Adverse Oral Mucosal Reaction to Sublingual Captopril: A Case Report With Exploratory Insights Into AI‐Assisted Clinical Reasoning

AIMS: To describe a probable oral mucosal injury associated with the off-label sublingual administration of captopril in a medically complex patient, and to illustrate the role of structured clinical reasoning in identifying route-related adverse drug reactions, with exploratory insights into AI-assisted reasoning. METHODS AND RESULTS: A 77-year-old patient presented with persistent burning pain and a progressive oral mucosal lesion on the floor of the mouth. Despite appropriate management of local infectious and mechanical factors, symptoms worsened over time. A consistent temporal relationship was observed between lesion exacerbation and repeated sublingual captopril use during hypertensive episodes. Structured clinical reasoning, including iterative causal analysis, supported identification of a probable route-related adverse drug reaction. Discontinuation of sublingual captopril, combined with topical corticosteroid therapy, resulted in complete resolution of the lesion. An exploratory interaction with a large language model was conducted to examine how structured clinical input may influence the coherence and clinical relevance of AI-assisted reasoning. CONCLUSION: Sublingual administration of captopril may cause localized chemical injury to the oral mucosa, particularly in vulnerable patients with complex medical conditions. Recognition of route-specific adverse effects is essential to avoid unnecessary interventions and improve patient outcomes. This case also illustrates that AI-assisted reasoning is highly dependent on the structure and quality of clinical input, supporting its role as a complementary cognitive tool rather than an autonomous diagnostic system.