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个性化医疗的变革:ChatGPT对重症监护病房持续肾脏替代治疗警报管理的贡献。

Personalized Medicine Transformed: ChatGPT's Contribution to Continuous Renal Replacement Therapy Alarm Management in Intensive Care Units.

作者信息

Sheikh Mohammad S, Thongprayoon Charat, Qureshi Fawad, Suppadungsuk Supawadee, Kashani Kianoush B, Miao Jing, Craici Iasmina M, Cheungpasitporn Wisit

机构信息

Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.

Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Samut Prakan 10540, Thailand.

出版信息

J Pers Med. 2024 Feb 22;14(3):233. doi: 10.3390/jpm14030233.

Abstract

The accurate interpretation of CRRT machine alarms is crucial in the intensive care setting. ChatGPT, with its advanced natural language processing capabilities, has emerged as a tool that is evolving and advancing in its ability to assist with healthcare information. This study is designed to evaluate the accuracy of the ChatGPT-3.5 and ChatGPT-4 models in addressing queries related to CRRT alarm troubleshooting. This study consisted of two rounds of ChatGPT-3.5 and ChatGPT-4 responses to address 50 CRRT machine alarm questions that were carefully selected by two nephrologists in intensive care. Accuracy was determined by comparing the model responses to predetermined answer keys provided by critical care nephrologists, and consistency was determined by comparing outcomes across the two rounds. The accuracy rate of ChatGPT-3.5 was 86% and 84%, while the accuracy rate of ChatGPT-4 was 90% and 94% in the first and second rounds, respectively. The agreement between the first and second rounds of ChatGPT-3.5 was 84% with a Kappa statistic of 0.78, while the agreement of ChatGPT-4 was 92% with a Kappa statistic of 0.88. Although ChatGPT-4 tended to provide more accurate and consistent responses than ChatGPT-3.5, there was no statistically significant difference between the accuracy and agreement rate between ChatGPT-3.5 and -4. ChatGPT-4 had higher accuracy and consistency but did not achieve statistical significance. While these findings are encouraging, there is still potential for further development to achieve even greater reliability. This advancement is essential for ensuring the highest-quality patient care and safety standards in managing CRRT machine-related issues.

摘要

在重症监护环境中,准确解读连续性肾脏替代治疗(CRRT)机器警报至关重要。ChatGPT凭借其先进的自然语言处理能力,已成为一种在协助医疗保健信息方面不断发展和进步的工具。本研究旨在评估ChatGPT-3.5和ChatGPT-4模型在解决与CRRT警报故障排除相关问题时的准确性。本研究包括两轮ChatGPT-3.5和ChatGPT-4的回复,以解决由两位重症监护肾病专家精心挑选的50个CRRT机器警报问题。通过将模型回复与重症监护肾病专家提供的预定答案进行比较来确定准确性,并通过比较两轮结果来确定一致性。ChatGPT-3.5在第一轮和第二轮中的准确率分别为86%和84%,而ChatGPT-4在第一轮和第二轮中的准确率分别为90%和94%。ChatGPT-3.5两轮之间的一致性为84%,卡方统计值为0.78,而ChatGPT-4的一致性为92%,卡方统计值为0.88。尽管ChatGPT-4往往比ChatGPT-3.5提供更准确和一致的回复,但ChatGPT-3.5和ChatGPT-4在准确性和一致率之间没有统计学上的显著差异。ChatGPT-4具有更高的准确性和一致性,但未达到统计学显著性。虽然这些发现令人鼓舞,但仍有进一步发展的潜力,以实现更高的可靠性。这一进展对于在处理与CRRT机器相关问题时确保最高质量的患者护理和安全标准至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/10971480/c69f2a56ed02/jpm-14-00233-g001.jpg

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