed a multidisciplinary assessment of the accuracy, reproducibility, and readability of ChatGPT in answering questions related to amyloidosis. METHODS: In total, 98 amyloidosis questions related to cardiology, gastroenterology, and neurology were curated from medical societies, institutions, and amyloidosis Facebook support groups and inputted into ChatGPT-3.5 and ChatGPT-4. Cardiology- and gastroenterology-related responses were independently graded by a board-certified cardiologist and gastroenterologist, respectively, who specialize in amyloidosis. These 2 reviewers (RG and DCK) also graded general questions for which disagreements were resolved with discussion. Neurology-related responses were graded by a board-certified neurologist (AAH) who specializes in amyloidosis. Reviewers used the following grading scale: (1) comprehensive, (2) correct but inadequate, (3) some correct and some incorrect, and (4) completely incorrect. Questions were stratified by categories for further analysis. Reproducibility was assessed by inputting each question twice into each model. The readability of ChatGPT-4 responses was also evaluated using the Textstat library in Python (Python Software Foundation) and the Textstat readability package in R software (R Foundation for Statistical Computing). RESULTS: ChatGPT-4 (n=98) provided 93 (95%) responses with accurate information, and 82 (84%) were comprehensive. ChatGPT-3.5 (n=83) provided 74 (89%) responses with accurate information, and 66 (79%) were comprehensive. When examined by question category, ChatGTP-4 and ChatGPT-3.5 provided 53 (95%) and 48 (86%) comprehensive responses, respectively, to "general questions" (n=56). When examined by subject, ChatGPT-4 and ChatGPT-3.5 performed best in response to cardiology questions (n=12) with both models producing 10 (83%) comprehensive responses. For gastroenterology (n=15), ChatGPT-4 received comprehensive grades for 9 (60%) responses, and ChatGPT-3.5 provided 8 (53%) responses. Overall, 96 of 98 (98%) responses for ChatGPT-4 and 73 of 83 (88%) for ChatGPT-3.5 were reproducible. The readability of ChatGPT-4's responses ranged from 10th to beyond graduate US grade levels with an average of 15.5 (SD 1.9). CONCLUSIONS: Large language models are a promising tool for accurate and reliable health information for patients living with amyloidosis. However, ChatGPT's responses exceeded the American Medical Association's recommended fifth- to sixth-grade reading level. Future studies focusing on improving response accuracy and readability are warranted. Prior to widespread implementation, the technology's limitations and ethical implications must be further explored to ensure patient safety and equitable implementation.
RESUMO
BACKGROUND: Mitral valve stenosis can be a highly symptomatic condition with significant complications if left untreated. In such cases, mitral valve replacement with a bioprosthetic or mechanical valve may be a viable solution to prevent progressive disease. Current guidelines do not recommend continued anticoagulation beyond 6 months for patients who have undergone bioprosthetic valve replacement without a separate indication for anticoagulation. With this case discussion we aim to 1) Review the current indications for anticoagulation for bioprosthetic mitral valves in patients without atrial fibrillation and 2) Discuss the constellation of comorbidities that may affect the decision to begin anticoagulation therapy. CASE PRESENTATION: We present a case describing a 55-year-old male with end-stage renal disease, coronary artery disease with coronary artery bypass graft surgery, and bioprosthetic mitral valve replacement 2 years prior with rapid degeneration of the replaced valve and on warfarin without a clear indication for anticoagulation. The patient was admitted for symptomatic, severe mitral stenosis and consideration of transcatheter mitral valve-in-valve replacement. During hospital admission, warfarin was discontinued and replaced with prophylactic anticoagulation. However, 8 days after warfarin cessation an intraoperative transesophageal echocardiography revealed a newly developed large left atrial thrombus leading to cancellation of the planned operation. CONCLUSIONS: This patient developed a left atrial thrombus after discontinuing warfarin in the setting of rapidly deteriorating bioprosthetic valve stenosis and vascular comorbidities. The decision to discontinue warfarin was made in concordance with current guidelines, which do not indicate systemic anticoagulation post 3-6 months after bioprosthetic valve replacement without separate indication for anticoagulation. This case identifies the need to investigate rebound hypercoagulability and further risk stratify comorbidities which may independently increase the risk of clot formation in the setting of severe mitral valve stenosis.
