Chiesa-Estomba Carlos M, Lechien Jerome R, Vaira Luigi A, Brunet Aina, Cammaroto Giovanni, Mayo-Yanez Miguel, Sanchez-Barrueco Alvaro, Saga-Gutierrez Carlos
Department of Otorhinolaryngology, Donostia University Hospital, Biodonostia Research Institute, Osakidetza, 20014, San Sebastian, Spain.
Otorhinolaryngology Department, Faculty of Medicine, Deusto University, Bilbo, Spain.
Eur Arch Otorhinolaryngol. 2024 Apr;281(4):2081-2086. doi: 10.1007/s00405-023-08104-8. Epub 2023 Jul 5.
Sialendoscopy has emerged in the last decades as a groundbreaking technique, offering a minimally invasive approach for exploring and managing salivary gland disorders. More recently, the advent of chatbots, powered by advanced natural processing language and artificial intelligence algorithms, has revolutionized the way healthcare professionals and patients access and analyze medical information and potentially will support soon the clinical decision-making process.
A prospective, cross-sectional study was designed to assess the level of agreement between Chat-GPT and 10 expert sialendoscopists aiming the capabilities of Chat-GPT to further improve the management of salivary gland disorders.
The mean level of agreement was 3.4 (SD: 0.69; Min: 2, Max: 4) for Chat-GPT's answers while it was 4.1 (SD: 0.56; Min: 3, Max: 5) for the group of EESS (p < 0.015). The overall Wilcoxon signed-rank test yielded a significance level of p < 0.026 when comparing the level of agreement between Chat-GPT and EESS. The mean number of therapeutic alternatives suggested by Chat-GPT was 3.33 (SD: 1.2; Min: 2, Max: 5), while it was 2.6 (SD: 0.51; Min: 2, Max: 3) for the group of EESS; p = 0.286 (95% CI - 0.385 to 1.320).
Chat-GPT represents a promising tool in the clinical decision-making process within the salivary gland clinic, particularly for patients who are candidates for sialendoscopy treatment. Additionally, it serves as a valuable source of information for patients. However, further development is necessary to enhance the reliability of these tools and ensure their safety and optimal use in the clinical setting.
唾液腺内镜检查在过去几十年中已成为一项开创性技术，为探索和管理唾液腺疾病提供了一种微创方法。最近，由先进的自然语言处理和人工智能算法驱动的聊天机器人的出现，彻底改变了医疗保健专业人员和患者获取和分析医疗信息的方式，并可能很快支持临床决策过程。
设计了一项前瞻性横断面研究，以评估Chat-GPT与10位唾液腺内镜专家之间的一致性水平，旨在评估Chat-GPT进一步改善唾液腺疾病管理的能力。
Chat-GPT答案的平均一致性水平为3.4（标准差：0.69；最小值：2，最大值：4），而专家内镜唾液腺外科医生组的平均一致性水平为4.1（标准差：0.56；最小值：3，最大值：5）（p < 0.015）。比较Chat-GPT和专家内镜唾液腺外科医生组的一致性水平时，总体Wilcoxon符号秩检验的显著性水平为p < 0.026。Chat-GPT建议的治疗替代方案的平均数量为3.33（标准差：1.2；最小值：2，最大值：5），而专家内镜唾液腺外科医生组为2.6（标准差：0.51；最小值：2，最大值：3）；p = 0.286（95%置信区间 - 0.385至1.320）。
Chat-GPT是唾液腺临床临床决策过程中的一个有前途的工具，特别是对于唾液腺内镜治疗候选患者。此外，它是患者的宝贵信息来源。然而，需要进一步发展以提高这些工具的可靠性，并确保它们在临床环境中的安全性和最佳使用。
