A Case of Bromism Influenced by Use of Artificial Intelligence
Open accessAbstract
Ingestion of bromide can lead to a toxidrome known as bromism. While this condition is less common than it was in the early 20th century, it remains important to describe the associated symptoms and risks, because bromide-containing substances have become more readily available on the internet. We present an interesting case of a patient who developed bromism after consulting the artificial intelligence–based conversational large language model, ChatGPT, for health information.
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A recent peer-reviewed case report describes a patient who developed bromism requiring inpatient psychiatric admission after following ChatGPT-derived dietary advice that was contextually defensible but inappropriate when delivered without contraindication framing.
“A recent peer-reviewed case report describes a patient who developed bromism requiring inpatient psychiatric admission after following ChatGPT-derived dietary advice that was contextually defensible but inappropriate when delivered without contraindication framing (n=1; Eichenberger et al. 2025)”
From Medical Fine-Tuning Reshapes, Not Reduces, Patient-Facing AI Risk: A Rubric-Based, LLM-Judge Evaluation Framework (2026) · cites this paper as Eichenberger et al. 2025
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Sallam, M. (2023) · Healthcare · doi:10.3390/healthcare11060887 · Cited by 3,126 · see citing works
Health, T. L. D. (2023) · The Lancet Digital Health · doi:10.1016/s2589-7500(23)00023-7 · Cited by 257 · see citing works
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- Rayamajhi S, Sharma S, Iftikhar H. Unexplained bromide toxicity presenting as hyperchloremia and a negative anion gap. Cureus. 2023;15:e36218. [PMID: 37069868] doi:10.7759/cureus.36218 · DOI
- Monks S, Yen M, Myers J. Bromism: an overlooked and elusive toxidrome from chronic dextromethorphan abuse. Am J Emerg Med. 2020;38:1696.e1. [PMID: 31864868] doi:10.1016/j.ajem.2019.158491 · DOI
- Lugassy DM, Nelson LS. Case files of the medical toxicology fellowship at the New York City Poison Control: bromism: forgotten, but not gone. J Med Toxicol. 2009;5:151-7. [PMID: 19655290] doi:10.1007/BF03161228 · DOI
- Friedman NA, Cantrell FL. Mind the gap: bromism secondary to internet-purchased supplements. Am J Emerg Med. 2022;60:229.e5-6. [PMID: 35953389] doi:10.1016/j.ajem.2022.08.005 · DOI
- Biyajima M, Satoh S, Morikawa T, et al. Bromisoval-induced bromism with status epilepticus mimicking Wernicke's encephalopathy: report of two cases. BMC Neurol. 2022;22:181. [PMID: 35578314] doi:10.1186/s12883-022- 02712-3 · DOI
- Thornton CS, Haws JT. Bromism in the modern day: case report and Canadian review of bromide intoxication. J Gen Intern Med. 2020;35:2459-61. [PMID: 32424782] doi:10.1007/s11606-020-05907-x · DOI
- Dalvi APR, Dias RM, Junger WL. ChatGPT in the health sciences: pause and ponder. Environ Health. 2023;22:64. [PMID: 37705054] doi:10.1186/s12940-023-01014-6 · DOI
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Delusional Experiences Emerging From AI Chatbot Interactions or “AI Psychosis”
Hudon, A., & Stip, E. (2025) · JMIR Mental Health · doi:10.2196/85799 · Cited by 88 · see citing works
- Authors
- Eichenberger, A., Thielke, S., & Van Buskirk, A.
- Affiliations
- University of Washington (US)
- University of Washington, Seattle, Washington
- ORCID
- Thielke, Stephen
- Venue
- Annals of Internal Medicine: Clinical Cases
- Publisher
- American College of Physicians
- Published
- 2025-08-01
- Volume
- 4
- Issue
- 8
- ISSN
- 2767-7664 (ISSN-L)
- OpenAlex
- W4412983000
- Cited by
- 28
- References
- 2
- Citations by year
- 2026: 19 · 2025: 9
- FWCI
- 24.95
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Annals of Internal Medicine Clinical Cases (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Emergency Medicine › Poisoning and overdose treatments
- Health Sciences › Medicine › Pathology and Forensic Medicine › Historical and Scientific Studies
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Heavy Metal Exposure and Toxicity
- Keywords
- bromism, bromide toxicity, ChatGPT, large language models, artificial intelligence, online health information seeking, online drug sales
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