Evidence map›Paper›PMID 42499297›Full record

ArticleSpecial care in dentistry : official publication of the American Association of Hospital Dentists, the Academy of Dentistry for the Handicapped, and the American Society for Geriatric Dentistry

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

Antônio Roberto Garcia Júnior, Catarina Melquiades Velane, Caroline Akemi Mendes Magario, Paulo Sergio Pina, Carina Domaneschi, Camilla Vieira Esteves

Abstract readCase Reports
In one paragraph

Article in Special care in dentistry : official publication of the American Association of Hospital Dentists, the Academy of Dentistry for the Handicapped, and the American Society for Geriatric Dentistry. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Adverse Oral Mucosal Reaction to Sublingual Captopril: A Case Report With Exploratory Insights Into AI-Assisted Clinical Reasoning.Special care in dentistry : official publication of the American Association of Hospital Dentists, the Academy of Dentistry for the Handicapped, and the American Society for Geriatric Dentistry
    Article
  2. Comment on: "Adverse Oral Mucosal Reaction to Sublingual Captopril: A Case Report With Exploratory Insights Into AI-Assisted Clinical Reasoning".Special care in dentistry : official publication of the American Association of Hospital Dentists, the Academy of Dentistry for the Handicapped, and the American Society for Geriatric Dentistry
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Antônio Roberto Garcia JúniorDepartment of Stomatology, School of Dentistry, University of São Paulo, São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0003-2400-8982
Catarina Melquiades VelaneDepartment of Stomatology, School of Dentistry, University of São Paulo, São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0009-0004-8276-1790
Caroline Akemi Mendes MagarioDepartment of Stomatology, School of Dentistry, University of São Paulo, São Paulo, São Paulo, Brazil.
Paulo Sergio PinaDepartment of Oral Pathology, School of Dentistry, University of São Paulo, São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0001-8205-9935
Carina DomaneschiDepartment of Stomatology, School of Dentistry, University of São Paulo, São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0001-8615-3283
Camilla Vieira EstevesDepartment of Stomatology, School of Dentistry, University of São Paulo, São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0001-9673-2756

Funding

FAPESP 2025/22650-4
6 · The paper itself

Abstract

aimsTo 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

resultsA 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.

conclusionSublingual 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.

Indexed as

Antihypertensive AgentsCaptoprilMouth DiseasesMouth MucosaAdministration, SublingualAgedHumansHypertensionMaleAntihypertensive AgentsCaptoprilartificial intelligencecaptoprilclinical reasoninghypertensionmouth mucosaoral administrationprompt engineeringtreatment outcome

Identifiers

PMID42499297
PMCPMC13401081

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.