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应对罕见病诊断的挑战。

Rising to the Challenge of Rare Diagnoses.

作者信息

Venus Kevin, Kwan Janice L, Frost David W

机构信息

Division of General Internal Medicine and Geriatrics, University Health Network and Sinai Health System, Toronto, Canada.

Department of Medicine, University of Toronto, Toronto, Canada.

出版信息

J Gen Intern Med. 2025 Mar;40(4):918-921. doi: 10.1007/s11606-024-09086-x. Epub 2024 Nov 1.

DOI:10.1007/s11606-024-09086-x
PMID:39485586
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11914530/
Abstract

Patients with rare conditions often experience substantial delays between presentation and diagnosis, and some remain undiagnosed. In this Perspective, we outline the many challenges in diagnosing rare conditions in the modern clinical context. We review relevant concepts of diagnostic reasoning as they relate to rare conditions. We present solutions currently available for clinicians to mitigate some of these problems, including facilitating deliberate reflection, utilizing a diagnostic management team, and optimizing diagnostic calibration. Finally, we speculate how technology, such as chatbots and decision support tools enhanced by artificial intelligence, may augment a clinician's ability to diagnose rare conditions in a timely and accurate manner without excessive resource use.

摘要

患有罕见病的患者在出现症状到确诊之间往往会经历相当长的延迟,有些患者仍未得到诊断。在这篇观点文章中,我们概述了在现代临床环境中诊断罕见病所面临的诸多挑战。我们回顾了与罕见病相关的诊断推理的相关概念。我们介绍了目前可供临床医生使用的一些解决方案,以缓解其中的一些问题,包括促进审慎思考、利用诊断管理团队以及优化诊断校准。最后,我们推测诸如聊天机器人和由人工智能增强的决策支持工具等技术如何能够在不过度消耗资源的情况下,增强临床医生及时、准确诊断罕见病的能力。

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The influence of context on diagnostic reasoning: A narrative synthesis of experimental findings.语境对诊断推理的影响:实验结果的叙述性综合。
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Collective Intelligence Increases Diagnostic Accuracy in a General Practice Setting.群体智能提高了一般实践环境下的诊断准确性。
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Impact of diagnostic management team on patient time to diagnosis and percent of accurate and clinically actionable diagnoses.诊断管理团队对患者诊断时间和准确且具有临床可操作性诊断比例的影响。
Diagnosis (Berl). 2024 Jan 30;11(2):132-135. doi: 10.1515/dx-2023-0175. eCollection 2024 May 1.
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Early Experiences of Integrating an Artificial Intelligence-Based Diagnostic Decision Support System into Radiology Settings: A Qualitative Study.将基于人工智能的诊断决策支持系统整合到放射科环境中的早期经验:一项定性研究。
Stud Health Technol Inform. 2023 Oct 20;309:240-241. doi: 10.3233/SHTI230787.
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ChatGPT in medicine: an overview of its applications, advantages, limitations, future prospects, and ethical considerations.医学领域的ChatGPT:其应用、优势、局限性、未来前景及伦理考量概述
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Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicine.GPT-4作为医学人工智能聊天机器人的益处、局限性和风险
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ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns.ChatGPT在医学教育、研究与实践中的应用:对其前景与合理担忧的系统评价
Healthcare (Basel). 2023 Mar 19;11(6):887. doi: 10.3390/healthcare11060887.
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Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models.ChatGPT在美国医师执照考试中的表现:使用大语言模型进行人工智能辅助医学教育的潜力。
PLOS Digit Health. 2023 Feb 9;2(2):e0000198. doi: 10.1371/journal.pdig.0000198. eCollection 2023 Feb.
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Diagnostic delay in rare diseases: data from the Spanish rare diseases patient registry.罕见病诊断延迟:来自西班牙罕见病患者登记处的数据。
Orphanet J Rare Dis. 2022 Nov 17;17(1):418. doi: 10.1186/s13023-022-02530-3.
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Bridging the feedback gap: a sociotechnical approach to informing clinicians of patients' subsequent clinical course and outcomes.弥合反馈差距:一种告知临床医生患者后续临床病程及结果的社会技术方法。
BMJ Qual Saf. 2021 Jul;30(7):591-597. doi: 10.1136/bmjqs-2020-012464. Epub 2021 May 6.