TRV-2026-1505Certified recordPeer-reviewed

LLM-supported self-diagnosis and self-treatment of familial Mediterranean fever: a case report

Large language models (LLMs) are increasingly being used by patients to seek explanations for persistent or unexplained symptoms. However, their impact on real-world diagnostic pathways and patient behavior remains poorly understood. We report the case of a 34-year-old male of Egyptian origin with recurrent episodes of fever, severe migratory abdominal pain, arthralgia, myalgia, and intermittent erythematous skin lesions since early childhood. Despite almost 3 decades of extensive investigations, no unifying dia…

Health · The Trace — both readings · certified 2026-10-15 · v1 · article view · machine-readable

Current reading — gain

After about three decades without a unifying diagnosis, a patient's iterative dialogue with DeepSeek narrowed the differential to familial Mediterranean fever, later confirmed by a specialist, and colchicine stopped his inflammatory attacks.

Current reading — problem

The same chatbot exchange, with confident diagnostic language and actionable treatment information, was followed by independent genetic testing and colchicine self-treatment without specialist review, and liver enzymes rose.

Evidence

Reader signal

How should this claim be treated?

Cite this record

Truvace Impact Record TRV-2026-1505, v1: “LLM-supported self-diagnosis and self-treatment of familial Mediterranean fever: a case report.” Truvace, 2026-10-15. /record/TRV-2026-1505 (accessed at citation time). sha256 352eefcbbade7007…

Calibration history

Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.

  1. Certifiedv1352eefcbbade…

    Certified into the record

Verify this record
How to verify without trusting this page

Fetch the canonical text of any version from /api/record/TRV-2026-1505 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.