Case Report: Intranasal esketamine combined with a form of generative artificial intelligence in the management of treatment-resistant depression.
Alexandre Fraichot, Sophie Favre, Hélène Richard-Lepouriel
Frontiers in psychiatry January 1, 2025 DOI: 10.3389/fpsyt.2025.1536232 via PubMed
Summary
AI-generated from the abstractA 37-year-old patient with treatment-resistant depression received intranasal Esketamine (84 mg) and used ChatGPT-4 to generate images and interpretations of his dissociative experiences, supported by a nurse. Depression severity was measured with the Montgomery-Åsberg Depression Rating Scale (MADRS). The patient achieved remission, with MADRS scores declining by 50% by the third session and indicating mild depression or euthymia in the eight subsequent sessions. The patient reported that the artificial intelligence-generated images and interpretations helped him create a timeline of his experiences. The case report suggests combining intranasal Esketamine with generative artificial intelligence may be effective, but further research is needed.
Study at a glance
| Characteristics | Case report Peer reviewed |
|---|---|
| Sample size | 1 |
| Population | 37-year-old patient with treatment-resistant depression |
| Intervention | Intranasal Esketamine |
| Dose | 84 mg |
| Topics | Depression |
| Keywords | Artificial intelligence Case report Intranasal esketamine |
| Citations | 1 |
| Key finding | Combining intranasal Esketamine with generative artificial intelligence images and interpretations, supported by a nurse, led to remission from depression in a patient with treatment-resistant depression. |
Abstract
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.