Fraichot Alexandre, Favre Sophie, Richard-Lepouriel Hélène
Mood and Anxiety Disorder Unit, Psychiatric Specialties Service, Department of Psychiatry, Geneva University Hospital, Geneva, Switzerland.
Department of Psychiatry, University of Geneva, Geneva, Switzerland.
Front Psychiatry. 2025 Aug 14;16:1536232. doi: 10.3389/fpsyt.2025.1536232. eCollection 2025.
Intranasal Esketamine is an effective rapid-acting antidepressant currently used to treat treatment-resistant depression. Artificial intelligence is another emerging tool in medicine, but little is known about the effectiveness of combining these innovations in psychiatry.
This case report presents the outcome of a 37-year-old patient who received intranasal Esketamine treatment (84 mg) and utilized artificial intelligence (ChatGPT-4) to generate images and interpretations of his experiences with dissociation. This process was conducted in the presence of a nurse who assessed and supported the patient. The Montgomery-Åsberg Depression Rating Scale (MADRS) was used to measure the severity of depression at the beginning of each session.
The patient achieved remission from depression, with MADRS scores declining by 50% in the third session, and the scores indicated mild depression or euthymia in the eight subsequent sessions. The patient reported that incorporating artificial intelligence-generated images and interpretations helped him create a timeline of his experiences at the end of each session.
This case report highlights the potential effectiveness of combining intranasal Esketamine treatment with generative artificial intelligence images and interpretations as part of an integration process. It also emphasizes the importance of having a nurse present to support the process. Further research is needed to determine which patients may benefit most from this combined treatment approach.
鼻内用艾司氯胺酮是一种有效的速效抗抑郁药,目前用于治疗难治性抑郁症。人工智能是医学领域另一种新兴工具,但对于将这些创新方法结合应用于精神病学的有效性,人们了解甚少。
本病例报告介绍了一名37岁患者的治疗结果,该患者接受了鼻内用艾司氯胺酮治疗(84毫克),并利用人工智能(ChatGPT-4)生成其解离体验的图像及解读。此过程在一名对患者进行评估和支持的护士在场的情况下进行。使用蒙哥马利-Åsberg抑郁评定量表(MADRS)在每次治疗开始时测量抑郁严重程度。
患者实现了抑郁缓解,在第三次治疗时MADRS评分下降了50%,且在随后的八次治疗中评分显示为轻度抑郁或心境正常。患者报告称,纳入人工智能生成的图像和解读有助于他在每次治疗结束时梳理自己的经历时间线。
本病例报告强调了将鼻内用艾司氯胺酮治疗与生成式人工智能图像及解读相结合作为整合过程一部分的潜在有效性。它还强调了有一名护士在场支持该过程的重要性。需要进一步研究以确定哪些患者可能从这种联合治疗方法中获益最大。