BACKGROUND Recent advances in artificial intelligence (AI) have enabled development of natural language algorithms capable of generating coherent texts. We evaluated the quality, validity, and safety of this generative AI in preoperative anaesthetic planning. METHODS In this exploratory, single-centre, convergent mixed-method study, 10 clinical vignettes were randomly selected, and ChatGPT (OpenAI, 4.0) was prompted to create anaesthetic plans, including cardiopulmonary risk assessment, intraoperative anaesthesia technique, and postoperative management. A quantitative assessment compared these plans with those made by eight senior anaesthesia consultants. A qualitative assessment was performed by an adjudication committee through focus group discussion and thematic analysis. Agreement on cardiopulmonary risk assessment was calculated using weighted Kappa, with descriptive data representation for other outcomes. RESULTS ChatGPT anaesthetic plans showed variable agreement with consultants' plans. ChatGPT, the survey panel, and adjudication committee frequently disagreed on cardiopulmonary risk estimation. The ChatGPT answers were repetitive and lacked variety, evidenced by the strong preference for general anaesthesia and absence of locoregional techniques. It also showed inconsistent choices regarding airway management, postoperative analgesia, and medication use. While some differences were not deemed clinically significant, subpar postoperative pain management advice and failure to recommend tracheal intubation for patients at high risk for pulmonary aspiration were considered inappropriate recommendations. CONCLUSIONS Preoperative anaesthetic plans generated by ChatGPT did not consistently meet minimum clinical standards and were unlikely the result of clinical reasoning. Therefore, ChatGPT is currently not recommended for preoperative planning. Future large language models trained on anaesthesia-specific datasets might improve performance but should undergo vigorous evaluation before use in clinical practice.

中文翻译：

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通过 ChatGPT-4.0 生成术前麻醉计划：一项混合方法研究。


背景 人工智能 （AI） 的最新进展使能够生成连贯文本的自然语言算法的发展成为可能。我们评估了这种生成式 AI 在术前麻醉计划中的质量、有效性和安全性。方法 在这项探索性、单中心、收敛混合方法研究中，随机选择 10 个临床小插曲，并提示 ChatGPT （OpenAI， 4.0） 制定麻醉计划，包括心肺风险评估、术中麻醉技术和术后管理。一项定量评估将这些计划与 8 名高级麻醉顾问制定的计划进行了比较。评审委员会通过焦点小组讨论和主题分析进行定性评估。使用加权 Kappa 计算心肺风险评估的一致性，其他结局的描述性数据表示。结果 ChatGPT 麻醉计划与顾问计划的一致性不同。ChatGPT、调查小组和裁决委员会经常在心肺风险评估上存在分歧。ChatGPT 的答案是重复的，缺乏多样性，对全身麻醉的强烈偏好和缺乏局部区域技术证明了这一点。它还显示关于气道管理、术后镇痛和药物使用的不一致选择。虽然一些差异被认为没有临床意义，但低于标准的术后疼痛管理建议和未推荐肺误吸高风险患者进行气管插管被认为是不合适的建议。 结论 ChatGPT 生成的术前麻醉计划并未始终符合最低临床标准，不太可能是临床推理的结果。因此，目前不建议将 ChatGPT 用于术前计划。未来在麻醉特异性数据集上训练的大型语言模型可能会提高性能，但在用于临床实践之前应经过严格的评估。